Copyright by Roberto Ulises Cofresi 2018
The Dissertation Committee for Roberto Ulises Cofresi Certifies that this is the approved version of the following Dissertation:
Attenuating enduring alcohol cue reactivity via extinction during memory reconsolidation
Committee:
Rueben Gonzales, Supervisor
Hongjoo Lee
Marie Monfils
Nadia Chaudhri
Kim Fromme
Attenuating enduring alcohol cue reactivity via extinction during memory reconsolidation
by
Roberto Ulises Cofresi
Dissertation Presented to the Faculty of the Graduate School of The University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
The University of Texas at Austin August 2018 Dedication
I dedicate this dissertation to every person who has been or will be harmed by alcohol abuse and/or alcoholism. I truly hope the preclinical work presented here can inform clinical research and/or practice in a meaningful way.
Acknowledgements
First, I would like to thank the members of my dissertation committee for helping me accomplish the first step toward realizing my dream of someday working to answer behavioral neuroscience questions relevant to alcohol use disorder etiology and/or treatment using both human subjects and non-human animal models. Before anyone else, I need to thank Dr. Rueben Gonzales for many things, but above all else, for his faith and patience. He has been my steadfast supporter since I joined his laboratory in summer 2010. Without Dr. Gonzales, I may have not pursued a PhD at all. He helped me cope with a crisis of confidence in my last year of undergraduate that would have otherwise resulted in me abandoning my dream. He has always pushed me to grow as a trainee and been patient with my idiosyncrasies, sometimes-sluggish development, and occasional resistance to change. Moreover, he has fostered my research interests even when they took me away from the shared interest in neurochemistry that originally brought us together. I also need to thank Dr. Hongjoo Joanne Lee. She also pushed me to grow as a trainee and helped me think more critically about my ideas and experiments. Dr. Lee also helped me learn how to cope with unsuccessful fellowship and grant applications. Finally, she helped me chart a clearer course for myself in life and science. Without Dr. Lee, I may have quit my PhD. I also want to thank Dr. Marie Monfils for exposing me to interesting ideas in behavioral neuroscience, teaching me how to see and share scientific stories instead of simply reporting experimental results, and helping me build confidence in my ideas and writing. I feel lucky to have worked with a “rockstar” whose work has invigorated research on exposure-based therapies for behavioral disorders involving maladaptive associative memory. Next, I want to thank Dr. Nadia Chaudhri for advising and mentoring me from v afar. As one of the few alcohol researchers working on non-human animal models of enduring alcohol cue reactivity and its neurobiology, her feedback on my ideas and work across the last 4 years were critical to my developing interest in alcohol cue reactivity. Finally, I want to thank Dr. Kim Fromme for believing in me and my ability to make the jump from “mice to men” during my last year of graduate school. She helped me think about my ideas from a different perspective and pointed me to scientific literatures relevant to my work that I would have otherwise never discovered. I especially want to thank Dr. Fromme for helping me secure a post-doctoral fellowship position where I will learn how to study alcohol cue reactivity in human subjects. Without Dr. Fromme, I may not have taken the next step toward realizing my dream. Second, I want to thank Dr. Regina Mangieri, who was my first mentor at the University of Texas at Austin and provided my initial training in the laboratory of Dr. Gonzales. She fostered a budding interest in behavioral neuroscience research early in my undergraduate years and has continued to serve as a mentor and friend since then. Third, I would like to thank my wife, Sandie Keertstock, who kept me from burning out in the past year by forcing me to make time for family and friends, food, fun, rest, and relaxation. Fourth, I would like to thank my best friend, Taylor Allen for teaching me to accept help when I need it, for reminding me to stay open to new experiences, and who has helped me grow as a person across my undergraduate and graduate years. Fifth, I would like to thank Lauren MacKnight, Colette Clendaniels, Geoff Dilly, Nicholas Karasik, Suzanne Lewis, Anna Warden, Alisa Baron, Chantal Ramirez, and Lina Gonzalez as well as Drs. Elizabeth Smith, Rheall Roquet, Laura Ferguson, Ashley Vena, and Shannon Zandy, for stimulating existential, intellectual, and scientific conversations
vi as well as helping me deal with disappointments and frustrations inside and outside academia. Sixth, I also want to thank Dr. Juan Dominguez for his life advice as well as advocacy on behalf of my admission to the Institute for Neuroscience graduate program. I also thank Dr. Laura Colgin for her advocacy. I also want to thank the former and current directors of the Waggoner Center for Alcohol & Addiction Research (WCAAR), Drs. Adron Harris and Robert Messing, for building our research community. Thanks also to Dr. Michaela Marinelli for her interest in and help with my public education projects. I also need to thank staff in the Waggoner Center for Alcohol & Addiction Research, the College of Pharmacy Division of Pharmacology & Toxicology, the College of Liberal Arts Department of Psychology, and the Institute for Neuroscience; especially, Mirna Benhamou, Gloria Fang, and Krystal Phu. Finally, I need to thank Drs. Richard Timmons and Ryan Stork from the University of Texas at Arlington who helped me win a research fellowship from the UT System Louise-Stokes Alliance for Minority Participation (LSAMP) without which I would never have approached the laboratory of Dr. Rueben
Gonzales during the summer 2010. Seventh, I want to thank Drs. Greg Hixon, Nitish Mittal, Ryan Will, and James Reno for helping me, in different ways, to build my proficiency in applied statistical analysis. I also want to thank Drs. James Doherty and John Valenta for teaching me gas chromatographic analysis and various blood ethanol sampling methods. Thanks also to Ms. Suzanne M. Lewis, Ms. Kathleen M. Tuite, Ms. Innsun Park, and Mr. Dylan J. Grote for helping me score videofootage. Suzanne M. Lewis and Kathleen Tuite are also thanked for helping me conduct the pre-conditioning and conditioning phases of experiments. Dylan Grote is also thanked for his help with c-Fos immunohistochemistry. Thanks to Mr. Jarod Chaney, Ms. Lauren Schneider, and Mr. Eric Le, for helping with microscopy and Fos+ vii cell counts. Thanks to Dr. Greg Loney for suggesting the idea to automate sipper site/faceplate contact measurement at the Research Society on Alcoholism Annual Scientific Meeting in 2016. Thanks to Mr. Jonathan Rosenzweig for his help designing, prototyping, and fabricating the frame used to automate sipper site/faceplate contact measurement in conjunction with the Longhorn Maker Studio, the Aerospace Research Machine Shop, the Mechanical Engineering Machine Shop, and Mechanical Engineering Wood Shop. I want to thank Elena Lightfeather, Karen King, Nachi Shukla, and the Animal Resources Center (ARC) husbandry staff for working around my experiment schedules. I also want to thank the Custodial Services team that works the ARC for saying hello me every morning, asking me about my progress in school, and reminding me to relax sometimes. Eight, I am also exceptionally grateful to my family and friends, especially my mother Marybel Bonilla, stepfather Manuel Pesante, and maternal uncle Wilfredo Bonilla for pushing me to challenge myself in school and pursue higher education. Thank you also to my father Bernardo Cofresi for calling me every week from Puerto Rico and planning his visits to Texas around my experiment schedule. Ninth, I want to thank the National Institute of Health (NIH) and the National Institute for Alcohol Abuse and Alcoholism (NIAAA). Specifically, I want to thank the Alcohol Training Grant (ATG) (NIAAA T32AA007471) including the trainee selection committee as well as present and past administrators (especially Anita Mote). The ATG fellowship enabled me to fully immerse myself in the training opportunities at the University of Texas at Austin. I also thank the NIAAA for my supervisor’s funding (NIAAA R37AA11852), which allowed me to conduct all of the experiments described in this work. The National Science Foundation (NSF) also played an important role early in my career by funding the University of Texas System Louise-Stokes Alliance for Minority viii Participation (LSAMP), which provided the undergraduate research experience opportunity to me that landed me in my supervisor’s lab. Funding sources were not involved in study design, collection, analysis, interpretation, manuscript preparation, of the decision to submit any of the work for publication in scientific journal.
ix Abstract
Attenuating enduring alcohol cue reactivity via extinction during memory reconsolidation
Roberto Ulises Cofresi, PhD The University of Texas at Austin, 2018
Supervisor: Rueben Gonzales
One of the ways the brain can adapt to repeated alcohol intoxication is to learn about predictive environmental cues such as the sight, smell, and taste of an alcoholic beverage. Over a person’s drinking history, these cues can become associated with alcohol’s post-ingestive pharmacology and acquire the ability to elicit affective, behavioral, and physiological reactions that anticipate alcohol availability, access, and/or intoxication. This reactivity to alcohol-associated cues may facilitate problematic alcohol use and promote the progressive loss of control over alcohol use that typifies alcohol use disorder (AUD). Reactivity to alcohol cues before treatment has been linked to the course and severity of AUD. People suffering from AUD may benefit from cue exposure therapy (CET), which involves systematic exposure to these cues without subsequent alcohol ingestion, viz., cue extinction. However, many people do not benefit from cue extinction, and even for those who do, the benefit is limited. Enduring reactivity to alcohol cues, even after CET, has been linked to risk for relapse to AUD. One of the reasons alcohol cue reactivity is believed to be resistant to treatment is that cue extinction does not undo or erase the original cue-alcohol associative memory. In fact, in most cases, cue extinction is x believed to favor the formation of a new response-inhibiting memory that must compete for expression with the original response-exciting memory. However, it may be possible to update the existing alcohol-associated cue memory by conducting behavioral treatments such as CET during an inducible period of memory instability known as the memory reconsolidation window. I set out to test this idea. Using a novel preclinical rodent model of alcohol cue reactivity that I developed and characterized as part of my dissertation, I found that alcohol cue reactivity was resistant to standard extinction, but persistently attenuated after extinction during the memory reconsolidation window. I hope that these promising initial findings prompt more work into the development of memory reconsolidation-based behavior updating approaches to CET in order to improve AUD treatment outcomes.
xi Table of Contents
List of Figures ...... xxiii
Chapter 1. Introduction ...... 1
1 Alcohol use, use disorder, and & the role of cues...... 1
1.1 Alcohol use prevalence & consequences ...... 1
1.3 Prevalence of alcohol use disorder (AUD) ...... 2
1.4 AUD recovery and relapse rate ...... 3
1.5 AUD treatment seeking and post-treatment relapse rate ...... 4
1.6 Relapse and alcohol-related cues...... 5
1.7 Conclusions ...... 6
2 Explaining cue reactivity, in general: learning & non-learning accounts ...... 7
2.1 Learning-based accounts ...... 7
2.1.1 Associative learning ...... 7
2.1.1.1 The classical/pavlovian conditioning framework ...... 9
2.1.1.2 Conditional and unconditional stimuli (CS, US) ...... 9
2.1.1.3 Conditional and unconditional reactivity (CR, UR) ...... 10
2.1.1.4 Determinants of CR: the US...... 10
2.1.1.5 Determinants of CR: the CS ...... 11
2.1.1.6 Determinants of CR: the CS-US interval ...... 11
2.1.1.7 Determinants of CR: Other ...... 11
2.1.2 Non-associative learning ...... 12
2.1.2.1 Habituation ...... 12
2.1.2.2 Sensitization ...... 13
xii 2.1.3 Testing for associative versus non-associative learning ...... 13
2.1.4 Interactions between associative and non-associative learning processes ...... 14
2.2 Non-learning-based accounts ...... 15
2.2.1 Damage (Illness or injury) ...... 15
2.2.2 Development (maturation)...... 16
2.2.3 Fatigue ...... 16
2.2.4 Sensory Adaption ...... 16
2.3 Role of learning and non-learning processes in human behavior ...... 17
3 Alcohol cue reactivity in humans and non-human animal models ...... 17
3.1 Cue-elicited appetitive responses or “wanting” for alcohol in humans . 17
3.1.1 Increased attentional bias, approach tendency, and self- reported craving...... 18
3.1.2 Increased swallowing and salivation ...... 19
3.1.3 Increased heart rate ...... 20
3.1.4 Increased brain-level cue processing & activity in addiction- relevant circuits ...... 21
3.2 Issues with studying cue reactivity in human subjects & reasons for non-human animal models ...... 23
3.3 Non-human animal models of “wanting” ...... 24
3.3.1 Paradigm parameters & considerations ...... 24
3.3.2 Cue-elicited alcohol seeking behavior in self-administration paradigms ...... 25
3.3.3 Alcohol-paired place preference ...... 26
3.3.4 Alcohol-paired flavor preference ...... 27
3.4 Cue-elicited compensatory responses to alcohol in humans ...... 27 xiii 3.4.1 Increased skin conductance ...... 28
3.4.2 Decreased heart rate ...... 29
3.4.3 Increased vasoconstriction...... 29
3.5 Non-human animal models of cue-elicited compensatory responses to alcohol ...... 30
4 How alcohol cue reactivity drives alcohol use ...... 30
4.1 Pavlovian to instrumental transfer effects in humans ...... 31
4.2 Non-human animal models of Pavlovian to instrumental transfer effects ...... 31
4.3 Conclusions ...... 32
5 Alcohol cue exposure therapy (CET) ...... 32
5.1 Introduction to CET...... 32
5.1.1 History ...... 32
5.1.2 Approaches to CET ...... 33
5.1.3 Basic structure ...... 33
5.1.4 Mechanisms of action ...... 34
5.2 Alcohol-associated stimuli targeted in CET ...... 35
5.3 Measurement considerations...... 35
5.4 Efficacy of alcohol CET ...... 37
5.5 Conclusions ...... 38
6 Efficacy of CET is limited by the intrinsic limitations of extinction...... 38
6.1 Known persistence of reactivity after cue extinction ...... 38
6.2 Explaining persistence from a memory competition perspective...... 39
6.3 Conclusions ...... 40
xiv 7 Improving alcohol CET by applying the neurobiology of learning & memory ... 40
7.1 Basics of memory ...... 40
7.1.1 Forming and maintaining long-term memories ...... 40
7.1.1.1 Consolidation ...... 41
7.1.1.2 Reconsolidation ...... 41
7.2 Harnessing reconsolidation-based memory updating to treat maladaptive behavior ...... 42
7.2.1 Cue memory retrieval + cue extinction: harnessing reconsolidation-based memory updating for CET ...... 43
7.2.1.1 Promising (preclinical) results ...... 44
7.2.1.2 Potential for improving efficacy of alcohol CET ...... 44
7.3 Conclusions ...... 45
8 Testing the potential of memory retrieval + extinction for alcohol CET ...... 45
Chapter 2. Cue memory retrieval + extinction attenuates alcohol cue reactivity in rats .. 47
2.1 Abstract ...... 47
2.2 Introduction ...... 47
2.3 Methods & materials...... 49
2.3.1 Subjects ...... 49
2.3.2 Behavioral Methods ...... 50
2.3.2.1 Apparatus ...... 50
2.3.2.2 Experiment Phase 1: Alcohol Drinking in the Homecage ...... 50
2.3.2.3 Experiment Phase 2: Cue Conditioning ...... 51
2.3.2.4 Experiment Phase 3: Cue Extinction with or without Initial Retrieval ...... 52
2.3.2.5 Experiment Phase 4: Testing ...... 53 xv 2.3.3 Data collection ...... 54
2.3.4 Data analysis ...... 54
2.4 Results ...... 55
2.4.1 Matched history of homecage alcohol drinking...... 55
2.4.2 Matched history of alcohol cue conditioning...... 55
2.4.3 Equivalent extinction of conditioned responses to alcohol predictive cues...... 56
2.4.4 Retrieval-extinction confers protection against early spontaneous recovery and alcohol odor-induced reinstatement...... 57
2.5 Discussion ...... 60
2.6 Figures ...... 66
Chapter 3. Characterizing conditioned reactivity to sequential alcohol-predictive cues in well-trained rats ...... 73
3.1 Abstract ...... 73
3.2 Introduction ...... 74
3.3 Methods and materials ...... 76
3.3.1 Subjects ...... 76
3.3.2 Apparatus ...... 77
3.3.3 Behavioral methods ...... 77
3.3.3.1 Drinking unsweetened ethanol in the homecage ...... 77
3.3.3.2 Cue conditioning with unsweetened ethanol...... 78
3.3.3.3 Blood ethanol concentration following cue conditioning ...... 79
3.3.3.4 Behavioral measurements...... 79
3.3.3.5 Blood ethanol analysis ...... 80
3.3.4 Statistical analysis ...... 81 xvi 3.4 Results ...... 81
3.4.1 Post-acquisition dynamics in reactivity to houselight illumination .... 81
3.4.2 Post-acquisition dynamics in reactivity to sipper presentation ...... 82
3.4.3 Post-acquisition dynamics in reactivity to oral ethanol receipt ...... 83
3.4.4 Blood ethanol concentrations in the conditioning task ...... 84
3.4.5 Conditioned reactivity to houselight illumination promotes ethanol drinking ...... 85
3.5 Discussion ...... 86
3.5.1 Cue conditioning with unsweetened alcohol in non-deprived rats ..... 86
3.5.2 Control of alcohol seeking and drinking by multiple alcohol- predictive cues ...... 86
3.5.3 Alcohol consumed during cue-conditioning sessions was pharmacologically active ...... 89
3.5.4 Reactivity to an alcohol-predictive CS promotes alcohol intake ...... 91
3.5.5 Summary ...... 91
3.6 Supplemental Information ...... 92
3.6.1 Drinking unsweetened ethanol in the homecage ...... 92
3.6.2 Acquisition of sipper-site approach elicited by the houselight...... 92
3.6.3 Acquisition of sipper contact and consummatory licking ...... 93
3.6.4 Ethanol doses ingested in the conditioning task ...... 93
3.6.5 No houselight CS conditioning without ethanol US experience ...... 94
3.7 Figures ...... 95
Chapter 4. Alcohol-associated antecedent stimuli elicit alcohol anticipation in a non- dependent rat model and activate the insula ...... 104
4.1 Abstract ...... 104
xvii 4.2 Introduction ...... 104
4.3 Methods & materials...... 106
4.3.1 Subjects ...... 106
4.3.2 Behavioral Methods ...... 107
4.3.2.1 Paired and Unpaired Cue-Ethanol Conditioning ...... 107
4.3.2.2 Brain Collection Day ...... 108
4.3.2.3 Behavioral Measurements ...... 109
4.3.2.4 Fos Immunohistochemistry ...... 110
4.3.3 Statistical Analysis & Data Visualization ...... 110
4.4 Results ...... 111
4.4.1 Acquisition of alcohol drinking and behavioral reactivity ...... 111
4.4.2 Ethanol-directed reactivity to houselight illumination depends on relationship between ethanol access and houselight illumination ...... 112
4.4.3 Dynamics but not form of reactivity to ethanol sipper presentation depends on relationship between ethanol sipper presentation and houselight illumination...... 113
4.4.4 Dynamics but not form of reactivity to oral ethanol receipt depends on relationship between oral ethanol receipt and houselight illumination ...... 114
4.4.5 Different brain regions are responsive to Paired v. Unpaired cue- ethanol conditioning ...... 116
4.5 Discussion ...... 117
4.5.1 Form of learned reactivity depends on the cue-alcohol relationship 117
4.5.2 Dynamics of learned reactivity depend on the cue-alcohol relationship ...... 119
4.5.3 Insular cortex c-Fos expression in the rat depends on the cue- alcohol relationship ...... 120
xviii 4.5.4 Conclusion ...... 122
4.6 Supplemental Information ...... 123
4.6.1 Fos immunostaining & analysis procedures ...... 123
4.6.2 Ethanol drinking in the homecage ...... 124
4.6.3 Ethanol drinking in the conditioning chamber ...... 125
4.6.4 Consummatory sipper licking across conditioning ...... 126
4.6.5 Acquisition of conditioned sipper site approach reaction to houselight illumination...... 127
4.6.6 Habituation of orienting reaction to houselight illumination ...... 127
4.6.7 No houselight CS conditioning without ethanol US experience ...... 128
4.7 Figures ...... 130
Chapter 5. Cue-alcohol associative learning in female rats and examination of estrous cycle in established limited access free-choice drinking ...... 140
5.1 Abstract ...... 140
5.2 Introduction ...... 141
5.3 Methods & materials...... 142
5.3.1 Subjects ...... 142
5.3.2 Behavioral Methods ...... 143
5.3.2.1 Pre-conditioning ethanol drinking in the homecage ...... 143
5.3.2.2 Ethanol-reinforced classical conditioning ...... 143
5.3.2.3 Blood collection & ethanol analysis ...... 144
5.3.2.4 Post-conditioning ethanol drinking in the homecage ...... 144
5.3.2.5 Vaginal lavage & estrous cycle stage determination ...... 144
5.3.2.6 Behavior Measurement ...... 145
xix 5.3.3 Statistical Analysis ...... 146
5.4 Results ...... 146
5.4.1 Drinking in the homecage before ethanol cue conditioning ...... 147
5.4.2 Acquisition of houseight cue-triggered alcohol appetitive state in group Paired, but not Unpaired...... 147
5.4.3 Acquisition of similar reactions to sipper presentation in group Paired and Unpaired ...... 148
5.4.4 Drinking in the conditioning chamber across ethanol cue conditioning ...... 149
5.4.5 Similar blood ethanol concentrations after a conditioning session ... 149
5.4.6 Vaginal lavage-required extra handling did not alter established daily drinking pattern ...... 150
5.4.7 Estrous cycle stage and daily drinking pattern ...... 150
5.5 Discussion ...... 151
5.5.1 Pre-conditioning free-choice alcohol drinking & preference ...... 152
5.5.2 Acquisition of alcohol cue reactivity ...... 152
5.5.3 Post-conditioning free-choice alcohol drinking & preference: effects of vaginal lavage ...... 153
5.5.4 Post-conditioning free-choice alcohol drinking & preference: effects of the estrous cycle ...... 154
5.5.5 Conclusion ...... 155
5.6 Supplemental Information ...... 156
5.6.1 Free-choice ethanol drinking and preference in the homecage after ethanol cue conditioning ...... 156
5.6.2 Acquisition of similar pre-session alcohol-directed behavior in Paired and Unpaired ...... 157
xx 5.6.3 Total v. partial habituation of orienting reaction to houselight cue in Paired v. Unpaired ...... 158
5.7 Figures ...... 159
Chapter 6. Conclusion ...... 171
6.1 Demonstrated positive effect of retrieval + extinction in the reinstatement model of relapse ...... 171
6.1.1 Need to replicate this effect in other models of relapse ...... 171
6.1.1.1 Stress-induced reinstatement ...... 171
6.1.1.2 Context-induced reinstatement ...... 172
6.1.1.3 Priming-induced reinstatement ...... 172
6.1.1.4 Long-term spontaneous recovery ...... 173
6.1.1.5 Reconditioning rate test ...... 174
6.1.1.6 Post-treatment Pavlovian to instrumental transfer (PIT) test 174
6.1.2 Need to test the retrieval + extinction effect for other alcohol- related memories ...... 175
6.1.2.1 Over-trained cue memory and/or longer histories of drinking ...... 176
6.1.2.1.2 Cue memory in context of physical dependence or models of severe AUD ...... 176
6.2 Post-ingestive effects are required for certain forms of alcohol cue reactivity 177
6.3. Resistance of alcohol cue reactivity to extinction ...... 179
6.4 Need to know mechanisms of retrieval + extinction in order to optimize ...... 180
6.4.1 Behavioral mechanisms ...... 180
6.4.2 Neurobiological mechanisms ...... 181
6.5 Translation & Clinical Applications ...... 182
6.5.1 Issues that might come up in studies with human subjects ...... 183 xxi 6.6 Conclusion ...... 184
Works Cited ...... 185
xxii List of Figures
Figure 2.1. Retrieval + extinction experiment timelines...... 66 Figure 2.2. Matched free-choice ethanol drinking history...... 67 Figure 2.3. Matched cue-conditioned appetitive response acquisition...... 68 Figure 2.4. Equivalent cue-conditioned appetitive response extinction...... 69 Figure 2.5. Similar daily recovery of cue-conditioned appetitive responses...... 70 Figure 2.6. Retrieval-extinction treatment protects against early spontaneous recovery of cue-conditioned appetitive responses relative to two different
baselines...... 71 Figure 2.7. Retrieval-extinction treatment protects against alcohol odor-induced reinstatement of cue-conditioned appetitive responses relative to two
different baselines...... 72 Figure 3.1. Dynamics of reactivity to houselight illumination...... 95 Figure 3.2. Dynamics of reactivity to sipper presentation...... 96 Figure 3.3. Dynamics of reactivity to oral ethanol receipt...... 97 Figure 3.4. Ethanol in blood after a conditioning session...... 98 Figure 3.5. Houselight cue-elicited appetitive reactivity predicts drinking...... 99 Figure 3.6. Drinking in the homecage...... 100 Figure 3.7. Conditioning of reactivity to houselight illumination...... 101 Figure 3.8. Drinking in the conditioning chamber...... 102 Figure 3.9. Pharmacologically active ingested doses required to condition reactivity to
houselight illumination...... 103 Figure 4.1. Ethanol sipper-seeking reaction to houselight illumination...... 130 Figure 4.2. Reactivity to sipper presentation...... 131
xxiii Figure 4.3. Reactivity to oral ethanol receipt...... 132 Figure 4.4. Brain c-Fos expression after a Paired or Unpaired cue-ethanol
conditioning session or its omission in well-trained rats...... 133 Figure 4.5. c-Fos study...... 134 Figure 4.6. Drinking in the homecage...... 135 Figure 4.7. Drinking in the conditioning chamber...... 136 Figure 4.8. Conditioning task acquisition...... 137 Figure 4.9. Orienting reaction to houselight illumination...... 138 Figure 4.10. No acquisition of conditioned approach without ingestion of
pharmacologically-active ethanol doses...... 139 Figure 5.1. Initiation of free-choice ethanol drinking...... 159 Figure 5.2. Cue-conditioned appetitive response acquisition...... 160 Figure 5.3. Consummatory response across appetitive cue-conditioning...... 161 Figure 5.4. Ethanol in blood after a conditioning session...... 162 Figure 5.5. No effect of vaginal lavage handling on established limited access free-
choice ethanol drinking...... 163 Figure 5.6. No effect of estrous cycle on established limited access free-choice
drinking...... 164 Figure 5.7. Re-initiation of free-choice ethanol drinking under limited access
conditions...... 165 Figure 5.8. Estrous cycle and ethanol drinking in lavaged rats...... 166 Figure 5.9. Estrous cycle and ethanol drinking in non-lavaged rats...... 167 Figure 5.10. No estrous cycle effect on the last day of free-choice drinking...... 168 Figure 5.11. Pre-session waiting period behavior across conditioning...... 169 Figure 5.12. Orienting response to houselight illumination across conditioning...... 170 xxiv Chapter 1. Introduction
1 ALCOHOL USE, USE DISORDER, AND & THE ROLE OF CUES
1.1 Alcohol use prevalence & consequences
Of adults (people ≥18 years old) in the United States (U.S.), 65-70% can be expected to have drank at least one alcoholic beverage in the past year and 10-13% can be expected to have engaged in excessive drinking (≥ 5 drinks per day for men, ≥ 4 drinks per day for women) at least weekly over the past year (Grant, Chou, Saha, et al., 2017). Those recommended daily drinking limits are informed by the negative health consequences of drinking for the individual. Although in the past, people with “light” to “moderate” drinking patterns (e.g., ≤ 2 drinks per day for men, ≤ 1 drinks for women) have been reported to be at lower risk for some heath issues (e.g., cardiovascular function, mortality), these findings typically do not survive correction for confounding sociodemographic characteristics (e.g., Chou, Grant, & Dawson, 1998). In fact, a recent meta-analysis of person-level data (N = 599, 912) from 83 independent prospective studies found no statistical evidence for any health benefit of “light” or “moderate” drinking whatsoever (Wood, Kaptoge, Butterworth, et al., 2018). Its findings suggest that health risks reported for “heavier” drinking are actually dose-dependent health risks for any alcohol use. Among the many health issues for which increased harm or risk is reliably observed in people with “heavy” drinking patterns (e.g., ≥ 5 drinks per day for men, ≥ 4 drinks for women) are cardiovascular and hepatic disease and mortality (Rehm et al., 2010; Reynolds et al., 2003; Ronksley et al., 2011) as well as gastrointestinal cancers (Bagnardi et al., 2001; Klarich, Basser, & Hong, 2015) (for other health issues, see Rehm, 2009). People with “heavy” drinking patterns also at increased risk of other serious negative medico-legal consequences including assault, drunk driving, unintentional injury, unprotected sex, and
1 unplanned pregnancies (Courtney & Polich, 2009; Hingson et al., 2009; Holway, Tillman & Brewster, 2017; Naimi et al., 2003; Smith, Branas & Miller, 1999; Wechsler et al., 1994). Some of these risks do not only affect the health of the person drinking, but also the health of others. Finally, “heavy” drinking also puts people at risk for neuropsychiatric illnesses (see Rehm, 2009).
1.3 Prevalence of alcohol use disorder (AUD)
In the American Psychiatric Association Diagnostic and Statistical Manual version 5 (DSM-5) (2013), any person meeting 2 or more of the following criteria may be suffering from an alcohol use disorder (AUD): (1) drank more than intended, (2) tried to decrease or stop drinking and failed, (3) spent a lot of time drinking or getting over its aftereffects, (4) wanted to drink so badly that it blocked out other thoughts, (5) experienced social or legal troubles due to drinking or its aftereffects, (6) continued to drink despite those troubles, (7) stopped doing other interesting and pleasurable things in order to drink, (8) engaged in risky behavior after drinking, (9) had a drinking-related blackout, (10) needed to drink more than you once did in order to get the same effect, and/or (11) experienced withdrawal symptoms when the effects of alcohol were wearing off. The more criteria are met, the more severe the AUD. Among the 65-70% of adults in the United States who drank any alcohol in the past year, 13-17% can be expected to meet diagnostic criteria for AUD in the past year (Grant, Chou, Saha, et al., 2017). Among the 10-13% of adults in the United States who drank above the recommended daily drinking limits at least weekly across the past year, 17-46% can be expected to meet diagnostic criteria for AUD in the past year (Grant, Chou, Saha, et al., 2017). In fact, as many as 30% of adults in the United States can be expected to meet diagnostic criteria for AUD in their lifetime with about 14% qualifying for severe AUD
2 (Grant, Goldstein, Saha, et al., 2015). These estimates are consistent with prior reports (Lopez-Quintero, Cobos, Hasin, et al., 2011a). Only about 2% of people who start drinking can be expected to meet diagnostic criteria for AUD after 1 year, but after 10 years, as many as 11% can be expected to meet diagnostic criteria for AUD (Lopez-Quintero, Cobos, Hasin, et al., 2011b). Additionally, Schuckit and colleagues (1995) have found that it takes people with AUD about 10-12 years to seek treatment after the onset of alcohol use-related problems, during which time problem number and severity increase. Thus, in a minority of cases, exposure alone may be sufficient to induce AUD, but in most cases, loss of control of alcohol consumption develops progressively over a much longer drinking history.
1.4 AUD recovery and relapse rate
In the United States, almost 50% of non-treated people with AUD can be expected to fully recover in 1 year (Dawson et al., 2005). However, only about 40% of non-treated people with AUD can be expected to remain recovered 3 years later, and about 60% of these can be expected to relapse to AUD at least once within 16 years (Moos & Moos, 2006). Consequently, short-term (3 years) recovery may occur, but only in about 24% of non-treated people. Long-term (16 years) natural recovery may also occur, but only in about 16% of non-treated people. Additionally, about 25% of non-treated people that present with AUD have a history of prior natural recovery (Dawson et al., 2006), suggesting a high rate of natural relapse to AUD. Finally, 60% of non-treated people can be expected to continue to suffer from AUD without experiencing even short-term recovery (Moos & Moos, 2006). Thus, short-term natural recovery from AUD may be fairly common, but long-term natural recovery is rare, and the more common outcome of short- term natural recovery is relapse to AUD.
3 1.5 AUD treatment seeking and post-treatment relapse rate
There is no easy “cure” for AUD, but there are treatment options from which at least some people are able to benefit and use to recover fully from AUD. Among psychosocial interventions, cognitive-behavioral therapy, motivational enhancement therapy, relapse prevention, and 12-step facilitation all have some demonstrable efficacy (Babor & Del Boca, 2003; Brooks & Penn, 2003; Brown et al., 2002; Burke et al., 2004; Dunn et al., 2001; Ouimette et al., 1997). In the United States, there are also three pharmacological agents approved by the Food & Drug Administration for treatment of AUD: disulfiram, acamprosate, and naltrexone. However, only the latter two have at least some demonstrable efficacy (Kranzler & van Kirk, 2001). In general, psychosocial and pharmacological interventions are equally efficacious (or inefficacious, depending on who you ask) (Zweben, Pettinati, Weiss, et al., 2008), and their combination remains recommended in clinical practice (Kleber, Weiss, Anton, et al., 2006). Despite these treatment options, very few people seek or obtain treatment for AUD. Indeed, among adults in the United States with lifetime history of diagnosable AUD, about 20% had sought some form of treatment in their lifetime, and only about 7% of those diagnosable in the past year had sought treatment in the past year (Grant, Goldstein, Saha, et al., 2015). There are many reasons why a person with diagnosable AUD may not seek treatment including lack of access or awareness to services and perceived stigma (Keyes, Hatzenbuehler, McLaughlin, et al., 2010). There is also the erroneous perception that treatment is futile. In fact, AUD treatment is no more futile than treatment of other chronic illnesses (O’Brien & McLellan, 1996). However, one good reason people may not seek treatment is that the options available to them are perceived as not efficacious enough to warrant the effort (Mark, Kranzler, Poole, et al., 2003). 4 Depending on initial AUD severity and the criteria used to define recovery, anywhere from 20 to 50% of treated people can be expected to fully recover in 1 year (Armor & Meshkoff, 1983; Miller, Walters, & Bennett, 2001; Monahan & Finney, 1996). About 60% of treated people can be expected to remain recovered 3 year later, and only about 40% of these can be expected to relapse to AUD at least once within 16 years (Moos & Moos, 2006). Thus, treatment can be expected to be highly efficacious in about 36% of treated people and moderately efficacious in about 24% of treated people. In about 40% of treated people, treatment will not produce full recovery (Moos & Moos, 2006), although it may still reduce alcohol use-related negative consequences and/or improve quality of life (Miller, Walters, & Bennet, 2001).
1.6 Relapse and alcohol-related cues
Post-treatment recovery/relapse rates are strongly determined by the environment in at least two ways (Marlatt, 1996). First, individuals with AUD may have learned to cope stress related to with environmental demands (e.g., accidents, evaluations, financial difficulty, interpersonal conflict, social pressure) by using alcohol. Second, individuals with AUD may encounter alcohol-related cues in their environments (e.g., hidden bottles, passing by a bar, alcohol advertising). There are two types of alcohol-related cues: general cues and personal cues. General alcohol-related cues are those environmental stimuli experienced by everyone who drinks alcohol (e.g., sight, smell, and taste). Personal alcohol-related cues are those alcohol use-related stimuli that are especially meaningful to a specific person. People with AUD commonly encounter both general and personal alcohol-related cues and consequently experience alcohol “craving” (viz., a desire or urge to drink) (Witteman, Post, Tarvainen, et al., 2015; Fatseas, Serre, Alexandre, et al., 2015). Increases in the intensity of alcohol
5 craving increase the likelihood of subsequent alcohol use (Fatseas, Serre, Alexandre, et al., 2015). Additionally, stress promotes alcohol use by increasing the intensity of alcohol craving (Law, Gullo, Daglish, et al., 2016). In the laboratory, alcohol-related imagery, which includes both kinds of cues, induces reactivity in treatment-seeking people with moderate to severe AUD that includes alcohol craving, anxiety, and altered physiology (e.g., changes in heart rate, cortisol secretion, salivation) (Fox, Berquist, Hong, et al., 2007; Sinha, Fox, Hong, et al., 2009). The (automatic) behavioral and physiological reactions to alcohol-related cues (e.g., attentional bias, brain circuit activation, heart rate, salivation) that people cannot reliably self-report also predict lapses and relapse risk after AUD treatment (Braus, Wrase, Grüsser, et al., 2001; Grüsser, Wrase, Klein, et al., 2004; Cox, Hogan, Kristian, et al., 2002; Garland, Franken, & Howard, 2012; Papachristou, Nederkoorn, Giesen, et al., 2014; Rohsenow, Monti, Rubonis, et al., 1994; but see Snelleman, Schoenmakers, & van de Mheen, 2015).
1.7 Conclusions
Alcohol use is prevalent and harmful. At least a quarter of regular alcohol users will suffer from alcohol use disorder in their lifetime. Few people suffering from AUD seek treatment. Over half of treated people fully recover; the rest recover only partially. Reactivity to alcohol-related cues in daily life contributes to the risk for relapse after treatment. There is need to improve existing treatments to persistently attenuate the power of alcohol-related cues.
6 2 EXPLAINING CUE REACTIVITY, IN GENERAL: LEARNING & NON-LEARNING ACCOUNTS
2.1 Learning-based accounts
Learning can be defined as “an enduring change in the mechanisms of behavior involving specific stimuli and/or responses that results from prior experience with those or similar stimuli and responses” (Domjan, 2014). An important point is that learning is defined by a change in the mechanisms of behavior as opposed to changes in behavioral performance. Performance can be determined by factors other than learning. The mechanisms of behavior means the relevant circuits and/or systems in the central nervous system. Even though what it is learned and how quickly it is learned may vary by species, the behavioral processes and biochemical mediators of learning appear to be conserved, at least across vertebrate species (O’Connell & Hofman, 2011). Modeling aspects of human behavior in nonhuman animals permits us to ask and answer questions about the mechanisms of behavior directly, something which is difficult, if not impossible, to do in humans. Like models in any other domain, the validity of nonhuman animal models of human behavior hinges upon how well the latter reproduce the relevant features of the problem being studied. There are two broad classes of learning, associative v. non-associative learning, both of which can account for changes in a person’s reactions to a stimulus.
2.1.1 Associative learning
We can define associative learning as an enduring change in the mechanisms of behavior that reflects experience with the relationship between stimuli and/or responses. It is important to note here that responses can produce sensations that can serve as stimuli.
7 The concept of “association” explains how pairs of simple sensations can combine into more complex perceptions. At least 3 major rules are thought to govern how associations are formed (see Domjan, 2014). These 3 major rules came from Aristotle (384-322 BCE). His rule of contiguity states that if two stimuli occur together repeatedly in space or time, they will become associated. Thomas Brown (1778-1820 CE) amended the rule of contiguity to emphasize that both how frequently the two stimuli co-occur and how recently they co- occurred matters. Aristotle’s rule of similarity states that if two stimuli are similar enough, they will become associated. Aristotle’s last rule, the rule of contrast, states that if two events are different enough, they will become associated. Of Aristotle’s 3 rules, only contiguity and similarity have been demonstrated empirically (e.g., Cusato & Domjan, 1998; Rescorla & Furrow, 1977). Thomas Brown also proposed some additional rules. His rule of intensity states simply that the stimuli can only become associated if they are intense enough to be detected by some sense organ. He also proposed that there might be a limit on how many associations certain stimuli could be involved. Finally, Brown suggested that the similarity of an association that could be formed to previously acquired associations may also matter. Although we are often interested in declarative or explicit associative learning processes that are accessible to conscious awareness and self-report, there is a growing appreciation among neuroscientists and psychologists that much of what takes us though our daily lives relies on processes that are inaccessible to conscious awareness (Lewicki, Hill, & Czyzewska, 1992). Conscious awareness plays a limited role in the most prevalent forms of associative learning, reinforcement-based emotional and procedural learning, which take place automatically in an unsupervised manner (Lieberman, Sunnucks, & Kirk, 1998; Smith et al., 2005). In fact, the majority of daily human life hinges on habitual 8 reactions to stimuli have been stamped in by reinforcement over time (Wood & Neal, 2007; Gasbarri et al., 2014). Implicit associations are at the core of habitual reactions. One of the simplest models for studying implicit associative learning is classical conditioning. Conditioning procedures can be carried out in nonhuman animals, allowing us to model and study aspects of human behavior under much simpler, better controlled, more rigorous, more interpretable, and less expensive conditions.
2.1.1.1 The classical/pavlovian conditioning framework
The classical conditioning model of associative learning was popularized by Ivan Pavlov (1927). In this framework, the environment is deconstructed into antecedent stimuli, responses, and outcomes or consequences. It is assumed that changes in the relationships among these elements of the environment will manifest as changes in behavior.
2.1.1.2 Conditional and unconditional stimuli (CS, US)
Pavlov used the term conditional stimulus (CS) to signify a stimulus whose effectiveness in eliciting a specific reaction depended on its repeated pairing with an unconditional stimulus (US), viz., a stimulus whose response-eliciting effectiveness did not depend on prior experience. Thus, the same stimulus may serve as the CS relative to one stimulus and as a US relative to another stimulus in the same training context. Additionally, once a CS is well trained, it can be used to train a new CS in a different training context, a phenomenon known as second-order conditioning (Witnauer & Miller, 2011).
9 2.1.1.3 Conditional and unconditional reactivity (CR, UR)
In Pavlov’s original terminology, any behavior that was eventually elicited by the CS was referred to as the conditional response (CR) whereas behavior elicited by the US was referred to as the unconditional response (UR). The CR can be a CS-directed anticipatory UR-like response (sign-tracking, ST) or a US-directed anticipatory UR-like response (goal-tracking, GT) (Brown & Jenkins, 1968; Jenkins & Moore, 1973; Hearst & Jenkins, 1974; Graham, Davey, Phillips, & Witty, 1989). For example, in a paradigm where illumination of key light fixture reliably precedes food delivery at a nearby site, a hungry may learn to move toward the light fixture (ST) or toward the food delivery site (GT) as a response to key light illumination. Alternatively, the CR can be a modification of the UR such as conditioned analgesia or conditioned drug tolerance (Domjan, 2005; Ross, 1986). Additionally, the CR can be persistence of the initial orienting reaction to the CS (Buzsáki, 1982; Holland, 1977).
2.1.1.4 Determinants of CR: the US
The identity or nature of the US plays a critical role in the form of acquired CR (Jenkins & Moore, 1973; Davey & Cleland, 1982). The nature of the US will determine what mechanisms of behavior are engaged during CS-US pairings. An exteroceptive CS paired with mild footshock, which is an aversive exteroceptive US, is unlikely to acquire approach and contact behavior as its CR, but it might if the US were instead an intravenous bolus of low-to-moderate dose cocaine. According to one of the major theories for conditioning, the entirety of CR acquisition (viz., formation of the CS-US association) hinges upon the surprisingness of US presentation (Kamin, 1969; Rescorla & Wagner, 1972; Pearce & Hall, 1980; Roesch et al., 2012). For this reason, extensive experience with the US prior to CS-US pairings often inhibits CR acquisition (Randich & LoLordo, 1979;
10 Franklin & Hall, 2011). For the same reason, the animal’s physiological state can also make certain US more or less effective at the time of CS-US pairing.
2.1.1.5 Determinants of CR: the CS
The identity or nature of the CS plays an important role in the form of acquired CR (Timberlake & Grant, 1975; Holland 1980a). In part, this is because animals initially react to both the CS and the US. Reactions to the CS may compete with reactions to the US. In fact, often, initial reactions to a CS must be eliminated before it can acquire a CR. However, in some cases, extensive experience with the CS prior to CS-US pairings inhibits CR acquisition, a phenomenon known as latent inhibition (Lubow & Moore, 1959; De la Casa, Marquez, & Lubow, 2009).
2.1.1.6 Determinants of CR: the CS-US interval
Different mechanisms of behavior are engaged at different intervals between CS and US, which in turns determines what responses are available for conditioning (Akins, 2000; Esmoris-Arran, Pardo-Vazques, & Vazquez-Garcia, 2003; Holland, 1980b; Silva & Timberlake, 1997; Waddell, Morris, & Bouton, 2006). For example, when there is a long interval between an exteroceptive CS and an appetitive US like food or water, the animal is more likely to emit general foraging-related spatial behavior such as increased gross locomotion. When the CS-US interval is short, the animal is more likely to emit more focused foraging-related behavior such as approach to a specific place and species-typical behaviors that consummate foraging (e.g., gnawing, licking) (Craig, 1918).
2.1.1.7 Determinants of CR: Other
Other determinants of CR acquisition, form, and/or dynamics include the intensity and relevance of CS and US. More intense CS and US expedite or facilitate CR acquisition 11 and may determine its vigor (Bevins et al., 1997; Scavio & Gormezano, 1974). Similarly, the more ecologically relevant the CS is to the US, the faster or stronger the conditioning (Garcia & Koelling, 1966; Rescorla, 2008; Logue et al., 1981; Pelchat & Rozin, 1982). For example, in primates, images of snakes acquire CR when paired with a mild electric shock more easily than neutral images (Ohman et al., 2007).
2.1.2 Non-associative learning
Adapting the definition of learning given above, we can define non-associative learning as an enduring change in the mechanisms of behavior arising from repeated stimulus presentation alone. Two well-known forms are habituation and sensitization, both of which are adaptive and pervasive in human experience. For example, both forms of non- associative learning are prominent features of Solomon & Corbit’s theory of motivation (1974) and consequently, Koob & Le Moal’s theory of drug addiction (2008).
2.1.2.1 Habituation
Habituation describes the situation in which an organism’s reaction to a stimulus decreases with repeated stimulus presentation. This form of non-associative learning is observed across many different species and situations (Rankin et al., 2009). It is stimulus specific and subject to spontaneous recovery. Spontaneous recovery refers to situations in which an organism’s reaction to a stimulus returns to a previous level due to the passage of time since the last stimulus presentation. Habituation can take on two time-scales: short and long-term. Sometimes only short-term habituation is observed (e.g., Thompson & Spencer, 1966), in which case the organism’s level of reaction to the stimulus will fully recover if allowed to rest. In long-term habituation, reactivity to the stimulus never recovers
12 to its initial level. Habituation plays an important role in human hedonic and salivary reactions to taste stimuli (Epstein et al., 1992; Epstein et al., 2003; Epstein et al., 2009).
2.1.2.2 Sensitization
Sensitization describes the situation in which an organism’s reaction to a stimulus increases with repeated stimulus presentation. Unlike habituation, sensitization is not stimulus specific. In fact, it is typically demonstrated by inducing an emotional state prior to stimulus presentation. For example, fear can potentiate startle reactions in rats and humans (Davis et al., 2010). Similarly, sexual arousal can potentiate sensitivity to touch in humans (Jiao, Knight, Weerakoon, & Turman, 2007). Reactions to interoceptive stimuli may also be sensitized (Miller & Domjan, 1981). Like habituation, however, sensitization is subject to spontaneous recovery (viz., it can dissipate with rest).
2.1.3 Testing for associative versus non-associative learning
Habituation and sensitization act on different mechanisms of behavior (Groves & Thompson, 1970). Based on its stimulus specificity, habituation is thought to occur in the neural circuit that mediates the specific behavioral reaction to the stimulus in question. In contrast, sensitization is thought to occur in the brain’s arousal systems (e.g., dopamine or norepinephrine-releasing nuclei in midbrain; Yetnikoff, Lavezzi, Reichard, & Zahm, 2014; Saper & Stornetta, 2014). There are at least 3 accepted procedures for determining whether changes in the organism’s reaction to an eliciting stimulus or putative CS stems from associative versus non-associative processes (Rescorla, 1967). The first (between-subjects) control procedure asks whether similar changes in reactivity occur when the putative CS is always followed by the US versus when it is followed by the US on only 50% of occasions. However, this
13 procedure does not prevent the development of a CR (Kirkpatrick & Church, 2004). The second (between-subjects) control procedure asks whether similar changes in reactivity occur when the putative CS and US are explicitly paired versus unpaired. In situations where associative learning is taking place, the CR is only observed in the explicitly paired condition. A third (within-subjects) control procedure (known as discrimination training) asks whether similar changes in reactivity occur to a CS that positively predicts the US (referred to as the CS+) relative to a CS that predicts its absence (referred to as the CS-). In an associative learning situation, a CR is developed to the CS+ but not CS-.
2.1.4 Interactions between associative and non-associative learning processes
It is possible for associative and non-associative learning to interact, at least in theory. For example, one of the major learning-based theories of drug addiction, the incentive salience sensitization theory (Robinson & Berridge, 1993), proposes that a CR to an addictive drug-associated CS can undergo sensitization because the addictive drug US is able to act directly (pharmacologically) on one of the brain’s arousal systems, specifically, a midbrain nucleus with dopamine-releasing projections into the mesotelencephalon. Robinson & Berridge believe that this nucleus is responsible for imbuing the perception of a stimulus with incentive salience (viz., motivational significance), a property that makes perceived stimuli attractive and “wanted.” The same system is known to participate in associative learning (Bassareo & De Chiara, 1997; Flagel et al., 2010; Saddoris et al., 2015). This sets up a maladaptive feed-forward process. A stimulus such as the sight of the drug or the self-administration device becomes associated with the addictive drug and imbued with incentive salience, bringing the person into contact with the drug. Repeated experience of the drug’s effects adapts the mechanism of incentive salience, causing continued/excessive attribution of incentive salience, which can
14 manifest as a change in the form of CR. For example, there may be a shift from goal- tracking to sign-tracking type CR with chronic oral alcohol self-administration (Srey, Maddux, & Chaudhri, 2015).
2.2 Non-learning-based accounts
Processes other than learning can account for changes in a person’s reaction to a stimulus. These processes are not considered “learning” because they may not occur at the mechanisms of behavior, may not last enough, and/or may not result from experience with specific stimuli and/or responses. Some examples are damage, development, fatigue, and sensory adaptation.
2.2.1 Damage (Illness or injury)
An important non-learning process that can cause change in behavior is damage. Damage refers to acute or chronic illness or injury that can directly affect the mechanisms of behavior. An important caveat here is that damage can sometimes serve as a stimulus for learning. For example, acute post-ingestive illness can serve as an aversive unconditional stimulus for taste avoidance learning (Garcia, Hankins, & Rusiniak, 1974). Perhaps a more dramatic example comes from the literature of recovery from stroke, a cardiovascular event that causes acute and chronic damage to the mechanisms of behavior. If a stroke damages motor cortex in one hemisphere of the brain, an animal must learn how to perform even formerly routine motor tasks in a new and different way to compensate for loss of function in the contra-lateral limb (Jones, 2017). In this example, only the loss of contra-lateral limb function stems from damage itself.
15 2.2.2 Development (maturation)
A major process that can account for changes in behavior across long periods is genetically-programmed development or maturation of the animal. Maturation causes sweeping changes in the mechanisms of behavior. However, these changes in behavior can typically occur in the absence of experience with the specific stimuli and/or responses. The lines between learning and non-learning are blurred when genetically-programmed developmental processes are initiated or released by specific environmental stimuli (e.g., experience-dependent shaping of the sensory cortices in the early post-natal environment).
2.2.3 Fatigue
One of the simplest explanation for changes in behavioral performance is physical exertion, that is, fatigue. Fatigue describes the situation in which an animal’s reaction to a stimulus decreases with repeated stimulus presentation because the biochemical/metabolic resources required to produce the reaction have been depleted. Like habituation, fatigue is experience-dependent. Unlike habituation, it is not stimulus/response-specific.
2.2.4 Sensory Adaption
Another simple explanation for changes in behavioral performance is sensory adaptation. Sensory adaptation describes the situation in which an animal’s reaction to a stimulus decreases with repeated stimulus presentation because the biochemical/metabolic resources required to sense the stimulus have been depleted. Like habituation, sensory adaptation is experience-dependent. Unlike habituation, it is not stimulus/response- specific.
16 2.3 Role of learning and non-learning processes in human behavior
It is difficult to rank the relative contribution of each of the above processes to overall human behavior. Ranking their relative contribution to problematic behavioral phenotypes such as alcohol and drug abuse is easier. The consensus is overwhelmingly in favor of the idea that maladaptive alcohol and drug-related behavior such as cue reactivity is controlled by a mixture of explicit and implicit associative learning processes (Stewart, de Wit, & Eikelboom, 1984; Tiffany & Conklin, 2000; Wiers & Stacy, 2006; Lee, Dickinson, & Duka, 2010; Belin et al., 2013).
3 ALCOHOL CUE REACTIVITY IN HUMANS AND NON-HUMAN ANIMAL MODELS
3.1 Cue-elicited appetitive responses or “wanting” for alcohol in humans
In humans, alcohol-associated stimuli such as the sight and smell of the preferred alcoholic beverage can elicit responses that bring the individual closer to the alcoholic beverage and/or the act of ingestion—conditioned appetitive responses or states in the language of Stewart, de Wit, & Eikelboom (1984) or “wanting” (conditioned motivational value/impact) in the language of Robinson & Berridge (1994). Cue-elicited appetitive responses or “wanting” may contribute to and/or manifest as “attentional bias, “approach tendency,” or “alcohol craving” (measured as self-reported urge to drink, desire to drink, temptation to drink, or difficulty in resisting a drink if offered). The cue-elicited responses involve and/or are mediated by changes in physiology (e.g., brain activity, heart rate, salivation). In Robinson & Berridge’s theory of addiction (1994), drug “liking” (hedonic value/impact) and “wanting” (motivational value/impact) are dissociable at the behavioral and brain systems level, and it is drug cue-elicited drug “wanting” that undergoes
17 sensitization. The liking-wanting dissociation has been empirically demonstrated for alcohol at the behavioral level in humans (Hobbs, Remington, & Glautier, 2005).
3.1.1 Increased attentional bias, approach tendency, and self-reported craving
Alcohol-related pictures can produce attentional bias (Field & Eastwood, 2005; Field, Mogg, & Bradley, 2005; Shin, Hopfinger, Lust, et al., 2010) and approach tendency (Field, Mogg, & Bradley, 2005; Fleming & Bartholow, 2014; Hollet, Strikze, Edgeworth, & Weinborn, 2017) in humans without alcohol use disorder. Alcohol-related pictures also produce attentional bias (Vollstädt-Klein, Loeber, Richter, et al., 2012; Snelleman, Schoenmakers, & van de Mheen, 2015) in humans with alcohol use disorder. The sight and smell of the person’s preferred alcoholic beverage are also able to produce an approach tendency (Kreusch, Billieux, & Quertemont, 2017) as are alcohol-related pictures (Loijen, Rinck, Walvoort, et al., 2018). Both manifestations of cue reactivity are directly related to alcohol abuse and/or use disorder severity (Cox et al., 2006; Fadardi & Cox, 2006; Klein et al., 2007; Klein & Anker, 2013). The attentional manifestation is also inversely related to perceived behavioral control over alcohol use (Cox et al., 2003, 2007; McCusker, 2001). Humans without alcohol use disorder can respond with increased alcohol craving to the sight and/or smell of alcoholic beverages (Bragulat, Dzemidzic, Talavage, et al., 2008; Field, Mogg, Zetteler, et al., 2004; Field, Mogg, & Bradley, 2005; Kambouropoulos & Staiger, 2004; Kaplan, Cooney, Baker, et al., 1985; Kareken, Bragulat, Dzemidzic, et al., 2010; Kiefer, Kirsch, Bach, et al., 2015; MacKillop & Lisman, 2005; MacKillop, Few, Stojek, et al., 2015), their taste (Filbey, Claus, Audette, et al., 2008; Oberlin, Dzemidzic, Tran, et al., 2013; Oberlin, Dzemidzic, Harezlak, et al., 2016), or a combination of these stimuli (Yoder, Morris, Constantinescu, et al., 2009; McCusker & Brown, 1990). The sight and smell of the preferred alcoholic beverage (Pomerleau, Fertig, Baker, & Cooney, 1983;
18 Monti, Binkoff, Zwick, et al., 1987; Rohsenow, Monti, Abrams, et al., 1992; Staiger & White, 1991; Yoon, Kim, Thuras, et al., 2006) as well as alcohol-related images (pictures/videos) (Payne, Rychtarik, Rappaport, et al., 1992; Witteman, Post, Tarvainen, et al., 2015; Vollstädt-Klein, Loeber, Richter, et al., 2012; but see: Mucha, Geier, Stuhlinger, & Mundle, 2000) or odors (Stormark, Laberg, Bjerland, et al., 1995; Schneider Habel, Wagner, et al., 2001) are also able to elicit increases in alcohol craving in humans with an alcohol use disorder. Additionally, negative mood induction alone can increase alcohol craving in humans with alcohol use disorder (Litt, Cooney, Kadden, & Gaupp, 1990), and pictures of alcoholic beverages induce more alcohol craving in humans with alcohol use disorder who also have mild/moderate depression symptoms (Wiers, Shumay, Volkow, et al., 2015). In humans with alcohol use disorder, exposure to alcohol use or stress-related imagery can also elicit increases in alcohol craving in (Fox, Bergquist, Hong, et al., 2007; Sinha, Fox, Hong, et al., 2009). The idea that the stimulus features of alcoholic beverages elicit alcohol craving in people due to a naturally-occurring classical conditioning process is supported by controlled conditioning study conducted in humans without alcohol use disorder by Field & Duka (2002) in which the sight and smell of a beverage that contained a low dose of ethanol (0.2 g/kg) during training (CS+) acquired the ability to elicit increased alcohol craving at test relative to the sight and smell of a beverage that did not contain ethanol during training (CS-).
3.1.2 Increased swallowing and salivation
The sight and smell of the preferred alcoholic beverage are able to elicit increased swallowing and salivation rate in humans with an alcohol use disorder (Kaplan, Cooney, Baker, et al.,1985; Monti, Binkoff, Zwick, et al., 1987; Pomerleau, Fertig, Baker, &
19 Cooney, 1983; Rohsenow, Monti, Rubonis, et al., 1994; Yoon, Kim, Thuras, et al., 2006). In at least one study, humans without alcohol use disorder also respond to these stimuli with increased swallowing and salivation (Kaplan, Cooney, Baker, et al.,1985). However, Field & Duka (2002) conducted a controlled discriminative conditioning experiment in humans without alcohol use disorder and found that the sight and smell of the beverage that contained a low dose of ethanol (0.2 g/kg) across training (CS+) did not acquire the ability to elicit increased swallowing and salivation at test relative to the sight and smell of a beverage that did not contain ethanol during training (CS-). Thus, there is no empirical support for the idea that the stimulus features of alcoholic beverages elicit swallowing and salivation in humans due to a naturally-occurring classical conditioning process. Whether a larger dose or more training sessions are needed to enable conditioning swallowing and salivation as cue-elicited anticipatory responses in humans remains to be seen.
3.1.3 Increased heart rate
In humans with and without alcohol use disorder, the sight and smell of the preferred alcoholic beverage are able to elicit an increase in heart rate that is sustained as the person initiates and/or completes the act of self-administering or ingesting the presented beverage, but dissipates shortly thereafter (Newlin 1985, 1986; Pomerleau, Fertig, Baker, & Cooney, 1983; Kaplan, Cooney, Baker, et al.,1985, Staiger & White, 1991). Increases in heart rate in humans with alcohol use disorder can also be elicited using only alcohol- related images (pictures/videos) (Payne, Rychtarik, Rappaport, et al., 1992; Witteman, Post, Tarvainen, et al., 2015) or alcohol-related odors (Stormark, Laberg, Bjerland, et al., 1995) or alcohol use-related imagery (Fox, Bergquist, Hong, et al., 2007; Sinha, Fox, Hong, et al., 2009).
20 The idea that the stimulus features of alcoholic beverages elicit anticipatory increases in heart rate due to a naturally-occurring classical conditioning process is supported by controlled conditioning study conducted in humans without alcohol use disorder by Staiger & White (1988). In that study, the sight and smell of a beverage that contained a moderate dose of ethanol (0.5 g/kg) during training (CS+) acquired the ability to elicit anticipatory increases in heart rate at test relative to the sight and smell of a beverage that did not contain ethanol during training (CS-).
3.1.4 Increased brain-level cue processing & activity in addiction-relevant circuits
In humans without alcohol use disorder, alcohol-related images also modulate event-related electroencephalographic (EEG) potentials (ERPs) such as the P100 and P300 as a function of individual differences in drinking pattern (Kroczek, Haeussinger, Hudak, et al., 2018; but see Martinovic, Jones, Christiansen, et al., 2014) and self-reported alcohol sensitivity (Bartholow, Lust, & Tragesser, 2010). These ERPs reflect pre-conscious perceptual processing and can be localized to brain regions but cannot typically be attributed to specific functional areas or nuclei. However, the blood oxygen level- dependent (BOLD) response measured in functional magnetic resonance imaging (fMRI) can be used to visualize stimulus-elicited activation or de-activation of specific areas of the human brain. Using the latter technique, specific areas of the human brain implicated in addiction and conditioning (e.g., amygdala, insula, medial prefrontal cortex, ventral striatum, dorsal striatum, midbrain dopamine nuclei) have been shown to activate in response to presentation of pre-existing/naturalistic alcohol cues (viz., presumably conditioned outside the laboratory) such as: alcohol-related words (Tapert, Brown, Baratta, & Brown, 2004; Ames, Grenard, He, et al., 2014) and images (pictures/videos) (Bach, Vollstädt-Klein, Kirsch, et al., 2015; Grüsser, Wrase, Klein, et al., 2004; Kim, Han, Min,
21 et al., 2014; Vollstädt-Klein, Wichert, Rabinstein, et al., 2010; Wiers, Shumay, Volkow, et al., 2015; Wrase, Grüsser, Klein, et al., 2002) as well as the sight, smell and/or flavor of preferred alcoholic beverages (Bragulat, Dzemidzic, Talavage, et al., 2008; Claus, Ewing, Filbey, et al., 2011; Filbey, Claus, Audette, et al., 2008; Kareken, Bragulat, Dzemidzic, et al., 2010; Kareken, Liang, Wetherill, et al., 2004; Kiefer, Kirsch, Bach, et al., 2015; Oberlin, Dzemidzic, Harezlak, et al., 2016; Schneider Habel, Wagner, et al., 2001). Importantly, the level of activation in some of these brain regions (specifically, striatum) induced by alcohol-related images has been shown to be stable within individuals over at least 2 weeks (Schacht, Anton, Randall, et al., 2011). In general, alcohol-related stimuli appear to activate the same brain regions in humans with and without alcohol use disorder; however, the level of activation in some brain regions (e.g., insula, dorsal striatum) may reflect disorder severity (Vollstädt-Klein, Wichert, Rabinstein, et al., 2010; Claus, Ewing, Filbey, et al., 2011). Some empirical support for the idea that the alcohol-related stimuli elicit (preconscious) brain activity in humans due to a naturally-occurring classical conditioning process can be derived from two studies in human subjects without alcohol use disorder conducted by David Kareken & colleagues. In the first study (Yoder, Morris, Constantinescu, et al., 2009), naturalistic alcohol cues (sight and smell) were presented to people without subsequent alcohol in the face of strong alcohol expectancies. The omission of expected alcohol produced negative reward prediction error that was measured as a decrease in dopamine release in the striatum using positron emission tomography (PET) methods. In the second study (Kareken, Grahame, Dzemidzic, et al., 2012), an arbitrary neutral visual stimulus (a geometric shape) was repeatedly paired with alcohol (18 mg/dL, intravenous infusions) across sessions. The arbitrary visual stimulus acquired the ability to elicit an expectation of subsequent alcohol infusion. This was revealed by the fact that 22 when the newly conditioned stimulus was presented and expected alcohol was omitted, a negative reward prediction error was produced that was measured as de-activation or negative BOLD response in the medial prefrontal cortex using fMRI methods.
3.2 Issues with studying cue reactivity in human subjects & reasons for non-human animal models
It is impossible to know whether reactions to alcohol cues in a person truly reflect a conditioning process because the experimenter likely had little to no control over the environment across the person’s drinking history. It is clearly possible to conduct experiments where naturalistic or neutral stimuli are paired with alcohol or drug in human subjects (e.g., Dafters & Anderson, 1982; Glautier, Drummond, & Remington, 1994; Field & Duka, 2002; Kareken, Grahame, Dzemidzic, et al., 2012). Theory can be also applied to test the idea that reactivity reflects conditioning. For example, it is possible to test whether a putative CS serves an effective US in a second-order conditioning paradigm. However, experiments of either sort in human subjects are costly in terms of time and money. Non-human animal models allow exquisite, if not total, experimental control over the subject’s daily and lifetime environments, which makes conducting conditioning experiments easier, more rigorous, and more interpretable. In the human situation, alcohol (availability/ingestion/intoxication)-associated stimuli are experienced in order, even if they co-occur in space. For example, the act of preparing an alcoholic beverage involves visual and auditory stimuli followed by olfactory stimuli, and the act of self-administering that beverage involves visual and olfactory stimuli followed by tactile and taste stimuli along with auditory stimuli. In the non-human animal model, spatial and temporal relationships between stimuli can be varied systematically in order to explore how they
23 determine the conditioned response (e.g., whether is a form of goal-tracking or sign- tracking appetitive response).
3.3 Non-human animal models of “wanting”
In rodents, it is especially easy to model cue-conditioned alcohol appetitive responses that in humans contribute to and/or manifest as attentional bias, approach tendency, craving. This means that rodent models of human alcohol “wanting” provide a scientifically rigorous preclinical way to dissect the biobehavioral causes of this form of alcohol cue-elicited reactivity and to the extent that it contributes to alcohol use disorder, test treatments for alcohol use disorder. However, the form of “wanting” responses acquired by rodents is highly dependent on the paradigm and its parameters. We consider these below before reviewing specific models.
3.3.1 Paradigm parameters & considerations
The major division in non-human animal models of human drug-related behavior has to do with whether the drug is administered by the model organism or the experimenter. Experimenter-administered drug can be used to study many of the conditioning effects of drugs in non-human animals. For example, drug-associated cue-facilitated behavioral tolerance to the drug’s post-ingestive effects. However, some features of human drug- related behavior may only emerge when drug is self-administered. For example, drug- associated cue-induced subjective arousal. Furthermore, even when a drug is self-administered, the motivational context matters. The fact that is impossible to reproduce human drug use or alcohol drinking motives in non-human animals does not mean that ecological validity goes out with the bathwater. Just like in humans, the (biological and behavioral) mechanisms underlying or
24 controlling alcohol-related behavior are likely to be different when the model organism is drinking alcohol-adulterated beverages to sate thirst or hunger than when it is drinking the same alcoholic beverage for its post-ingestive effects. In general, we know that different systems at the brain circuit, cell, and molecular level are involved in hedonically v. homeostatically-based fluid and food ingestion (Berridge, 2004).
3.3.2 Cue-elicited alcohol seeking behavior in self-administration paradigms
Oral alcohol self-administration paradigms in non-human animals provide the model with the most face-validity for human alcohol-related behavior. In the vast majority (so-called operant self-administration paradigms), cues are present and become associated with alcohol, but cue-elicited “wanting” is not studied per se. For this reason, we restrict our review to self-administration paradigms where the interest is in cue-elicited “wanting.” Cue-elicited behavior directed toward specific cues in the self-administration chamber including the magazine (viz., the alcohol container; e.g., fluid cup, sipper tube) may serve as useful models of human alcohol “wanting.” In paradigms where fixed amounts of drinking solution are delivered into an omnipresent magazine (e.g., those used in the laboratory of Patricia Janak), several factors interact to influence whether the cue acquires the ability to elicit cue-directed behavior or cue-elicited magazine-directed behavior or both, including the temporal relationship between cue and solution delivery, presence or absence of sweetener, food/fluid deprivation status, and the number of training sessions (Chaudhri, Sahuque, Schairer, & Janak, 2010; Krank, 2003; Krank, O’Neill, Squarey, & Jacob, 2008; Srey, Maddux, & Chaudhri, 2015; Villaruel & Chaudhri, 2015). In paradigms where time-limited opportunities to drink the solution are presented via a retractable magazine (sipper) (Tomie, Festa, Sparta, & Pohorecky, 2003; Tomie,
25 Miller, Dranoff, & Pohorecky, 2006; Tomie, Costea, Vohra, & Pohorecky, 2011), the temporal relationship between cue and drinking opportunity may be the most important, if not sole, determinant. If the drinking opportunity starts at cue offset, then the cue will likely come to elicit cue-directed behavior (because it does not interfere with subsequent drinking). If the cue and drinking opportunity co-occur, then the cue will likely come to elicit anticipatory magazine-directed behavior (because it facilitates drinking). Importantly, across all studies mentioned above, little to no cue-related behavior was observed in the explicitly unpaired cue-ethanol condition, indicating that cue-related behavior resulted from associative learning processes.
3.3.3 Alcohol-paired place preference
One of the simpler and more cost-effective non-human animal models of human drug cue learning & memory is the conditioned place preference paradigm. Although this paradigm is used by many researchers to determine whether non-human animals “like” the post-absorptive effects of a drug, some researchers maintain that it serves as a model of “wanting” because the place preference reflects the animal’s learned expectation of drug experience in that place. Among rodents, mice will exhibit preference for places paired with ethanol depending on whether the dose, experimenter-administration method and parameters, and other factors favor pairing with the initial, short-lived aversive or delayed rewarding effects of ethanol injection (Chester & Cunningham, 1999; Cunningham, Clemans, & Fidler, 2002). In contrast, in rats, dose, age, and sex interact to determine whether preference develops for places paired with ethanol injection (Torres, Walker, Beas, & O’Dell, 2014). Male rats, for example, may find experimenter-administered ethanol aversive independent of dose and administration route (Bormann & Cunningham, 1997, 1998; Cunningham,
26 1979, 1981; Fidler, Bakner, & Cunningham, 2004) Alternatively, a greater number of place-ethanol injection pairings may be required (Bozarth, 1990). Neither place avoidance nor preference is typically exhibited in the explicitly unpaired place-ethanol condition in these studies, indicating an associative learning process.
3.3.4 Alcohol-paired flavor preference
Another simple and cost-effective non-human animal model of human drug cue learning & memory is the conditioned flavor preference paradigm. As with the conditioned place preference, some researchers maintain that conditioned flavor preference can serve as a model of “wanting” because flavor preference reflects the animal’s learned expectation of subsequent drug exposure. Rodents will only acquire conditioned preference for flavors paired with experimenter-administered ethanol at younger ages (Cunningham, 1979; Pautassi, Godoy, Spear, & Molina, 2002; Pautassi, Myers, Spear, et al., 2008). However, rodents reliably acquire conditioned preference of flavors paired with self-administered ethanol (Cunningham & Niehus, 1997), even though the flavor of oral ethanol itself is initially aversive (viz., punishing or disliked) (Kiefer & Dopp, 1989). Neither flavor avoidance nor preference was exhibited in the explicitly unpaired flavor-ethanol condition in these studies, indicating an associative learning process.
3.4 Cue-elicited compensatory responses to alcohol in humans
Cue-conditioned compensatory responses (Siegel & Ramos, 2002), which are changes in physiology (e.g., heart rate, skin conductance) that oppose expected post- ingestive drug effects, are typically invoked to explain behavioral tolerance to drugs. However, in some theories of addiction/relapse (reviewed in Niaura, Rohsenow, Binkoff,
27 et al., 1988), conditioned compensatory responses can also contribute to and/or manifest as alcohol craving. For this reason, we review what cue-elicited compensatory reactions look like in humans and then non-human animal models, where it is easier to demonstrate that these are due to conditioning.
3.4.1 Increased skin conductance
In humans without alcohol use disorder, one of the post-ingestive effects of alcohol is a decrease in skin conductance level (Newlin, 1985), and the sight and smell of an alcoholic beverage are able to elicit an initial small increase skin conductance level that is sustained during and after drinking (Glautier, Drummond, & Remington, 1992; Newlin, 1985). Compared to humans without alcohol use disorder, those with alcohol use disorder exhibit a much larger increase in skin conductance level in response to the sight and smell of their preferred alcoholic beverage (Kaplan, Cooney, Baker, et al.,1985). Alcohol-related images alone are also able to elicit larger increases in skin conductance level in humans with alcohol use disorder than those without (Nees, Diener, Smolka, et al., 2012; Laberg, Hugdahl, Stormark, et al., 1992; but see: Wrase, Grüsser, Klein, et al., 2002). However, Glautier, Drummond & Remington (1994) conducted a controlled conditioning experiment in humans without alcohol use disorder and found that the sight and smell of the beverage that contained a moderate dose of ethanol (0.6 g/kg) across training did not acquire the ability to elicit changes in skin conductance level at test. Thus, there is no empirical support for the idea that the stimulus features of alcoholic beverages elicit this compensatory response in humans due to a naturally-occurring classical conditioning process. Whether a smaller or larger dose or more training sessions are needed to enable conditioning of a cue- elicited compensatory skin conductance response in humans remains to be seen.
28 3.4.2 Decreased heart rate
In humans without alcohol use disorder, increased heart rate (beats/min; tachycardia) is observed relative to baseline after self-administration of an alcoholic beverage containing a moderate dose of ethanol (e.g., 0.30-60 g/kg). This tachycardic effect of self-administered alcohol decreases with repeated self-administration of the same beverage in the same place but recovers when self-administration takes place in a new place (Dafters & Anderson, 1982), which shows that “tolerance” (decreases in drug response with repeated drug experience) in humans can be learned and elicited by specific environmental stimuli. Unfortunately, Dafters & Anderson did not test people in the original place after drinking a placebo alcoholic beverage, so their finding suggests, but do not show, that the original place acquired the ability to elicit a conditioned compensatory decrease in heart rate (bradycardia). However, this idea is supported by placebo alcohol (e.g., near beer) and placebo-controlled alcohol challenge studies (Newlin, 1985; 1986) and one controlled moderate dose (0.5 g/kg) conditioning study (Staiger & White, 1988) showing decreased heart rate during the post-drink period when people are tested in the placebo condition.
3.4.3 Increased vasoconstriction
In humans without alcohol use disorder, the sight and smell of an alcoholic beverage are also able to elicit peripheral vasoconstriction (decreased finger pulse volume) relative to a non-alcoholic beverage (Glautier, Drummond, & Remington, 1992). Support for the idea that this is a conditioned compensatory cardiovascular response comes from a controlled conditioning study conducted by Glautier, Drummond, and Remmington (1994) in humans without alcohol use disorder. In the latter study, the sight and smell of a beverage
29 that contained a moderate dose of ethanol (0.6 g/kg) during training acquired the ability to elicit peripheral vasoconstriction (decreased finger pulse volume) at test.
3.5 Non-human animal models of cue-elicited compensatory responses to alcohol
In rodents, injection of ethanol doses in the 1-3 g/kg range produce transient hypothermia (decrease in core body temperature). Places paired with this effect of ethanol can acquire the ability to elicit a compensatory hyperthermia (increase in core body temperature) response in rodents (Lê et al., 1979; Crowell et al., 1981; Mansfield & Cunningham, 1980). The internal state produced by injection of an ethanol dose that does not produce hypothermia (0.8 g/kg) can also be paired with the hypothermic effect of larger doses and acquire the ability to elicit a compensatory hyperthermia response (Greeley et al., 1984). No such cue-elicited reactivity was observed in the explicitly unpaired cue- ethanol condition of these studies, indicating an associative learning process. In rodents, ethanol injection or ingestion sufficient quantities (≥1 g/kg) produces sedative-like ataxia (decrease in locomotion). The act of self-administration, as a stimulus sequence, can be paired with this post-ingestive effect and acquire the ability to elicit a compensatory hypertaxia (increase in locomotion) response (Weise-Kelly & Siegel, 2001). No such cue-elicited reactivity was observed in the explicitly unpaired cue-ethanol condition, indicating an associative learning process.
4 HOW ALCOHOL CUE REACTIVITY DRIVES ALCOHOL USE
In humans, alcohol cue-related reactivity, especially in the form of a cue-elicited appetitive or “wanting” state, is believed to promote alcohol use in the moment through Pavlovian to instrumental transfer (PIT)-effects (Tomie, 1996; Holmes, Marchant, & Coutureau, 2010).
30 4.1 Pavlovian to instrumental transfer effects in humans
In humans without alcohol use disorder, the sight, smell, and/or taste of alcoholic beverages (Leeman, Corbin, & Fromme, 2009; MacKillop & Lisman, 2005; Perkins, Ciccocioppo, Jacobs, 2003), beverage preparation and presentation in a simulated bar (Johnson, & Fromme, 1994), the internal stimulus effects produced by ingesting at least 2 standard drinks (Chutuape, Mitchell, & de Wit, 1994; Corbin, Gearhardt, & Fromme, 2008; Wetherill & Fromme, 2009), alcohol-related images (pictures/videos) and words (Farris & Ostafin, 2008; Field & Jones, 2017; Hollett, Stritzke, Edgeworth, & Weinborn, 2017; Jasna, Jones, & Christiansen, et al., 2014; Roehrich, Goldman, 1995; Van Dyke & Fillmore, 2015; but see: Carter & Tiffany, 1999; Field, Mogg, & Bradley, 2005) as well as other cues and information regarding alcohol availability (Fromme & Dunn, 1992; Kruse, Radnovich, Kalapatapu, et al., 2012) are able to increase instrumental responding for alcohol (measured by ingestion amount or speed in ad libitum consumption tests or number of responses in operant self-administration tests). In humans with an alcohol use disorder, the sight and smell of the preferred alcoholic beverages (Rankin, Hodgson, & Stockwell, 1979) and/or or the internal stimulus effects produced by ingesting them are able to invigorate instrumental responding for alcohol (Ludwig, Wikler, & Stark, 1974; Bigelow, Griffiths, & Liebson, 1977) as do other internal cues (Mello & Mendelson, 1965; Nathan & O’Brien, 1971).
4.2 Non-human animal models of Pavlovian to instrumental transfer effects
In rodents, the initial adulteration of a sweet beverage with ethanol decreases its palatability and typically reduces instrumental response rates for the adulterated beverage. However, presenting a cue or context previously paired with experimenter-administered
31 ethanol (2-4 g/kg intragastric) attenuates that initial response rate reduction (Krank, 1989; Krank & O’Neill, 2002). In oral ethanol self-administration paradigms using rodents, cue-elicited “wanting” responses and instrumental responding for oral ethanol can be trained separately and then tested for interaction. In these tests, ethanol-associated cue-elicited “wanting” has been found to invigorate instrumental responding for oral ethanol (Corbit & Janak, 2007; Glasner, Overmier, & Balleine, 2005; Krank, 2003; Krank, O’Neill, Squarey, & Jacob, 2008). Given equivalent ethanol cue conditioning, a larger PIT effect is seen in rodents with an extended history of instrumental responding for oral ethanol (Corbit & Janak, 2016). This is in agreement with previous experiments showing that instrumental responding for oral ethanol in rodents with similar histories is controlled more strongly by presumably ethanol-associated antecedent stimuli than the consequences of ethanol self- administration per se (Corbit, Nie, & Janak, 2012, 2014).
4.3 Conclusions
Now that we have reviewed what cue reactivity looks like and how it promotes alcohol use in the moment, we can better appreciate how cue reactivity can create risk for lapse and relapse in alcohol use disorder. The next sections present one of the few available behavioral treatments that aims to reduce alcohol cue reactivity.
5 ALCOHOL CUE EXPOSURE THERAPY (CET)
5.1 Introduction to CET
5.1.1 History
The cue exposure and response prevention treatment paradigms arose from the implications of classical conditioning experiments in non-humans animals for the treatment 32 of maladaptive associative learning. The paradigms were originally developed for the treatment of fear and anxiety-related disorders and provide an evidence-based, relatively efficacious, symptom-specific treatment option (see meta-analytic reviews: Bandelow et al., 2015; Cusack et al., 2016; Carpenter et al., 2018). The paradigms were then adapted for the treatment of alcohol and substance use disorders by defining an alcohol or substance abuser’s “craving” as a complex system of learned behavioral and physiological reactions to alcohol or substance-associated stimuli. This meant that “craving” or cue-elicited urges to use might be treated the same way cue-elicited anxiety and fear were being treated; viz., using cue exposure and response prevention, with promising initial results in treatment of alcohol use disorders (Blakey & Baker, 1980).
5.1.2 Approaches to CET
Work is on-going to develop alcohol cue exposure therapy (CET) as a stand-alone treatment and/or as a component of comprehensive treatment programs for AUD (Monti & Rohsenow, 1999). Often, the other major component in the treatment is coping skills training (CST). CST involves teaching general social skills as well as situation-specific coping skills and training people on how to handle high-risk situations for relapse. CET stems from classical conditioning theories of relapse whereas CST stems from the social learning theory of relapse (Niaura et al., 1988; Marlatt, 1996). This is a common issue in psychosocial treatment outcome research. Many treatment paradigms, despite originating from different theoretical perspectives, ultimately train people in similar ways.
5.1.3 Basic structure
Any CET program begins with a thorough clinical assessment including measurement of the person’s level of reactivity to in response to alcohol-related and neutral
33 cues (3-5 min exposure trials). The modality of cue presentation may vary (see 5.2 below). The measures of reactivity taken also vary (see 5.3 below). People are tested in hunger- free and thirst-free state, so that these physiological drives do not exert undue influence on reactivity measurements. After initial assessment, the person is administered CET across 6-10 sessions (60- 90 min total duration). The structure of each session can vary, especially if there is a skills training component. In general, at least one discrete active cue exposure trial is given (8- 15 min duration), sometimes two or more. Often there is also continuous passive cue exposure because therapeutic props remain in plain view even when not in active use. Occasionally, a mixture of exposure modalities is used. In many cases, the therapist intervenes between discrete cue exposure trials or at the end of a trial block to teach a skill or help the person discuss his or her reactions. In a minority of cases, pure cue exposure is done where there is no therapist/administrator intervention.
5.1.4 Mechanisms of action
For the reasons outlined above, the active ingredients of CET are difficult to isolate. In cases where CET is mixed with CST, many forms of associative learning are engaged, including those that operate at the level of conscious awareness. In cases where more or less “pure” CET sessions are conducted, the major process believed to be at play is extinction, which refers to the learned suppression (or habituation) of conditioned reactions to specific stimuli. However, there is concern that the way even “pure” CET for alcohol and substance use disorders is conducted differs from how extinction procedures are conducted in the non-human animal models of classical conditioning that inspired them (Conklin & Tiffany, 2002).
34 5.2 Alcohol-associated stimuli targeted in CET
The most commonly targeted cues in alcohol CET are the sight and smell of the alcoholic beverages that the person drank most frequently before treatment (Monti et al., 1987; Monti et al., 1993; Monti et al., 2001). This involves exposure to bottles, cans, and glasses containing beverages with various colors, smells, tastes, textures, etc. The most common way of presenting stimuli in alcohol CET is in vivo auto- exposure. The person is asked to prepare themselves their usual alcoholic beverage him- or her-self (e.g., uncork the wine bottle and pour it into a stemless wineglass). The person is then asked to look at, hold, and smell the beverage, and focus on whichever sensory modality is most salient to them. In some cases, they may even be allowed to sip it for taste. Rarely, the person may be asked to drink to a certain blood alcohol concentration. The setting for these events is often a break room/living room-like environment, but occasionally, the setting is a simulated or real bar. In some cases, cue exposure is imaginal (Monti & Rohsenow, 2003) or in virtual reality (Lee & Kwon, 2007). Overall, what is presented in alcohol CET captures the sights, smells, sounds, and tastes that are experienced when people use alcohol; however, other alcohol-associated stimuli may still be missing (Laberg, 1990). For example, unless CET is done in a group setting for some people, normal social stimuli may be missing. For others, unless certain emotional states (e.g., sadness, stress) are induced, specific internal stimuli may be missing (Otto, Safren, & Pollack, 2004).
5.3 Measurement considerations
Although the cue-elicited self-reported urge to drink alcohol in response to cue exposure should be measured, it should not be the only measurement. In fact, physiological measures of reactivity that people either cannot self-report or self-report unreliably (e.g.,
35 activity in the nervous system, blood pressure, heart rate, salivation) are the most strongly related to risk for relapse (Drummond & Glautier, 1994; Garland et al., 2012; Garbusow et al., 2015; Grüsser et al., 2004; Rohsenow et al., 1994). Treatment philosophy informs what is measured as an outcome in treatment- outcome studies. For AUD treatments, the primary outcome is some measure(s) of drinking frequency and/or intensity. Depending on the treatment goal (e.g., abstinence, moderation), the following indicators can be measured: self-reported number of days abstinent in the follow-up period, self-reported number of consecutive days abstinent in the follow-up period, self-reported number of drinking days in the follow-up period, self-reported number of drinks per drinking day in the follow-up period, self-reported number of binge drinking episodes in the follow-up period, self-reported number of maximum drinks in a single drinking episode in the follow-up period. The reliability of self-report can be verified using drinking information collected from family and friends, continuous blood ethanol concentration monitoring via transdermal devices, or biomarkers of recent drinking such as phosphatidyl ethanol (Javors et al., 2016; Hill-Kapturczak et al., 2018).
However, the focus on whether some treatment, be it pharmacological or psychosocial, decreases drinking across the board seems to miss the point. Although, obviously, decreasing drinking frequency and/ intensity is the ultimate goal, it may be the case that a treatment prevents drinking in specific situations where it would have occurred otherwise (or that it reduces its intensity in those specific situations). If the number of such specific situations is lower for some reason during the follow-up period, then there would be fewer opportunities for the true treatment effect to manifest. For example, a drug that prevents stress-induced reinstatement in a non-human animal model of alcohol-related behavior may be developed as a medicine that can help people resist drinking to cope with stress. However, the medicine may manifest no net benefit on post-treatment drinking 36 outcomes if previous drinking-inducing stressors are absent during the follow-up period. Another consideration is that the treatment may not work, meaning it does not affect whatever underlying mechanisms it is meant to affect, on all individuals. An equally important consideration is that there may be a treatment effect, but it may not persist past a certain time post treatment without “booster” sessions. Too often, and understandably given how expensive these studies are, drinking outcomes are measured at a single post- treatment time. Together, these and other considerations motivate the idea of also obtaining measurements of the mediating variables on which the treatment is supposed exert its effects, and at multiple times. If, for example, we believe that cue reactivity (e.g., cue- elicited craving) can drive problematic drinking, then we should make sure that reductions in cue reactivity persist after treatment (e.g., by measuring reactivity in the lab at some post-treatment time), and then ask whether the treatment affected drinking, making sure to account for differential exposure to the relevant cues in daily life. Two problem social drinkers for whom social drinking cues were targeted in CET may show different drinking- related treatment outcomes over the follow-up period if one of the two individuals had less exposure to social events during that time, which may show up as a false positive effect of treatment if the person did not drink too often or too much outside such situations before treatment.
5.4 Efficacy of alcohol CET
When measured immediately after treatment in 4 controlled experiments, alcohol CET appears to decrease measures of reactivity as diverse as activation of the ventral striatum in BOLD-fMRI (Vollstädt-Klein, Loeber, & Kirsch, 2011), self-reported drinking urge (Monti et al., 1993; Rankin et al., 1983), latency to finish a drink (Rankin et al., 1983), and salivation (Monti et al., 1993).
37 Alone, CET can be as efficacious as standard cognitive-behavioral treatment in reducing relapse to drinking in individuals with AUD (Drummond & Glautier, 1994; Loeber et al., 2006) Combined with CST, CET may effectively reduce relapse to drinking (Monti et al., 1993; Rohsenow et al., 2001; Monti et al., 2001). CET appears to be effective in either an individual or group format (Monti et al., 2001; Rohsenow et al., 2001), but individualized sessions are recommended for maximal efficacy (Monti & Rohsenow, 2003). CET has been tested on people suffering from an alcohol use disorder who are at varying stages of treatment with varying histories of physical dependence. Although few randomized clinical trials of CET for AUD have been conducted, at least one meta-analysis has been conducted (Mellentin et al., 2017). Its conclusion was that alcohol CET might provide a small benefit on measures of drinking and relapse to AUD relative to active control treatments, but that the overall quality of evidence was low. The authors called for more studies with better methodology.
5.5 Conclusions
Despite promise as a treatment tool, CET may leave individuals susceptible to the return of conditioned reactions with stress, exposure to non-extinguished cues and contexts as well as the passage of time, which may in part explain eventual relapse to problematic drinking.
6 EFFICACY OF CET IS LIMITED BY THE INTRINSIC LIMITATIONS OF EXTINCTION
6.1 Known persistence of reactivity after cue extinction
Standard extinction (repeated exposure to a CS without subsequent US) can lead to a suppression of conditioned reactivity, but it is well known that reactivity can and does readily reemerge, as evidenced by the post-extinction, relapse-like phenomena of
38 spontaneous recovery, cue-induced reinstatement, context-induced reinstatement (renewal), priming-induced reinstatement, and stress-induced reinstatement (Bouton and Bolles, 1979a, b; Rescorla and Heth, 1975; Robbins, 1990). Spontaneous recovery was described earlier (Section 2); it refers to return to a previous level of performance simply due to the passage of time. Reinstatement refers to the ability of a stimulus—such as an emotional state (e.g., stress), a CS or context that was not extinguished, the internal stimulus effects of the drug, or a combination of these—to bring back the CR after CS extinction. Additionally, there is evidence for rapid reconditioning after extinction (Bouton et al., 2004). In cases where an alternative response was reinforced during CS extinction, subsequent non-reinforcement of the alternative response can cause resurgence of reactivity to the extinguished CS (Bouton, Winterbauer, & Todd, 2012).
6.2 Explaining persistence from a memory competition perspective
One perspective on why conditioned reactivity persists despite extinction is that standard extinction protocols generally facilitate the formation of a new inhibitory association between the conditional stimulus (CS) and the unconditional stimulus (US) (CSàno US; Bouton, 2004). These new response-inhibiting memories must then compete with existing response-exciting memories. There are at least 3 reasons why the new response-inhibiting memories may lose in competing for expression. First, the response- inhibiting memory has not been as intensively trained as the existing response-exciting memory. The number of times CS has not been followed by US is tiny relative to the number of times CS has been followed by US. Second, the response-inhibiting memory has not been as extensively trained as the response-exciting memory. Situations in which the CS has not been followed by US may be restricted to a single context (e.g., in the treatment center) whereas situations in which the CS has been followed by US have
39 occurred in multiple contexts (e.g., in different bars, among different groups of friends). Third, due to its relative youth, the newly acquired response-inhibiting memory has also not had as much time to integrate into the person’s broader network of memories (alcohol- associated and not).
6.3 Conclusions
The fundamental goal of CET is to reduce the risk for relapse created by drug- associated conditional stimuli people may encounter while going about their daily lives. These cues can trigger problematic behavior whether the person is or is not consciously aware of the cue-behavior link. Alas, the cue extinction sessions conducted in CET neither erase nor reverse maladaptive CS-drug associations. Even when CET works, it leaves people susceptible to the return of CR. Thus, there exists a great need to improve how we conduct CET, especially its cue extinction sessions, to persistently attenuate the ability of drug-associated conditional stimuli to drive relapse.
7 IMPROVING ALCOHOL CET BY APPLYING THE NEUROBIOLOGY OF LEARNING & MEMORY
7.1 Basics of memory
7.1.1 Forming and maintaining long-term memories
Short-term memory refers to information about the environment that is immediately albeit only temporarily accessible, and working memory refers to contents of short-term memory being used or expressed in behavioral output (Cowan, 2008). Short-term memory can be stored for later use by formation of a long-term memory, which entails biological processes collectively known as “consolidation.” When long-term memories are retrieved, the information can be used or expressed in behavioral output. Under certain conditions, it
40 becomes important to update the contents of that long-term memory, which entails distinct biological processes collectively known as “reconsolidation.”
7.1.1.1 Consolidation
Consolidation refers to biochemical changes at the synaptic level believed to be responsible for long-term memory formation. Although some of the changes are presumably specific to the brain systems involved and/or the type of information being stored, there are some commonalities. Retention of recently learned information can be impaired if shortly after initial learning, protein synthesis is inhibited (e.g., Flexner, Flexner, & Stellar, 1965) or competing information is presented (e.g., Walker, Brakefield, Hobson, & Stickgold, 2003). In contrast, retention can be improved when certain drugs are given shortly after initial learning (Packard, 1999). None of these are observed when the manipulation is given after a sufficiently long delay (in general, 5-6 hr or more). As such, there is a consolidation “window.”
7.1.1.2 Reconsolidation
Reconsolidation refers to distinct biochemical changes at the synaptic level believed to be responsible for some of the flexibility of long-term memory, including its susceptibility for distortion over repeated retrieval (Schacter, Guerin, & St. Jacques, 2011). Although some of the changes are presumably specific to the brain systems involved and/or the type of information being stored, there are some commonalities. Retention of remembered information can be impaired if shortly after retrieval, protein synthesis is inhibited (e.g., Nader, Schafe, Le Doux, 2000) or new information is presented that competes or conflicts with what was remembered (e.g., Walker, Brakefield, Hobson, & Stickgold, 2003). In contrast, retention of remembered information can be improved when
41 certain drugs are given shortly after retrieval (Schramm, Everitt, & Milton, 2016). None of these are observed when the manipulation is given after a sufficiently long delay (in general, 5-6 hr or more). As such, much like there is a consolidation “window,” there is a reconsolidation “window.” A key feature of reconsolidation is that it occurs only if retrieval takes place under certain conditions. Specifically, retrieval must destabilize the long-term memory. Although we do not yet know all the conditions under which retrieval will destabilize, and whether those will hold across memory types, considerable evidence has accumulated to know about some. For example, in memory for CS-US associations, a major reconsolidation- inducer is surprising omission of the US; that is, production a sufficiently large negative prediction error (Pedreira, Pérez-Cuesta, Maldonado, 2004; Piñeyro, Monti, Alfei, Bueno, Urcelay, 2014; Reichelt & Lee, 2012; Flavell & Lee, 2013). The biochemical mechanisms by which surprising omission of the US destabilizes the long-term memory remain unclear. For example, it may be a consequence of neuromodulator released by cells in a signal- detection or stress-responsive circuit onto the cells maintaining the retrieved long-term memory. In contrast, surprising omission of the US appears to be insufficient to induce reconsolidation of memory for highly-trained instrumental responses (e.g., operating a device to obtain a desired outcome); instead, a sufficiently surprising change in response- outcome contingencies must take place (Exton-McGuinness, Patton, Sacco, & Lee, 2014).
7.2 Harnessing reconsolidation-based memory updating to treat maladaptive behavior
The fact that retrieval of a long-term memory can, under certain circumstances, induce reconsolidation means that the simple act of “remembering” can create a period where the memory is vulnerable. Specific pharmacological agents given during the
42 reconsolidation window may be able to ablate the memory altogether (viz., erase it), or modify specific properties (e.g., its emotional salience). However, many of the agents shown to accomplish these feats in preclinical non-human animal models, such as protein synthesis inhibitors, may be too toxic to use in humans. Additionally, those agents acceptable for use in humans, such as the beta-adrenergic receptor antagonist propranolol, have not lived up to the potential identified in the non-human animal models (Kindt, Soeter, & Vervliet, 2009; Lonergan, Brunet, Olivera-Figueroa, Pitman, 2013). All is not lost, however. New information acquired during the reconsolidation window may be able to modify specific properties of the memory (e.g., its ability to elicit a behavioral response). It is important to remember that new learning and behavioral performance both entail transient biochemical changes across various levels of organization (synapses, circuits, systems). This means behavior therapy, such as CET, deployed during the reconsolidation window has the potential to interfere or integrate with the memory. Behavior therapy is safe and tolerated by humans.
7.2.1 Cue memory retrieval + cue extinction: harnessing reconsolidation-based memory updating for CET
In 2009, Monfils, Cowansage, Klann, & Ledoux proposed a novel variation on cue exposure therapy for fear-provoking conditional stimuli (CS) based on the idea that the memory reconsolidation window represented not only a window of vulnerability, but also a window for opportunity for updating the contents of existing memories. In her procedure, the CS was presented but not followed by the unconditional stimulus (US; here: mild electric shock) to retrieve and destablize memory for the CS-US association. After a strategic delay (at least 10 min but no more than 5 hr in her experiments), a block of multiple extinction (CSàno US) trials on a shorter inter-trial interval is given such that
43 new learning takes place while memory for the CS-US association is restablizing. Monfils showed that this slight variation on the standard extinction procedure reduced spontaneous recovery, renewal, reinstatement, and reconditioning of the CS-elicited fear response in rats (2009). Thus, her procedure appeared to be able to modify the original memory (viz., degrade the response-exciting CSàUS association) rather than create a new memory (viz., train a response-inhibiting CSàno US association).
7.2.1.1 Promising (preclinical) results
Subsequent demonstrations of reconsolidation-based behavioral updating in human (e.g., Schiller, Monfils, Raio, et al., 2010) and non-human animal models (e.g., Flavell Barber, & Lee, 2011) alike generated considerable interest in preclinical and clinical areas of anxiety and fear disorder research. The fields of alcohol & drug abuse research caught on quickly (e.g., Xue, Luo, Wu, et al., 2012; Sartor & Aston-Jones, 2013). In 2016, a meta- analysis by Kredlow & colleagues (2016) found support for a benefit of retrieval plus extinction over extinction alone across preclinical models of maladaptive memory (fear, food, and abused substances) in humans and non-human animals. At least 17 experiments attempting to replicate Monfils’ initial findings or test the idea in a new paradigm have been published since Kredlow & colleagues’ review. Some of these were strikingly successful (Luo, Xue, Liu, et al., 2015; Germeroth et al., 2017); others were not (Goode, Holloway-Erickson, & Maren, 2017; Luyten & Beckers, 2017).
7.2.1.2 Potential for improving efficacy of alcohol CET
We know that alcohol-related cue memories can undergo reconsolidation in both rats (Barak et al., 2013; von der Goltz et al., 2009; Milton et al., 2012; Schramm et al., 2016) and humans (Das et al., 2015). However, we do not know whether retrieval +
44 extinction will be able to persistently attenuate alcohol cue reactivity. In 2013, Millan and colleagues set out to test this possibility. However, the retrieval episode used in that study was shown to be incapable of inducing memory reconsolidation (Hernandez & Kelley, 2004; Flavell & Lee, 2013; Exton-McGuiness et al., 2014), so no valid conclusions could be drawn about the potential benefit or risk of retrieval + extinction for alcohol cue reactivity. Additionally, conditioned behavior in that study was unlikely to be specific for alcohol because rats were food and water deprived except for 1 hr after conditioning sessions, limiting the relevance of any findings derived from their paradigm to alcohol- associative memory in humans.
7.3 Conclusions
Given the potential for rapid translation and improved treatment outcomes, I proposed to examine whether retrieval + extinction could persistently attenuate alcohol cue reactivity in a preclinical rat model.
8 TESTING THE POTENTIAL OF MEMORY RETRIEVAL + EXTINCTION FOR ALCOHOL CET
In Chapter 2, I present an initial test of the ability of memory retrieval + extinction to persistently attenuate alcohol cue reactivity using a novel preclinical model of alcohol cue reactivity in rats that I developed specifically for this purpose. In Chapter 3, I present an initial but in-depth analysis of alcohol cue reactivity in the preclinical rat model that I developed. In Chapter 4, I confirm that alcohol cue reactivity in the preclinical rat model that I developed stems from associative learning, which is believed to be the basis for alcohol cue reactivity in human. In Chapter 4, I demonstrate that alcohol-associated cue reactivity in my preclinical rat model is not a sex-specific phenomenon, which is important because in humans, both sexes exhibit maladaptive alcohol cue reactivity. In Chapter 6, I
45 conclude by summarizing key findings across my experiments, acknowledging open questions relevant to the potential, translation, and application of the memory updating strategy to alcohol cue exposure therapy, and pointing potential ways forward.
46 Chapter 2. Cue memory retrieval + extinction attenuates alcohol cue reactivity in rats1
2.1 ABSTRACT
Conditioned responses to alcohol-associated cues can hinder recovery from alcohol use disorder (AUD). Cue exposure (extinction) therapy (CET) can reduce reactivity to alcohol cues, but its efficacy is limited by phenomena such as spontaneous recovery and reinstatement that can cause a return of conditioned responding after extinction. Using a preclinical model of alcohol cue reactivity in rats, we evaluated whether the efficacy of alcohol CET could be improved by conducting CET during the memory reconsolidation window after retrieval of cue-alcohol associations. Rats were provided with intermittent access to unsweetened alcohol. Rats were then trained to predict alcohol access based on a visual cue. Next, rats were treated with either standard extinction (n=14) or memory retrieval + extinction (n=13). Rats were then tested for long-term memory of extinction and susceptibility to spontaneous recovery and reinstatement. Despite equivalent extinction, rats treated with memory retrieval + extinction exhibited reduced spontaneous recovery and reinstatement relative to rats treated with standard extinction. Memory reconsolidation-based CET shows promise for persistently attenuating the risk to relapse posed by alcohol cues in individuals with AUD.
2.2 INTRODUCTION
Drinking episodes involve taking multiple drinks of an alcoholic beverage in relatively close succession. Repetition of such episodes allows the sight, smell, and taste
1 This work was previously published: Cofresí, R. U., Lewis, S. M., Chaudhri, N., Lee, H. J., Monfils, M.- H., & Gonzales, R. A. (2017). Postretrieval Extinction Attenuates Alcohol Cue Reactivity in Rats. Alcoholism: Clinical & Experimental Research, 41(3), 608–617. http://doi.org/10.1111/acer.13323 Dissertator contributed to the conception, design, data collection, analysis, interpretation, and writing of the study. 47 of alcoholic beverages, as well as the contexts in which these sensory stimuli occur, to become conditioned as cues for alcohol availability, ingestion, and intoxication. Consequently, these conditioned cues alone can increase the urge to drink (craving) and produce physiological responses (Niaura et al., 1988). Importantly, reactivity to alcohol cues has been linked to a higher risk of relapse (Monti et al., 1993; Drummond & Glautier, 1994; Rohsenow et al., 1994; Papachristou et al., 2014). Systematic exposure to alcohol-associated cues without subsequent alcohol ingestion (cue exposure therapy, CET) may help reduce the risk for relapse posed by these cues in daily life (Monti & Rohsenow, 1999; Rankin et al., 1983). When combined with other cognitive and behavioral techniques, CET may also effectively reduce relapse to drinking (Monti et al., 1993; Rohsenow et al., 2001). As stand-alone therapy, cue exposure has also been found to reduce drinking levels self-reported by heavy drinkers (Drummond & Glautier, 1994), and to be as efficacious as standard cognitive-behavioral treatment in reducing relapse to drinking in individuals with AUD (Loeber et al., 2006). Cue exposure therapy also increased perceived ability to control cravings and resist the urge to drink
(Loeber et al., 2006). Despite promise as a treatment tool, CET may leave individuals susceptible to the return of conditioned reactions with stress, exposure to non-extinguished cues and contexts as well as the passage of time, which may in part explain eventual relapse to problematic drinking. One reason for this enduring reactivity may be that standard CET protocols generally facilitate the formation of new inhibitory associations between the cues and their predicted event (Bouton, 2004). These new inhibitory memories must then compete with the excitatory memories acquired over the individual’s drinking history for control over behavior.
48 A potential way to reduce the persistence of reactivity to conditioned alcohol cues may be by updating existing long-term memories with response-inhibiting information, which can be achieved by conducting CET during a period of memory instability—the memory retrieval-induced memory reconsolidation window. Convergent evidence suggests that giving cue exposure during the reconsolidation window (memory retrieval + extinction) can ameliorate the problem of enduring reactivity to cues after treatment (Kredlow et al., 2016). Memory retrieval + extinction was first shown to persistently attenuate the return of cued fear in rats (Monfils et al., 2009). This manipulation was then adapted to persistently attenuate the return of fear responses in humans (Schiller et al., 2010). Since then, memory retrieval + extinction has been applied to attenuate conditioned responses in rats after appetitive conditioning with grain or sucrose pellets (Olshavsky et al., 2013a; Flavell et al., 2011; Flavell & Lee, 2013), as well as morphine or cocaine (Ma et al., 2012; Xue et al., 2012; Sartor & Aston-Jones. 2013). Using a newly developed alcohol cue conditioning paradigm in outbred male rats, we set out to establish whether memory retrieval + extinction could persistently attenuate alcohol cue reactivity. If so, then a simple procedural modification might improve treatment outcomes following cue exposure therapy for AUD.
2.3 METHODS & MATERIALS
2.3.1 Subjects
Adult, male Long-Evans rats from Harlan (now Envigo; Indianapolis) (n=37) were used. Rats weighed 250-275 g upon arrival and were singly housed (22±2 ºC; 12hr light cycle; procedures conducted during light phase) in homecages containing bedding. Unrestricted chow and tap water were available throughout. Rats received 1 week to acclimate, during which time they were weighed daily. Ethanol (v/v) solutions were 49 prepared every 3 days from 95% ethyl alcohol (ACS/USP grade, Pharmco-AAPER) and tap water. Solutions were kept and served at room temperature (20 ºC). All procedures were approved by our Institutional Animal Care and Use Committee and conducted in accordance with NIH guidelines.
2.3.2 Behavioral Methods
2.3.2.1 Apparatus
Phases 2 thru 4 took place in Med Associates, Inc. (Fairfax, VT) conditioning chambers (interior dimensions: 30.5 cm L x 24.1 cm W x 29.2 cm H) housed in sound- attenuating cubicles. Each cubicle was equipped with a digital video camera (KT&C USA, Fairfield, NJ) and an exhaust fan. Each MedPC-controlled chamber was equipped with a houselight and retractable bottle assembly. The houselight was installed facing downward as the top center panel of the right chamber wall. The retractable bottle assembly was placed on the right panel of the front wall such that the hole through which the metal sipper inserted into the chamber was approximately 8.5 cm above the grid floor. The sipper hole was approximately 8.5 cm to the right and 16 cm lower than the houselight.
2.3.2.2 Experiment Phase 1: Alcohol Drinking in the Homecage
After acclimation to the facility, the rats (approximately 300 g) received unsweetened ethanol solution in the homecage (15% ethanol in tap water; v/v; 15E) for 24 hr sessions on an intermittent schedule (MWF) across 5 weeks (Figure 2.1 A) (Sparks et al., 2014). Placement of 15E and water bottles on the cage was alternated (L/R) across sessions. Rats were weighed before every session. Bottles were weighed before and after every session, with a control cage used to correct for evaporation and spillage. Two water
50 bottles were provided on “off” days. In order to minimize attrition, rats failing to drink doses > 0.5 g/kg on session 1 and 2 were provided with 5% ethanol in tap water (v/v; 5E) on subsequent sessions until a dose ≥ 1 g/kg was achieved for 4 sessions in a row. Next, 10% ethanol in tap water (v/v; 10E) was provided until the same criterion was met. If so, 15E was provided again unless fewer than 4 sessions remained, in which case the rat was kept on 10E. Rats drinking enough 10E or 15E to achieve ≥ 1 g/kg on average across the last 3 sessions were retained for conditioning (32 out 37).
2.3.2.3 Experiment Phase 2: Cue Conditioning
Rats were habituated to the conditioning chambers and stimuli (described above) in a single session (34-36 min total duration) conducted 48 hr after the last homecage ethanol drinking session. No bottles were loaded into the retractable bottle assembly during habituation, so there was no sipper presentation. Following habituation, rats underwent cue conditioning across 12 consecutive days (Figure 2.1 B). During each session, there were 8 trials using a variable intertrial interval (ITI) (Figure 2.1 C). The ITI was selected randomly from a list (160 s, 240 s, 240 s, 250 s, 320 s, 320 s, 350 s, 360 s) until values were exhausted, at which point all values became options again. The first trial began after a 5 min wait period and was signaled by onset of the cubicle exhaust fan. The session ended once the final ITI (selected after trial 8) had elapsed and this was signaled by exhaust fan offset. During each of these trials, the houselight was illuminated for 20 s. After 10 s, the retractable bottle assembly motor was activated to insert a metal sipper into the chamber. Licking the sipper produced ethanol. The sipper contained a ball bearing to prevent spillage upon insertion and retraction, and was attached to a bottle was filled with either 10E (n=6) or 15E (n=21) depending on which solution the rat drank across the last 3 homecage ethanol drinking sessions. Different
51 ethanol concentrations were maintained during this phase to prevent attrition in conditioning that might have arisen from switching rats that had previously received 10E to 15E. Thus, during a conditioning trial (Figure 2.1 F), the houselight was illuminated for 20 s and the sipper was inserted 10 s after light onset such that ethanol access and light presentation co-terminated. Only rats drinking ≥ 0.3 g/kg on average across the last 3 cue conditioning sessions were retained for subsequent phases (27 out of 32). After the final session, rats were subdivided into two groups matched on ingested doses. Assignments made on this basis were later found to have similar acquisition and final level of cue-conditioned behavioral responses. The 10E-drinking rats were split evenly between groups.
2.3.2.4 Experiment Phase 3: Cue Extinction with or without Initial Retrieval
Rats began 14 consecutive days of “retrieval-extinction” or “no retrieval- extinction” treatment 24 hr after the last cue conditioning session (Figure 2.1 B). Each day (Figure 3.1 D), rats undergoing “retrieval-extinction” (n=13; Ret-Ext) experienced a cue memory retrieval episode followed by 1 hr in the homecage and then a cue extinction session. Rats undergoing “no retrieval-extinction” (n=14; NoRet-Ext) experienced a context exposure episode followed by followed by 1 hr in the homecage and then a cue extinction session. The cue memory retrieval episode consisted of an isolated trial in which the houselight was illuminated for 20 s with co-terminating sipper presentation starting 10 s after houselight onset. Importantly, there was no ethanol present in the sipper or anywhere in the cubicle (Figure 2.1 G). This single trial was flanked by 2 variable ITIs. The first ITI was selected after a 2 min wait period and was signaled by cubicle exhaust fan onset. The episode ended when the second ITI elapsed and was signaled by exhaust fan offset. NoRet-
52 Ext rats experienced session start and end signals (exhaust fan onset and offset, respectively), but were not given the isolated extinction trial. All rats were then returned to their homecages for 1 hr. Subsequently, all rats were returned to the conditioning chambers for the cue extinction session. Session onset, signaled by the exhaust fan, occurred after a 2 min wait period. NoRet-Ext rats were given 12 extinction trials (as described immediately above, with variable ITI as described in Phase 2). The session ended when the final ITI (selected after trial 12) elapsed and was signaled by exhaust fan offset. Ret-Ext rats experienced session start and end signals (exhaust fan onset and offset, respectively) as well as trials 1- 11, but were not given trial 12. All rats were then returned to their homecages until the next day. These treatments involved the same amount of cue and context exposure (duration and frequency) in the absence of ethanol (i.e., under extinction conditions). The only difference was exposure to the cue plus context vs. only context 1 hr before an extinction protocol.
2.3.2.5 Experiment Phase 4: Testing
All rats underwent a long-term memory test (LTMT) to determine the persistence of extinction of cue-elicited responses 48 hr after the last extinction session. LTMT was a 4-trial cue extinction session (same variable ITIs described in Phase 2) (Figure 2.1 E and G). Two days later, the rats underwent a test for the ability of ethanol odor to reinstate cue- elicited responses (reinstatement test: RT). RT was also a 4-trial cue extinction session except that an open vial of 10E or 15E was placed out of sight and out of reach inside the sound-attenuating cubicle to provide ethanol odor (Figure 2.1 E and H). In both tests, response return was expected to occur on trial 1 and extinguish across trials 2-4.
53 2.3.3 Data collection
All trials were sampled for behavioral states from digital video recordings by making instantaneous observations every 1.25 s starting 5 s prior to houselight onset as in Chapter 2. At each observation during the 5 s before houselight onset (trial phase preCS), the 1st 5 s of houselight (trial phase CS1), and 2nd 5 s of houselight (trial phase CS2), the mutually exclusive rating options were “sipper site approach” (approaching, attending to, or exploring the sipper insertion hole, including sniffing, gnawing, and clawing at the hole) or “other” (e.g., grooming, resting, rearing). During the 1st 5 s of sipper presentation (3rd 5 s of light; trial phase CS3) and 2nd 5 s of sipper presentation (4th 5 s of light; trial phase CS4), an additional mutually exclusive rating option was possible: “sipper contact” (presumed licking: snout occluding sipper, snout angled toward and close enough to sipper plus rapid whisker movement). Observations were made by highly trained judges (≥95% agreement on joint ratings) who were blinded to treatment conditions. For every trial in every session, we counted the incidence of each behavioral state within each trial phase for every rat. Only 4 observations were made per trial phase, so the maximum behavior frequency per trial phase on any trial of any session was 4. During Phase 1 and 2, we also monitored the dose of ethanol self-administered by each rat across sessions. Drinking solution intake was measured as the difference in bottle weight pre- and post-session after correcting for spillage. The grams of solution ingested were then converted to g ethanol and dose ingested was expressed as g/kg body weight for each rat.
2.3.4 Data analysis
Our main goal was to test whether Ret-Ext could reduce spontaneous recovery and reinstatement of houselight-elicited sipper site approach (trial phases CS1 and CS2) and
54 sipper-elicited sipper contact (trial phases CS3 and CS4) relative to NoRet-Ext. Since hypotheses were directional (NoRet-Ext > Ret-Ext), planned comparisons were made using one-tailed t-tests. We also confirmed that response decay during cue extinction was comparable between treatment groups and that rats in each group were matched in histories of cue conditioning and drinking using mixed factorial ANOVA and simple effects analysis. Post hoc comparisons were made using two-tailed t-tests. Statistical significance was met at p<0.05.
2.4 RESULTS
2.4.1 Matched history of homecage alcohol drinking.
Rats in groups NoRet-Ext (n=14) or Ret-Ext (n=13) drank similarly across the initial 5-week homecage alcohol pre-exposure phase (group x session and group effect: NS). As can be seen in Figure 2.2, ingested doses increased over sessions (session effect:
F14,350=12.71, p<0.05). Across the last 3 sessions, the grand mean±sem dose per session was 3.52±0.23 g/kg (n=27).
2.4.2 Matched history of alcohol cue conditioning.
Rats in groups NoRet-Ext (n=14) and Ret-Ext (n=13) learned similarly to anticipate alcohol access based on the visual cue. Sipper site approach during trial phase preCS (5 s bin before light onset) was constant across sessions (Figure 2.3 A) whereas approach during trial phases CS1 (1st 5 s of light) and CS2 (2nd 5 s of light) increased across sessions
(Figure 2.3 B and C, respectively) (trial phase x session interaction: F22,550=2.085, p<0.05). These patterns did not vary by group (group x trial phase x session, group x trial phase, group x session, and group effect: NS).
55 Rats in both groups also learned similarly to interact with the alcohol access device (sipper). Sipper contact during trial phases CS3 (3rd 5 s of light, 1st 5 s of sipper) and CS4 (4th 5 s of light, 2nd 5 s of sipper) increased across sessions (Figure 2.3 D and E, respectively) with contact during trial phase CS4 reaching a higher level by the end of the conditioning protocol (trial phase x session interaction: F11,275=2.19, p<0.05). These patterns did not vary by group (group x trial phase x session, group x trial phase, group x session, and group effect: NS). Finally, rats in both groups also drank similarly across conditioning (Figure 2.3 F).
Ingested ethanol doses increased over sessions (session effect: F11, 275=47.32, p<0.05), and this pattern did not vary by group (group x session and group effect: NS). Across the last 3 sessions, the grand mean±sem dose per session was 0.50±0.03 g/kg (n=27).
2.4.3 Equivalent extinction of conditioned responses to alcohol predictive cues.
NoRet-Ext (n=14) and Ret-Ext (n=13) rats exhibited equivalent extinction of visual cue-elicited approach to the former site of alcohol access. Sipper site approach during trial phase preCS remained at floor across treatment days (Figure 2.4 A), while approach during trial phases CS1 and CS2 decreased across treatment days (Figure 2.4 B and C, respectively) (trial phase x treatment day interaction: F26, 650=2.83, p<0.05). These patterns did not vary by treatment group (group x trial phase x treatment day, group x trial phase, group x treatment day, and group effect: NS). Interaction with the sipper also extinguished similarly between treatment groups. Sipper contact during trial phases CS3 and CS4 decreased across treatment days (Figure 2.4 D and E, respectively). On some treatment days, responding differed by trial phase differently for each group (group x trial phase x treatment day interaction: F13, 325=1.79,
56 p<0.05), but day-by-day extinction did not vary by group (group x treatment day and group effect within each trial phase: NS). By the end of extinction (last 4 trials of E14), approach and contact (Figure 2.4 F and G, respectively) were at floor in both treatment groups (main effects of group, trial, and trial phase, all interactions: NS). This means that treatment groups not only extinguished similarly day-by-day, but also to the same final level. Analysis of responding on the first trial of each treatment day (trial 1 for group Ret- Ext is the retrieval trial; Figure 2.5) further confirmed similar day-by-day extinction. Sipper site approach during trial phase preCS remained at floor, but decreased over days during trial phases CS1 and CS2 (trial phase x treatment day interaction: F26, 650=7.96, p<0.05). This pattern did not vary by group (group x trial phase x treatment day interaction: NS). Sipper contact during trial phase CS3 and CS4 decayed differently across treatment day
(trial phase x treatment day interaction: F13, 325=2.34, p<0.05), but the patterns of decay did not vary by group (group x trial phase x treatment day interaction: NS).
2.4.4 Retrieval-extinction confers protection against early spontaneous recovery and alcohol odor-induced reinstatement.
As expected, in the long-term memory test (LTMT) and reinstatement test (RT) response return was observed on trial 1, but rapidly extinguished across trials 2-4 (main effect of trial in each test: F3, 75 >=3.70, p<0.05; group x trial interaction in each test: NS; data not shown). To assess vulnerability to short-term spontaneous recovery following Ret-Ext and NoRet-Ext treatment, we first examined whether responding on LTMT trial 1 varied between groups relative to each subject’s baseline response level at the end of extinction (average response level across E14 trial 9-12). Neither group exhibited spontaneous
57 recovery of trial phase CS1 sipper site approach (Figure 2.6 B). However, spontaneous recovery was reduced in Ret-Ext-treated rats (n=13) relative to NoRet-Ext-treated rats (n=14) for sipper site approach during trial phase CS2 (test–baseline for NoRet-Ext > Ret-
Ext: one-tailed Welch’s t22.16=1.75, p<0.05; Figure 2.6 C) as well as sipper contact during trial phase CS3 (test–baseline for NoRet-Ext > Ret-Ext: one-tailed Student’s t25=2.70, p<0.01; Figure 2.6 D) and trial phase CS4 (test–baseline for NoRet-Ext > Ret-Ext: one- tailed Welch’s t21.05=1.85, p<0.05; Figure 2.6 E). We also considered spontaneous recovery relative to an alternative end of extinction baseline that better captures the temporal context of cue presentation at test (E14 trial 1). Neither group exhibited spontaneous recovery of trial phase CS1 sipper site approach (Figure 2.6 G). However, defined relative to this alternative baseline, spontaneous recovery was likewise reduced in group Ret-Ext relative to NoRet-Ext for sipper site approach during trial phase CS2 (test–baseline for NoRet-Ext > Ret-Ext: one- tailed Student’s t25=2.41, p<0.015; Figure 2.6 H) as well as sipper contact during trial phase
CS3 (test–baseline for NoRet-Ext > Ret-Ext: one-tailed Welch’s t19.18=1.77, p<0.05; Figure 2.6 I). Both groups exhibited recovery of sipper contact during trial phase CS4 (Figure 2.6 J), but NoRet-Ext rats made more contact than Ret-Ext rats at baseline (two-tailed Welch’s t14.66=2.58, p<0.025) and test (two-tailed Welch’s t20.81=2.13, p<0.025). Therefore, regardless of which baseline was used, our data indicate that cue memory retrieval plus extinction attenuated spontaneous recovery compared to extinction alone. To assess vulnerability to reinstatement following Ret-Ext and NoRet-Ext treatment, we first examined whether responding on RT trial 1 varied between groups relative to each subject’s baseline response level at the end of the long-term memory test (LTMT trial 4). Reinstatement was reduced in Ret-Ext-treated rats (n=13) relative to NoRet-Ext-treated rats (n=14) for sipper site approach during trial phase CS1 (test– 58 baseline for NoRet-Ext > Ret-Ext: one-tailed Student’s t25=1.74, p<0.05; Figure 2.7 B) and trial phase CS2 (test–baseline for NoRet-Ext > Ret-Ext: one-tailed Student’s t25=1.56, p=0.065; Figure 2.7 C) as well as sipper contact during trial phase CS3 (test–baseline for
NoRet-Ext > Ret-Ext: one-tailed Student’s t25=3.00, p<0.005; Figure 2.6 D), but not trial phase CS4 (Figure 2.7 E). The marginal significance for relative reduction in reinstatement of approach during trial phase CS2 was due to 1 NoRet-Ext rat having ceiling level approach at baseline. After excluding this rat, the protective effect of Ret-Ext during trial phase CS2 met the statistical significance threshold (test–baseline for NoRet-Ext > Ret-
Ext: one-tailed Student’s t24=3.01, p<0.005), in agreement with the significantly lower unadjusted level of approach during trial phase CS2 at test for group Ret-Ext than NoRet-
Ext (including the rat with the problematic baseline; two-tailed Student’s t25=2.45, p<0.02; Figure 2.7 C). We also considered reinstatement relative to the temporal context-sensitive end of extinction baseline (E14 trial 1). Defined against this alternative baseline, reinstatement of sipper site approach during trial phase CS1 was small and similar between groups (Figure
2.7 G). However, reinstatement was reduced in group Ret-Ext relative to NoRet-Ext for sipper site approach during trial phase CS2 (test–baseline for NoRet-Ext > Ret-Ext: one- tailed Student’s t25=2.44, p<0.02; Figure 2.7 H) as well as sipper contact during trial phase
CS3 (test–baseline for NoRet-Ext > Ret-Ext: one-tailed Student’s t25=1.98, p<0.05; Figure 2.7 I). Reinstatement of trial phase CS4 sipper contact appeared to be greater in Ret-Ext rats, but this was due to significantly lower baseline sipper contact, as reported earlier (two- tailed Welch’s t14.66=2.58, p<0.025; Figure 2.7 J). Therefore, regardless of the baseline used, our data indicate that memory retrieval plus extinction attenuated reinstatement compared to extinction alone.
59 2.5 DISCUSSION
Conditioned responses to alcohol-associated cues that are extinguished with standard exposure therapy readily re-emerge with the passage of time and re-exposure to non-extinguished cues. These post-treatment effects exist because the standard exposure therapy facilitates the formation of new response-inhibiting memories that must compete with existing excitatory memories for control over behavior. In the present study we were able to attenuate the return of conditioned responses to alcohol-associated cues by conducting extinction during the post-retrieval, memory reconsolidation window, an alternative approach to standard exposure therapy that may allow inhibitory learning to be incorporated into existing alcohol cue memories. Enduring reactivity to alcohol cues in humans with AUD likely arises from the interaction of conditioning- and alcohol-induced changes in the brain that accumulate across an individual’s drinking history. During the cue conditioning phase of our experiment, each trial modeled the stimulus sequence of taking a drink: olfactory and orosensory properties of alcohol preceded by specific visual stimuli. Each conditioning session (block of 8 trials) modeled the repetition of that stimulus sequence over the course of a drinking episode and as a consequence, the onset of alcohol’s psychopharmacological properties, which requires alcohol to reach the brain. As such, our study only included rats that by at least the end of the conditioning phase were reliably ingesting alcohol at doses that we have previously shown to result in detectable blood alcohol concentrations (BAC) (mean±sem BAC at the end of a conditioning session was 22±7 mg/dL for mean±sem ingested dose of 0.58±0.07 g/kg, n=12) (Cofresí et al., 2015). The BACs achievable in our paradigm are within a range easily achieved by humans during drinking episodes (10-60 mg/dL or 2-13 mM) (Thombs et al., 2003; Hustad & Carey, 2005; Clapp et al., 2008; Dougherty et al., 2012; Clapp et al., 2009). Since humans do not drink alcohol to meet 60 caloric or hydration needs, we neither food nor water restricted our rats—an overlooked confound in many oral self-administration paradigms. Finally, in order to attribute any conditioning effects specifically to alcohol, drinking solutions were never sweetened. We believe these choices maximize the relevance of our preclinical intervention study in rats to AUD treatment in humans. Using only those rats with conditioned reactions to alcohol-associated cues that were ultimately reinforced by alcohol’s actions on the brain, we created pseudo- randomized groups matched for drinking history (Figure 3.2 and Figure 3.3 F), which led to matching on conditioned reactivity (Figure 3.3 A-E). We then proceeded to evaluate long-term memory for extinction and susceptibility to alcohol odor-induced reinstatement following either standard- or memory retrieval-based CET. We termed the latter therapy “retrieval-extinction” treatment because it involved isolated cue presentation (memory retrieval) 1 hr before massed cue exposure all in the absence of alcohol. Rats in the standard therapy model, which we termed “no retrieval-extinction,” were not presented with an isolated cue, but were exposed to the conditioning chamber as well as session start and end signals that were yoked to the retrieval-extinction group 1 hr before massed cue exposure. Similarly, the last cue presentation during massed exposure was omitted for rats undergoing retrieval-extinction, but their session did not end until the control group’s session was finished. Thus, the total amount of cue and context exposure was matched between treatments within and across the 14 consecutive treatment days. We expected that the two treatments would similarly extinguish conditioned reactions to alcohol-associated cues (houselight illumination-elicited sipper hole approach and sipper presentation-elicited sipper contact) and thus produce similar long-term memory for extinction conditions. We hypothesized that retrieval-extinction treatment would reduce susceptibility to alcohol odor-induced reinstatement, relative to control treatment. 61 As expected, conditioned reactions to houselight and sipper presentation were similarly extinguished by the two treatments (Figure 3.4 and 3.5); however, when challenged with a 48 hr break in treatment, control rats exhibited spontaneous recovery of sipper site approach and sipper contact responses, whereas rats treated with retrieval- extinction did not (Figure 3.6). Thus, despite equivalently efficacious extinction of responding, treatments did not produce similar long-term behavioral memory: retrieval- extinction promoted better retention of response suppression. When challenged with alcohol odor, controls rats demonstrated robust reinstatement of sipper site approach and sipper contact responses. Rats treated with retrieval-extinction showed less reinstatement than controls (Figure 3.7), supporting our hypothesis. Furthermore, this effect was not restricted to the houselight-elicited anticipatory approach response, but rather extended to the sipper-elicited contact response. Thus, retrieval-extinction protected against reinstatement of the entire response sequence that was reinforced by alcohol ingestion during conditioning. It has previously been shown that alcohol cue memories can undergo retrieval- induced reconsolidation in rats and that post-retrieval pharmacological interference can disrupt alcohol seeking (Barak et al., 2013; von der Goltz et al., 2009; Milton et al., 2012; Schramm et al., 2016). Our study provides the first demonstration that memory retrieval + extinction, a form of behavioral interference, can also disrupt alcohol seeking. We were not, however, the first to test this possibility. A study by Millan and colleagues (2013) suggested that while in some cases, memory retrieval + extinction protects against relapse to alcohol seeking, in other cases it is ineffective or exacerbates relapse risk. In that study, however, the procedure used to reactivate memory may not have induced reconsolidation. Specifically, instrumental responding during the retrieval episode was not reinforced with alcohol (i.e., it did not deliver drinking solution into the magazine) but continued to result 62 in presentation of a discrete cue that had been paired with the drinking solution during prior operant self-administration sessions. Non-reinforcement is insufficient to trigger the reconsolidation of appetitive instrumental memories (Hernandez & Kelly, 2004; Exton- McGuinness et al., 2014) and in fact, response-contingent cue presentations in the absence of primary reinforcement can promote the formation of new inhibitory memory (Flavell & Lee, 2013). Thus, the retrieval procedure used by Millan and colleagues would not be expected to trigger reconsolidation of existing excitatory memories, but instead would be expected to initiate the consolidation of a new inhibitory memory. In this light, data from
Millan and colleagues suggest that additional inhibitory learning during the consolidation of a new inhibitory memory has disparate effects on response return. Furthermore, in the study by Millan and colleagues the motivation for alcoholic beverage seeking and drinking was critically confounded by motivation for sweet taste (malt sugars were present in the drinking solution), motivation for calories (rats were food-deprived till 1hr post-session), and motivation for water (rats were water-deprived till 1hr post-session). In contrast, rats in our study sought and drank unsweetened alcohol while neither food nor water deprived.
These important parametric differences must be accounted for when comparing the present data with previously published results. The memory reactivation procedure used in the present study was specifically designed to induce reconsolidation of the alcohol cue memory. To retrieve the memory, we presented the alcohol-predictive cue in an isolated trial. To trigger reconsolidation, we omitted the alcohol, which produces a negative prediction error (viz., we violated cue- based expectancy of subsequent alcohol access and ingestion). Negative prediction error is required for cue memory retrieval to induce a reconsolidation process (Pedreira et al., 2004; Piñeyro et al., 2013; Das et al., 2015). However, at some point during treatment, the isolated cue likely stopped producing prediction error, precluding reconsolidation-based updating 63 of the original memory, so we cannot rule out some contribution of new response-inhibiting memory to reduced response return following our retrieval-extinction treatment. Future studies should explore the parameters for memory reactivation to discover those that can be exploited to maximize reconsolidation-based updating of the original memory. For example, to the extent that rats learn to expect multiple presentations of the conditioned stimulus sequence—sight, smell, taste, and alcohol ingestion (non-intoxicating dose)—per day, a single stimulus sequence presentation may be enough to generate prediction error while maximally reactivating the cue memory. An internal drug stimulus- based memory reactivation procedure has also shown promise in rat models of relapse to cocaine seeking (Luo et al., 2015). Exposure to alcohol’s internal stimulus in the absence of antecedent stimuli (sight, smell, taste, and ingestion of the alcoholic beverage) naturally conditioned via routine oral self-administration may thus also be a promising strategy for reactivating alcohol-associated memories. Our present findings suggest that there is promise in conducting CET during reconsolidation of memory for alcohol-associated cues. Additional experiments are needed to replicate and extend these findings (e.g., in rat strains selected for high alcohol drinking or preference), to determine boundary conditions (e.g., aged memories, extensively trained associations, physical dependence), and to discover any potential risks. Whether post- retrieval CET will attenuate or exacerbate other forms of response return needs to be explored (e.g., stress or alcohol prime-induced reinstatement). It would be especially important to determine if post-retrieval CET can affect, and ideally reduce rapid reacquisition of conditioned responding using our procedure. Although the memory retrieval + extinction procedure in Millan et al. (2013) facilitated response reacquisition, the generalizability of this finding is unclear given the caveats discussed above.
64 In conclusion, we found that retrieval-extinction can attenuate the return of alcohol cue reactivity relative to standard extinction in rats. The relevance of our finding to AUD treatment is highlighted by two other recent findings. First, retrieval-extinction has been successfully applied to persistently attenuate cue-induced craving for heroin in individuals with heroin use disorder (Xue et al., 2012). Second, it was recently demonstrated that memory retrieval with prediction error can trigger the reconsolidation of naturally acquired alcohol cue memories in hazardous heavy drinkers (Das et al., 2015). Considered alongside these results, our study suggests that a treatment approach that incorporates post-retrieval
CET in individuals with AUD may help to persistently attenuate reactivity to alcohol- associated cues, thereby reducing the long-term risk that these cues pose in daily life.
65 2.6 FIGURES
Figure 2.1. Retrieval + extinction experiment timelines.
Panel A: Singly housed, adult male Long-Evans rats were induced to drink unsweetened alcohol in the homecage using an intermittent 24hr access schedule: alcohol available on MWF for 5 weeks. Water and standard chow were always available (ad libitum). Panel B: Following habituation to conditioning chamber and stimuli, rats had 12 consecutive days of cue conditioning followed by 14 consecutive days of cue extinction treatment. A test of long-term memory (LTMT) for extinction was conducted 48hr after the last day of extinction. A test of reinstatement (RT) was conducted 48hr after LTMT. Panel C: Cue conditioning sessions consisted of 8-trial blocks. Panel D: Cue extinction treatment days involved 12 extinction trials in either “no retrieval-extinction” or “retrieval-extinction” arrangement. Panel E: LTMT and RT consisted of 4-trial blocks. Panels C-E: The same variable inter-trial interval (vITI) was used (mean=280s; sd=68s; min=160s; max=360s). Panel F: Conditioning trials involved 20s chamber houselight illumination with co- terminating 10s access to alcohol (10% or 15% ethanol v/v in tap water; 10E/15E) sipper starting 10s after light onset. Panel G: Extinction trials for both Extinction and LTMT consisted of 20-s chamber houselight illumination with co-terminating 10s access to dry sipper starting 10s after light onset. Panel H: For RT, extinction trials were given, but an open vial of 10E/15E (20mL) was hidden in the cubicle housing the conditioning chamber.
66 Figure 2 5 Ret-Ext (n=13) NoRet-Ext (n=14) 4
3
2
1
0 Ethanol Ingested (g/kg) 1 3 5 7 9 11 13 15 Homecage Session
Figure 2.2. Matched free-choice ethanol drinking history.
Group mean ± SEM shown for ingested doses per day during the homecage phase. Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13).
Horizontal line indicates a priori study inclusion criterion: mean across last 3 days >=1.00 g/kg.
67 Figure 3
h Trial Phase preCS Trial Phase CS1 Trial Phase CS2 c 3 a ABC o
r Ret-Ext (n=13)
p NoRet-Ext (n=14)
p 2 A e t i 1 S r e p p
i 0
S 135791113579111357911 Conditioning Session
Trial Phase CS3 Trial Phase CS4 ) g 0.6 k
4 /
DE g F t ( c d a
t 3 e 0.4 t n s o e g C 2 r n e
I 0.2 l p o p 1 i n S a h 0 t 0.0 13579111357911 E 1357911 Conditioning Session
Figure 2.3. Matched cue-conditioned appetitive response acquisition.
Panels A-C: Group mean ± SEM shown for sipper site approach level (max level = 4). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels D-E: Group mean ± SEM shown for sipper contact level (max level = 4). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panel F: Group mean ± SEM shown for ingested doses per session. Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Horizontal line indicates a priori study inclusion criterion: mean across last 3 sessions >= 0.30 g/kg.
68 Figure 4 Trial Phase preCS Trial Phase CS1 Trial Phase CS2 2.0 ABC Ret-Ext (n=13) 1.5 NoRet-Ext (n=14)
1.0
0.5
Sipper Site Approach Sipper Site 0.0 1 3 5 7 9 11 13 1 3 5 7 9 1113 1 3 5 7 9 1113 Extinction Day Trial Phase CS3 Trial Phase CS4 2.0 End of Extinction DE Approach Contact 1.0 1.5 FG Ret-Ext (n=13) .75 NoRet-Ext (n=14) 1.0 .50
0.5 .25 SipperContact ResponseLevel 0.0 0.0 pre 1234 1 3 5 7 9 11 13 1 3 5 7 9 11 13 CS Trial Phase Extinction Day
Figure 2.4. Equivalent cue-conditioned appetitive response extinction.
Isolated cue plus context or context only exposure 1 hr before massed cue exposure similarly extinguished cue-conditioned responses across treatment. Panels A-C: Group mean ± SEM shown for sipper site approach level (max level = 4). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels D-E: Group mean ± SEM shown for sipper contact level (max level = 4). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels F-G: Group mean ± SEM shown for sipper site approach and sipper contact levels (max level = 4) across the last 4 trials on the last day of treatment. Open bars represent group NoRet-Ext (n=14). Filled bars represent group Ret-Ext (n=13).
69 Figure 5
Trial Phase preCS Trial Phase CS1 Trial Phase CS2 Trial Phase CS3 Trial Phase CS4 h t c 4 4 c a AB C DE a o
r Ret-Ext (n=13) t
p 3 3
NoRet-Ext (n=14) n p o
A 2 2 e C t i r e S
r 1 1 p e p p i p i
0 S 0
S 135791113 1357911131 3 5791113 1357911131 3 5791113 Extinction Day Extinction Day
Figure 2.5. Similar daily recovery of cue-conditioned appetitive responses.
Panels A-C: Group mean ± SEM shown for sipper site approach level (max level = 4) on trial 1 across extinction days (retrieval trial for Ret-Ext group). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels D-E: Group mean ± SEM shown for sipper contact level (max level = 4) on trial 1 across extinction days (trial 1 = retrieval trial for Ret-Ext group). Open circles represent group NoRet-Ext (n=14). Filled circles represent group Ret-Ext (n=13).
70
Figure 6 Spontaneous Recovery Relative to E14 Trial 9-12 h Trial Phase preCS Trial Phase CS1 Trial Phase CS2 Trial Phase CS3 Trial Phase CS4 c a 2.5 t 2.5 o c r ABCa D E t p 2.0 2.0 n p Ret-Ext (n=13) 1.5 o 1.5 A
e NoRet-Ext (n=14) C t r i 1.0 1.0 e S p r 0.5 0.5 p
i ** e p 0.0 * S 0.0 p i Baseline Test Baseline Test Baseline Test Baseline Test Baseline Test S Spontaneous Recovery Relative to E14 Trial 1
h Trial Phase preCS Trial Phase CS1 Trial Phase CS2 Trial Phase CS3 Trial Phase CS4 c a 2.5 t 2.5 o c r
FGHa I J t p 2.0 Ret-Ext (n=13) 2.0 n p
1.5 o 1.5 A NoRet-Ext (n=14) e C t r i 1.0 1.0 e S p r 0.5 0.5
* p i e * p 0.0 S 0.0 p i Baseline Test Baseline Test Baseline Test Baseline Test Baseline Test S
Figure 2.6. Retrieval-extinction treatment protects against early spontaneous recovery of cue-conditioned appetitive responses relative to two different baselines.
Group mean ± SEM shown for sipper site approach and sipper contact levels (max level = 4) (Panels A, B, C, F, G, H and D, E, I, J respectively). Open circles represent group NoRet- Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels A-E: Baseline refers to average across E14 trials 9-12. Panels F-J: Baseline refers to E14 trial 1 (retrieval trial for Ret-Ext group). All Panels: Test refers to long-term memory test trial 1. Asterisk (*) signifies one-tailed p<0.05 for directional comparison on response level change (test– baseline for NoRet-Ext > Ret-Ext). 71 Figure 7 Alcohol Odor-Induced Reinstatement Relative to LTMT Trial 4
h Trial Phase preCS Trial Phase CS1 Trial Phase CS2 Trial Phase CS3 Trial Phase CS4 c a t o 3 c 3 r
ABCa D E t p n p Ret-Ext (n=13) 2 o 2 A NoRet-Ext (n=14) e C t r i 1 # e 1 S p r
p * i e p 0 S 0 p
i * Baseline Test Baseline Test Baseline Test Baseline Test Baseline Test S Alcohol Odor-Induced Reinstatement Relative to E14 Trial 1
h Trial Phase preCS Trial Phase CS1 Trial Phase CS2 Trial Phase CS3 Trial Phase CS4 c a t o 3 c 3 r FGHa I J t p n p Ret-Ext (n=13)
2 o 2 A NoRet-Ext (n=14) e C t r i 1 e 1 S p r p i e * * p 0 S 0 p i Baseline Test Baseline Test Baseline Test Baseline Test Baseline Test S
Figure 2.7. Retrieval-extinction treatment protects against alcohol odor-induced reinstatement of cue-conditioned appetitive responses relative to two different baselines.
Group mean ± SEM shown for sipper site approach and sipper contact levels (max level = 4) (Panels A, B, C, F, G, H and D, E, I, J respectively). Open circles represent group NoRet- Ext (n=14). Filled circles represent group Ret-Ext (n=13). Panels A-E: Baseline refers to long-term memory test trial 4. Panels F-J: Baseline refers to E14 trial 1 (retrieval trial for Ret-Ext group). All Panels: Test refers to reinstatement test trial 1. Asterisk (*) and pound sign (#) signify one-tailed p<0.05 and p<0.07, respectively, for directional comparison on response level change (test–baseline for NoRet-Ext > Ret-Ext). 72 Chapter 3. Characterizing conditioned reactivity to sequential alcohol- predictive cues in well-trained rats2
3.1 ABSTRACT
Implicit learning about antecedent stimuli and the unconditional stimulus (US) properties of alcohol may facilitate the progressive loss of control over drinking. To model this learning, in Chapter 2, we developed a procedure in which a discrete, visual conditional stimulus (houselight illumination; CS) predicted the availability of a retractable sipper that rats could lick to receive unsweetened alcohol. Here we investigated the possibility that houselight illumination, sipper presentation, and oral alcohol receipt might each exert control over alcohol seeking and drinking. We also determined the relationship between ingested dose and blood alcohol concentration, in order to validate the idea that the US is a post-ingestive action of alcohol. Finally, we tested a major prediction from the conditioning account of problematic drinking [Tomie, A., & Sharma, N. (2013). Current Drug Abuse Reviews, 6, 201–219], which is that once learned, responses elicited by a CS will promote drinking. We found that despite having constrained opportunities to drink alcohol during the conditioning procedure, ingested doses produced discriminable blood concentrations that supported cue conditioning. Based on our analysis of the dynamics of cue reactivity in well-trained rats, we found that houselight illumination triggered conditioned approach, sipper presentation evoked licking behavior, and alcohol receipt promoted drinking. Reactivity to these cues, which varied in terms of their temporal proximity to the alcohol US, persisted despite progressive intoxication or satiety. Additionally, rats with the greatest conditioned reactivity to the most distal alcohol cue
2 This work was previously published: Cofresí, R. U., Lee, H. J., Monfils, M.-H., Chaudhri, N., & Gonzales, R. A. (2018). Characterizing conditioned reactivity to sequential alcohol-predictive cues in well- trained rats. Alcohol, 69, 41–49. http://doi.org/10.1016/j.alcohol.2017.11.034 Dissertator contributed to the conception, design, data collection, analysis, interpretation, and writing of the study. 73 were also the fastest to initiate drinking and drank the most. Our findings indicate that the post-ingestive effects of alcohol may condition multiple cues simultaneously in adult rats, and these multiple cues help to trigger alcohol seeking and drinking. Moreover, identification and characterization of these cues should be helpful for designing interventions that attenuate the power of these cues over behavior.
3.2 INTRODUCTION
Problematic drinking may result from implicit learning about conditional stimuli and the unconditional stimulus (US) properties of alcohol. The more well-defined the set of conditional stimuli for the alcohol US, the greater the ability of these stimuli to elicit conditioned responses that can promote drinking (Tomie & Sharma, 2013). In support of this theory, the stimulus features of an individual’s preferred alcoholic beverage (sight, smell, taste, glassware) have been shown to elicit changes in attention (Das, Lawn, & Kamboj, 2015; Field, Mogg, & Bradley, 2005; Field, Mogg, Zetteler, & Bradley, 2004; Townshend & Duka, 2001), craving (Fox, Bergquist, Hong, & Sinha, 2007; Kaplan et al., 1985; Li et al., 2015; McCusker & Brown, 1990; Monti et al., 1987; Pomerleau, Fertig, Baker, & Cooney, 1983; Witteman et al., 2015), body temperature (Newlin, 1985, 1986), heart rate (Glautier, Drummond, & Remington, 1992; Kaplan et al., 1985; Payne et al., 1992; Sinha et al., 2009; Staiger & White, 1991; Stormark, Laberg, Bjerland, Nordby, & Hugdahl, 1995), salivation (Monti et al., 1987; Pomerleau et al., 1983), and skin conductance (Glautier et al., 1992; Kaplan et al., 1985; Laberg, Hugdahl, Stormark, Nordby, & Aas, 1992). In order to model this implicit learning, we developed a task in which a discrete, visual conditional stimulus (CS; houselight illumination) predicted the availability of a retractable sipper that rats could lick to receive unsweetened alcohol (Chapter 2). Our
74 experimental set-up differs considerably from appetitive Pavlovian conditioning procedures in which i) a CS predicts the delivery of a fixed quantity (e.g., grain or sucrose pellets) or volume (e.g., liquid sucrose or alcohol) of an appetitive US that is delivered into an omnipresent magazine (e.g., food cup, fluid port), and ii) subjects are free to ingest the appetitive US at any point during the session. In our task, the CS predicts time-limited access to the magazine (sipper). Consequently, receipt of the alcohol solution is contingent upon timely interaction with the sipper, and the amount of alcohol ingested in each conditioning trial depends on this consummatory behavior. This task effectively separates
‘appetitive’ alcohol-seeking conditioned responses that are triggered by the CS – conditioned approach and orientation toward the sipper – from ‘consummatory’ licking responses. Conceptually, each conditioning trial models the stimulus sequence that is inherent in consuming a sip of alcohol, where individuals are exposed to the sight and smell of alcohol before making contact with the drinking receptacle. Blocks of conditioning trials (sessions) model the repetition of that stimulus sequence across a drinking episode, which precedes the slow-onset pharmacological effects of ingested alcohol.
Despite extensive extinction training in which the CS is presented without alcohol, the alcohol seeking and drinking sequence that is conditioned using our procedure exhibits spontaneous recovery and reinstatement (Chapter 2). We were able to significantly reduce this relapse-like return of responding by conducting daily extinction training after an isolated CS trial (Chapter 2), which is believed to trigger memory-updating processes that persistently alter the original CS-alcohol association (Auber, Tedesco, Jones, Monfils, & Chiamulera, 2013; Monfils, Cowansage, Klann, & LeDoux, 2009). However, we were unable to prevent response return altogether, suggesting that some alcohol cue memories remained intact. This outcome led us to consider the possibility that other stimuli in our behavioral paradigm may have also become conditioned to the pharmacological effects of 75 ingested alcohol. In our task, houselight onset is followed 10 sec later by insertion of the sipper into the conditioning chamber. Rats have access to the sipper for 10 sec, after which it is retracted and the houselight turned off. Sipper presentation is accompanied by an auditory stimulus that is generated by the sipper/bottle motor assembly, creating a compound visual and auditory stimulus that signals alcohol availability and could serve as a predictor of alcohol’s post-ingestive effects. Finally, licking the sipper provides access to the taste and smell of alcohol. These orosensory stimuli are likely to also act as predictors of the pharmacological consequences of alcohol ingestion.
The present study characterized appetitive and consummatory behavior in relation to potential cues in our oral alcohol-conditioning task. Specifically, in well-trained rats we examined the dynamics of i) conditioned alcohol-directed approach elicited by the houselight, ii) sipper contact elicited by sipper presentation, and iii) within-trial lick rate, which would have been influenced by the smell and/or taste of alcohol. Additionally, we were interested in determining the relationship between ingested dose and blood alcohol concentration in our task – something that is infrequently done in appetitive Pavlovian conditioning procedures with alcohol. Determining that alcohol is detectable in blood supports the idea that the US in our conditioning task is alcohol’s post-ingestive pharmacology. In relation to this idea, we were also interested in testing a major prediction from the conditioning account of problematic drinking (Tomie & Sharma, 2013), which is that once learned, responses elicited by a CS will promote drinking.
3.3 METHODS AND MATERIALS
3.3.1 Subjects
Subjects were adult, male Long-Evans rats (Envigo; Indianapolis, Indiana) weighing 250–275 g upon arrival. All were singly housed in a temperature and humidity 76 controlled room (22 ± 2 °; 12-h light cycle). Access to chow and tap water were unrestricted in the homecage, which contained Sani-Chips® bedding and a Bio-Serv Gummy Bone (polyurethane; 5 cm L × 2.5 cm W). All procedures took place during the light phase of the light/dark cycle. The colony room was adjacent to the procedure rooms. Ethanol (v/v) solutions were prepared every 3 days from 95% ethyl alcohol (ACS/USP grade, Pharmco-AAPER, Brookfield, CT, USA) and tap water. Solutions were kept and served at room temperature (20 ºC). All procedures were approved by the Institutional Animal Care and Use Committee at the University of Texas at Austin, and conducted in accordance with NIH guidelines.
3.3.2 Apparatus
Conditioning took place in Med Associates, Inc. (Fairfax, Vermont) chambers housed within sound-attenuating cubicles that were equipped with digital video cameras and exhaust fans. The houselight and retractable bottle assembly were installed on the same chamber wall. For a detailed description, see Chapter 2.
3.3.3 Behavioral methods
3.3.3.1 Drinking unsweetened ethanol in the homecage
A week after arrival, rats received 5 weeks of intermittent access to ethanol using a two-bottle choice procedure. This phase was conducted in order to acclimate rats to the taste and pharmacological effects of alcohol. Briefly, rats had 24-h access to unsweetened ethanol solution (15% ethanol in tap water; v/v; 15E) or tap water starting 4–6 h into the light phase on Monday, Wednesday, and Friday. On all other days, two water bottles were available. Ethanol and water bottle placement on the cage was alternated across sessions. Gravity-fed, metal sipper tubes were used. Rats that failed to drink ≥0.5 g/kg in week 1
77 were offered 5% ethanol v/v in tap water (5E) in week 2 and then 10% ethanol v/v in tap water (10E) over weeks 3–5 (for details, see Chapter 2). Rats drinking less than 1 g/kg/session on average across week 5 were not retained for conditioning.
3.3.3.2 Cue conditioning with unsweetened ethanol
Rats received 12 sessions of cue conditioning. Briefly, sessions occurred across consecutive days and consisted of eight conditioning trials on a variable intertrial interval (ITI) with mean 280 sec, minimum 160 sec, and maximum 360 sec. Upon initiating the Med-PC program, there was a 5-min delay period to allow rats to acclimate to the conditioning chambers, after which the exhaust fans were activated to signal session onset and the first ITI was selected. The final (9th) ITI was selected after trial 8, and the exhaust fan was turned off at the end of this ITI to signal the end of the session. In each conditioning trial, the houselight was illuminated for 20 sec and the bottle assembly activated such that a metal sipper was inserted into the chamber 10 sec after houselight onset and retracted upon houselight offset. The bottle assembly immediately produced a noise when it was activated and took up to 0.5 sec to complete each operation (movement of the sipper tip toward or away from the plane of the wall). The sipper was attached to a bottle filled with either 10E or 15E, depending on which solution the rat was drinking at the end of the homecage drinking phase, and contained a ball bearing to prevent spillage upon insertion and retraction. Rats were given a single habituation session the day before the first conditioning session, during which the houselight and bottle assembly motor were activated on the same schedule described above, but neither sipper nor drinking solution were presented. The day immediately after conditioning session 12, rats were given 12 trials with a dry sipper. Ambient ethanol odor was absent. The variable ITI was the same as described above except ~60 min elapsed between test trials 1 and 2 for seven rats who
78 were in the retrieval + extinction condition (Chapter 2). There were no notable differences in trial-by-trial behavior between those seven and the remaining 23 rats. Only test trials 1– 8 were considered here for ease of comparison to trial-by-trial data from conditioning session 12.
3.3.3.3 Blood ethanol concentration following cue conditioning
Blood sampling took place after rats had been re-conditioned, such that their response and ingested dose levels were stable within 15% of levels across conditioning sessions 10–12. On blood sampling day, as on any day, rats had unlimited access to chow and water in the homecage until they were transferred into conditioning chambers for a conditioning session. Rats were removed from the chamber immediately after the 8th sipper presentation and anesthetized with isoflurane gas. Blood was then collected from either the saphenous vein or the trunk after decapitation.
3.3.3.4 Behavioral measurements
Rats were weighed before every homecage drinking or cue-conditioning session. During the homecage phase, solution intake was measured as the difference in bottle mass pre- and post-session to the nearest 0.1 g. Intake was corrected for loss due to evaporation and/or leakage by subtracting the “intake” of an empty cage subjected to identical procedures. Grams of pure ethanol ingested were calculated using corrected ethanol solution intake. During the cue-conditioning phase, intake was measured as the difference in bottle mass pre- and post-session to the nearest 0.01 g. Intake was corrected by subtracting the mass of solution leaked from the sipper in its retracted state. Leaked solution was collected by a weighboat outside the chamber and measured as the difference
79 in weighboat mass pre- and post-session. Grams of pure ethanol ingested were calculated using corrected intake. During the cue-conditioning phase, we also measured appetitive and consummatory behaviors. Cue-conditioning trials were sampled from digital video recordings by making instantaneous observations every 1.25 sec, starting 5 sec before houselight onset as in Chapter 2. At each observation, the mutually exclusive rating options were “sipper site approach” (approaching, attending to, or exploring the sipper insertion hole, including sniffing, gnawing, and clawing at the hole) or “other” (e.g., grooming, rearing, resting).
Highly trained judges made these observations, with ≥95% agreement on joint ratings. Judges were blind to session/treatment parameters. For every conditioning trial in every session, “approach” behavior state ratings within each trial phase (5-sec bin before houselight illumination: pre-CS; consecutive 5-sec bins during illumination: CS1, CS2) were counted for every rat. Only four observations were made per trial phase, so the maximum sipper site approach frequency per trial phase on any trial of any session was 4. Consummatory sipper licking was recorded using a contact lickometer. The latency to initiate sipper licking was computed as the time to first lick following activation of the retractable bottle assembly. If no lick was registered during a trial, a maximum latency (10 sec) was assigned.
3.3.3.5 Blood ethanol analysis
Ethanol concentration (mg/dL) in blood samples (10 µL mixed with 90 µL saturated saline; three replicates per rat) was determined using gas chromatography as in Carrillo et al. (2008).
80 3.3.4 Statistical analysis
Behavior patterns were characterized using within-subjects analysis of variance (ANOVA) and 2-tailed paired t tests. Relationships between behaviors were explored using simple linear regression. Bonferroni correction was applied as appropriate. The threshold for statistical significance was p < 0.05. Analyses were conducted in R version 3.3.2 (R Core Team, 2016) using the car package (Fox & Weisberg, 2011).
3.4 RESULTS
In total, 44 rats were obtained for the study, 37 of which were retained for conditioning based on ethanol intake in the homecage (≥1.00 g/kg per day on average across the last three sessions). To characterize cue reactivity after task acquisition, we analyzed data from 30 rats that met a priori minimum ingested dose criteria across experiment phases (homecage: 1.00 g/kg per day on average across the last three sessions; conditioning: 0.30 g/kg per session across the last three sessions). Acquisition data are presented in Supplemental Information (see 3.6 below).
3.4.1 Post-acquisition dynamics in reactivity to houselight illumination
We analyzed sipper site approach elicited by houselight illumination during the pre- CS, CS1, and CS2 trial phases of each trial in conditioning session 12 and the dry sipper test session (Figure 3.1 A–B) for all 30 rats to characterize conditioned reactivity to this visual CS, which is most distal to the post-ingestive effects of ethanol, in well-trained subjects. Within-subjects ANOVA detected a significant 3-way interaction of trial phase, trial, and session on sipper site approach (F14,406 = 15.21, p < 0.001; Fig. 1C). Follow-up
ANOVA detected a significant trial phase × trial interaction in both sessions (F14,406=14.54, p < 0.001). In both sessions, the frequency of sipper site approach that occurred before houselight onset (pre-CS) did not vary significantly from floor across trials, but the 81 frequency of sipper site approach that occurred during houselight illumination (CS1 and
CS2) decreased significantly across trials (simple effects of trial: F7,203 ≥ 6.11, p < 0.001). In both sessions, approach level during CS1 and CS2 was greater in trials 1–4 than in trials
5–8 (t29 ≥ 4.11, p < 0.001). In both sessions, there was a consistent pattern of approach within trials (simple effects of trial phase: F2,58 ≥ 6.39, p < 0.004), such that the frequency of sipper site approach was greater during CS1 than pre-CS, and greater during CS2 than CS1. In the conditioning session, pairwise comparisons of trial phases within trials were significant across trials 1–8 (t29 ≥ 2.27, p < 0.05). In the dry sipper session, pairwise comparisons of trial phases within trials were significant in trials 1–6 and 8 (t29 ≥ 2.41, p < 0.025), but not trial 7 (t29 = 1.88, NS). While statistically significant, it appears the 3-way interaction of trial phase, trial, and session was driven by a practically insignificant difference in within-trial pattern persistence across trials between sessions. Essentially, however, within-session houselight cue-elicited alcohol approach dynamics were identical when tested under reinforcement (oral ethanol receipt) and non-reinforcement (dry sipper, no ethanol odor). Thus, despite some decline in conditioned reactivity across trials in each test condition, every illumination of the houselight elicited sipper site approach, and the frequency of this conditioned response increased across the period of illumination prior to sipper presentation.
3.4.2 Post-acquisition dynamics in reactivity to sipper presentation
We analyzed the latency to start licking the sipper per trial in conditioning session 12 and the dry sipper test session for 25 of 30 rats (five were missing lick data due to equipment malfunction) to characterize reactivity to this compound auditory-visual stimulus, which in our task is more proximal to the ethanol US than houselight illumination, in well-trained subjects. Within-subjects ANOVA detected significant main
82 effects of trial (F7,168= 15.78, p < 0.001) and session (F1,24 =12.86, p < 0.002) on latency to lick (Figure 3.2), but no interaction (F < 1, NS). To confirm this equivalence further, we conducted ANOVA within each session. In both sessions, the latency to start licking increased across trials (simple main effects of trial: F7,168 = 10.86, p < 0.001). Additionally, in both sessions, on average, the latency to lick was lower (namely, rats were faster to start licking) in trials 1–4 than in trials 5–8 (t24 = 4.82, p < 0.001). The only difference between sessions was that latency was greater across dry sipper test trials 4–6 than conditioning trials 4–6. Overall, however, within-session dynamics of sipper presentation-elicited sipper contact were identical when tested under reinforcement (oral ethanol receipt) and non- reinforcement (dry sipper, no ethanol odor). Thus, despite some decline across trials in each test condition, presentation of the sipper tended to prompt initiation of consummatory licking within the 10-sec window of opportunity.
3.4.3 Post-acquisition dynamics in reactivity to oral ethanol receipt
The receipt of unsweetened ethanol solution is an orosensory stimulus and it is the antecedent stimulus that is most proximal to ethanol’s post-ingestive effects in our task. In order to characterize reactivity to this stimulus in well-trained subjects, we analyzed lick rate (licks per 2-sec bin within the 10-sec sipper presentation) in each trial in conditioning session 12 and the dry sipper test session for 25 of 30 rats (five were missing lick data due to equipment malfunction). Within-subjects ANOVA detected a significant 3-way interaction of bin, trial, and session on lick rate (F28,672 = 1.65, p < 0.02; Figure 3.3). Follow-up ANOVA detected a significant bin × trial interaction on lick rate in the conditioning session (F28,672 = 1.98, p < 0.0025), but not in the dry sipper test session
(F28,672 = 1.01, NS). In the conditioning session, the simple effect of bin was significant in every trial (F4,96 ≥ 5.21, p < 0.001). In every trial, initial receipt of oral ethanol triggered a
83 spike in lick rate (bin 1 vs. bin 2: t24 = 2.54, p < 0.02). The final lick rate in every trial was also always greater than the starting rate (bin 1 vs. bin 5: t24 = 3.59, p < 0.002). What varied between trials was whether lick rate was stable after its initial spike or increased with more oral ethanol receipt. In 6 of 8 trials, there was an increase in rate across or sometime between bin 2 and bin 5. In only four of eight trials was the final rate (bin 5) greater than rate after the spike due to initial oral ethanol receipt (bin 2 or bin 3). However, none of these latter comparisons was statistically significant after correction for multiple comparisons. The simple effect of trial was also significant in every bin (F7,168 ≥ 6.09, p < 0.001), reflecting the overall decline in lick rate across trials in the conditioning session. Overall, lick rates in the dry sipper test session were significantly lower than in the conditioning session (collapsing bins and trials, t24= 13.35, p < 0.001). In the dry sipper test session, there was a significant main effect of trial (F7,168 = 14.67, p < 0.001) driven by a drop in the average lick rate (across bins) per trial to near-floor by the second half of the dry sipper test session (trials 1–4 vs. trials 5–8: t24 = 8.54, p < 0.001). A statistically significant main effect of bin was also detected in the dry sipper test session (F4,96 = 3.1, p < 0.02). However, none of the pairwise comparisons between bins (collapsing across trials) was statistically significant after correcting for multiple comparisons. Thus, despite some decline across trials, initial receipt of oral ethanol solution tended to accelerate the rate of consummatory licking within every trial. The same within-trial pattern was not observed when the sipper failed to deliver fluid and ambient ethanol odor was absent.
3.4.4 Blood ethanol concentrations in the conditioning task
To determine whether ethanol ingested in the conditioning task produced detectable levels of ethanol in blood, we obtained blood samples from 24 rats (13 from saphenous vein, 11 from trunk). The time between the 1st and 8th sipper presentation in the session
84 was 34–37 min, due to the variable ITI. Blood sampling time ranged from 2.5 to 12.5 min after the 8th sipper presentation. Body weights ranged from 416 to 547 g. Blood ethanol concentration (BEC) was detectable in most rats at the end of the conditioning session, and was significantly related to ingested dose (Pearson’s r = +0.73, t22 = 5.01, p < 0.001; Figure 3.4). The mean ± S.E.M. ingested dose was 0.59 ± 0.04 g/kg. The mean ± S.E.M. BEC was 16 ± 3 mg/dL. BEC ranged from 0 to 57 mg/dL.
3.4.5 Conditioned reactivity to houselight illumination promotes ethanol drinking
We used simple linear regression to test the prediction that sipper site approach elicited by the houselight promotes ethanol intake during sipper exposure after task acquisition. Specifically, we modeled drinking-related measurements as a function of reactivity to houselight illumination as indexed by sipper site approach during trial phase CS2 per trial. Data were averaged across sessions 10–12 to get the best estimates of asymptotic individual behavior and dose levels. Data from all 30 rats were available for regression of dose on conditioned approach level, but data from only 25 rats were available for regressions of licks and lick latency on conditioned approach level (data were missing for five of 30 rats due to equipment malfunction). Conditioned reactivity to the houselight was related to the latency to start licking per trial, the number of licks per trial, and the total ingested dose. Greater reactivity to houselight illumination predicted shorter latency to start licking (t23 = −9.15, p < 0.001; Figure 3.5 A), greater number of licks (t23= 6.32, p < 0.001;
Figure 3.5 B), and larger ingested doses (t28 = 2.06, p < 0.05; Figure 3.5 C). Houselight cue reactivity levels accounted for 78% of the variance in licking latencies, 63% of the variance in licks, and 13% of the variance in ingested doses.
85 3.5 DISCUSSION
Here, we set out to: i) characterize reactivity to potential conditional stimuli for alcohol availability and/or alcohol’s pharmacological effects in our paradigm, ii) confirm that alcohol consumed during conditioning sessions was detectable in blood, and iii) test the prediction that conditioned responses elicited by an alcohol-predictive CS can promote drinking.
3.5.1 Cue conditioning with unsweetened alcohol in non-deprived rats
In the present study, non-deprived adult male rats learned to drink unsweetened alcohol from a sipper that was presented in a conditioning chamber, and learned to react to houselight illumination – an antecedent conditional stimulus (CS) for alcohol access – with approach to the site of alcohol access. It is likely that providing rats with intermittent access to unsweetened alcohol in the homecage prior to cue conditioning facilitated this learning (Figure 3.6–3.8). Acclimation to the taste and pharmacological effects of alcohol during this phase may have permitted subsequent conditioning with unsweetened alcohol as the appetitive US in a different context, without the need for fluid or food deprivation or sweetened alcohol solution (see also Carnicella, Ron, & Barak, 2014; Chaudhri, Sahuque, Schairer, & Janak, 2010; Remedios, Woods, Tardif, Janak, & Chaudhri, 2014).
3.5.2 Control of alcohol seeking and drinking by multiple alcohol-predictive cues
The primary objective of the present study was to characterize the behavioral reactions of well-trained subjects to distinct stimuli – houselight illumination, sipper presentation, and alcohol solution – that comprise conditioning trials in our paradigm. We found that houselight illumination (visual cue) elicited approach to the location of the sipper (Figure 3.1), and sipper presentation (multimodal cue) elicited consummatory licking (Figure 3.2). Moreover, the receipt of alcohol for oral consumption (orosensory 86 cue) elicited increases in lick rate across the sipper presentation period (Figure 3.3). Although the conditioned response sequence within trials remained stable, responding was greatest at the beginning of a session and decreased across trials within that session. This decline in overall reactivity across trials may have been due to the slow onset of alcohol’s sedative-like effects (Chuck, McLaughlin, Arizzi-LaFrance, Salamone, & Correa, 2006; Frye & Breese, 1981). Alternatively, it may have been due to decreases in the momentary motivational value of alcohol as a function of consumption (namely, satiety) (Samson, Czachowski, & Slawecki, 2000; Samson, Slawecki, Sharpe, & Chappell, 1998).
In our paradigm, the explicit stimulus that was designed to acquire a conditioned response was houselight illumination, but other stimuli present in the task may also have acquired conditioned responses, specifically, alcohol sipper presentation and oral alcohol receipt. Our results show that sipper presentation elicited the initiation of consummatory licking, even in the absence of oral alcohol and ambient alcohol odor. However, it should be noted that sipper presentation occurred in the context of houselight illumination. Thus, it is possible that licking initiation was controlled by the houselight, and not a reaction to sipper presentation. To distinguish between these alternatives, one future study with well- trained subjects could probe reactivity to the sipper without antecedent houselight illumination. Another future study might compare the behavior of subjects trained to drink alcohol under houselight illumination to that of others trained to drink in its absence. Another possibility is that houselight illumination and sipper presentation were learned as a compound cue. This can be tested by probing reactivity to the constituent elemental stimuli in isolation after training or extinction of the compound stimulus. A related, important consideration is that sipper presentation itself is a multimodal compound stimulus and such stimuli can engender stronger conditioned responses (Rescorla, 1973; See, Grimm, Kruzich, & Rustay, 1999; Weiss, 1964). 87 Our results also show a dramatic spike in lick rate following initial receipt of oral alcohol and a less robust spike in lick rate toward the end of drinking opportunities. No such patterns were observed when licking did not deliver oral alcohol. These findings not only confirm that oral alcohol receipt sustains consummatory licking after it is initiated, but also suggest that the initial receipt of oral alcohol may act as a cue capable of eliciting increases in drinking speed (consummatory vigor) within drinking occasions. To confirm this possibility, a future study could probe lick rate reactivity to receipt of an alternative liquid (e.g., water or quinine with and without ambient alcohol odor) after training with oral alcohol. Another future study could compare the lick rate of subjects conditioned with alcohol to that of subjects conditioned with different liquid reinforcers. A final caveat worth mentioning is that conditioned reactivity is multiply determined. Other factors known to influence the form and dynamics of reactivity beyond those already described include the nature of the US (Jenkins & Moore, 1973), the nature of the CS (Timberlake & Grant, 1975), and the interval between them (Esmorís-Arranz, Pardo-Vázquez, & Vázquez-García, 2003; Waddell, Morris, & Bouton, 2006). The present study was not designed to dissociate the role of specific factors. Despite all the caveats presented above, we believe our results support the idea that multiple, distinct alcohol- predictive cues influence alcohol seeking and drinking, at least in our model (and perhaps also in naturalistic drinking by humans). The primary motivation for the present study was to gain insight into whether and, if so, how different cues elicit behavioral reactivity in our model, because in prior work using this model, we observed that conducting retrieval + extinction, an arrangement of CS-no US trials that is believed to persistently update the original CS-US association formed during conditioning, attenuated but did not completely prevent the subsequent return of responding in spontaneous recovery and relapse tests (Chapter 2). Importantly, 88 the retrieval cue consisted of houselight illumination and dry sipper presentation. This procedure may have reactivated and updated only memories related to the houselight and sipper cues. Memory for cues more proximal to alcohol’s post-ingestive pharmacology (the putative US), such as the smell and taste of the alcohol drinking solution, may not have been reactivated. Thus, a retrieval + extinction procedure that included olfactory and orosensory alcohol cues may allow broader or more robust memory reactivation and updating.
3.5.3 Alcohol consumed during cue-conditioning sessions was pharmacologically active
Except for Tomie and colleagues (Tomie et al., 2006; Tomie, Lewis, Curiotto, & Pohorecky, 2007; Tomie, Uveges, Burger, Patterson-Buckendahl, & Pohorecky, 2004), preclinical researchers modeling the appetitive conditioning effects of human alcohol consumption in rodents do not typically verify that ingested alcohol can be detected in blood. If alcohol can be detected in the blood, then it is reaching the brain, and it can be argued that conditioned behavior in these rodent models stems from some action of alcohol on the brain, as we believe it does in humans. However, species differences and task parameters can make it so that little to no ingested alcohol reaches the brain. Thus, verifying blood alcohol is important for the relevance of findings from these rodent models to cue-triggered alcohol use in humans. Despite the limited number of drinking opportunities and the spacing of those opportunities in time in our task, alcohol was detectable in a large majority of subjects’ blood at the end of conditioning sessions. Although pre-session stomach content was not controlled, blood alcohol concentration (BAC) was still strongly related to total ingested dose (Figure 3.4). The 95% confidence interval around the BAC-dose regression line included zero until ~0.4 g/kg. This suggests
89 that our a priori minimum ingested dose criterion for “alcohol-reinforced conditioning” (average dose ≥0.30 g/kg across the last three conditioning sessions) may be too lenient. However, without mid-session blood samples, we cannot exclude the possibility that rats drinking between 0.30 and 0.40 g/kg had detectable BAC earlier in the session. Perhaps more importantly, we do not know how BAC changes over time within the conditioning session. Thus, we cannot say whether conditioning took place on the ascending or descending limb or both limbs of the BAC-time curve. Additionally, we do not know how phases of the BAC-time curve affect expression of CS reactivity at asymptote.
However, doses ingested by rats at asymptote in our paradigm were in a range (0.30–0.95 g/kg) that produces discriminable internal states, and the average ingested dose (~0.56 g/kg) would substitute for the internal state produced by the same dose injected intraperitoneally (Macenski & Shelton, 2001). Additionally, ingested doses were similar to those that maintain operant self-administration of unsweetened alcohol by rats (Czachowski, 2005; Czachowski, Chappell, & Samson, 2001). Furthermore, we know that BACs detected in our rats were within a range that is easily achieved by humans in naturalistic drinking situations (10–60 mg/dL or 2–13 mM) (Clapp, Min, Shillington, Reed, & Ketchie Croff, 2008; Clapp et al., 2009; Dougherty et al., 2012; Hustad & Carey, 2005; Thombs, Olds, & Snyder, 2003). These data support the contention that our paradigm allows us to study conditioning processes that are ultimately reinforced by alcohol’s post- ingestive pharmacology, specifically its central neuropharmacology. Although ingested alcohol doses that produce central effects also produce peripheral effects, the central effects of ingested alcohol appeared to be critical for conditioning effects of alcohol in our paradigm. We saw no evidence for cue conditioning in rats that consistently ingested enough alcohol for peripheral effects, but not enough alcohol for central effects (Figure 3.9). 90 3.5.4 Reactivity to an alcohol-predictive CS promotes alcohol intake
Based in part on prior studies showing that the US properties of alcohol can alter responding elicited by a CS that predicts sweet taste or food, Tomie and colleagues (Tomie et al., 1998; Tomie, Festa, Sparta, & Pohorecky, 2003; Tomie & Sharma, 2013) proposed a model of alcohol abuse that predicts that reactivity to an alcohol-predictive CS would promote alcohol drinking. In agreement with this prediction, we found that in well-trained rats, greater reactivity to the houselight predicted faster initiation of drinking, more drinking, and the ingestion of larger alcohol doses (Figure 3.5 A–C). These relationships may represent a causal stimulus-response chain or between-subject differences in biological and psychological factors that influence conditioning rates, final levels of cue reactivity, and drinking behaviors. The link between cue reactivity and drinking in our paradigm is consistent with the finding that current and former heavy drinkers tend to show greater autonomic, behavioral, and neural reactivity to alcohol cues (Sinha et al., 2009; Sjoerds, van den Brink, Beekman, Penninx, & Veltman, 2014; Townshend & Duka, 2001; Vollstädt-Klein et al., 2010). This link is also in accordance with the finding that alcohol cue reactivity measurements can predict alcohol-use disorder relapse after treatment (Drummond & Glautier, 1994; Monti et al., 1993; Papachristou, Nederkoorn, Giesen, & Jansen, 2014; Rohsenow et al., 1994; but see Witteman et al., 2015).
3.5.5 Summary
Using a rat model of alcohol cue conditioning in which alcohol’s post-ingestive pharmacology arguably serves as the unconditional stimulus, we were able to measure alcohol-directed appetitive and consummatory behaviors while tracking the level of alcohol exposure within and across drinking episodes. This allowed us to describe the
91 dynamics of behavioral reactivity potentially conditioned to distinct antecedent stimuli for alcohol’s post-ingestive effects. We found that cue reactivity within drinking episodes persisted despite progressive intoxication or satiety, and predicted overall levels of drinking. Insight gained here about the incidental conditioning of multiple alcohol- predictive cues can help guide future work on ways to attenuate the control that such cues exert over alcohol seeking and drinking.
3.6 SUPPLEMENTAL INFORMATION
3.6.1 Drinking unsweetened ethanol in the homecage
This analysis considered data from only 16 of the 30 rats because data from this phase of the experiment for the other 14 were previously analyzed in Chapter 2. As in that study, we found that across the 5 weeks of intermittent ethanol access sessions (24 hr) in the homecage, this independent cohort of 16 rats drank an increasing percentage of their total fluid from the ethanol bottle and ingested increasing doses of ethanol (main effects of session: F14, 210>=5.86, p<0.001; Figure 3.6). By the 5th week, drinking was stable (main effects of session considering only sessions 13-15: NS), at which point these 16 rats were drinking (mean ± sem) 48 ± 5 % of their total fluid from the ethanol bottle and ingesting ethanol doses (mean ± sem) of 3.6 ± 0.4 g/kg/24 hr.
3.6.2 Acquisition of sipper-site approach elicited by the houselight
This analysis considered data from only 16 of the 30 rats because data from this phase of the experiment for the other 14 were previously analyzed in Chapter 2. As in that study, this independent cohort of 16 rats learned to anticipate access to the ethanol solution (sipper presentation) based on houselight illumination. Sipper site approach level during different trial phases changed differently across conditioning sessions (trial phase x session
92 interaction: F22, 308=10.94, p<0.001; Figure 3.7). Sipper site approach during the 5 s period before houselight onset (preCS) remained at floor across sessions (simple effect of session: NS), whereas sipper site approach during both the 1st 5 s and 2nd 5 s of houselight illumination (CS1 and CS2, respectively) increased across sessions (simple effects of session: F11, 165>=8.81, p<0.001). The level of approach during houselight illumination (CS1 and CS2) was robust and asymptotic by session 10 (main effect of session considering only sessions 10-12: NS).
3.6.3 Acquisition of sipper contact and consummatory licking
This analysis considered data from 25 of 30 rats (5 were missing lick data due to equipment malfunction). All rats learned to interact with the device (sipper) that provided access to ethanol solution for oral consumption. The latency to initiate drinking was measured directly as the time elapsed from bottle assembly activation to first lick per trial. Drinking was measured directly as the number of licks per trial. On average, the latency to start licking per trial in a session decreased across sessions, and the number of licks per trial in a session increased across sessions (F11, 264≥47.57, p<0.001; Figure 3.8 A-B). For both measures, asymptote was reached by session 10 (main effect of session considering only sessions 10-12: NS).
3.6.4 Ethanol doses ingested in the conditioning task
This analysis considered data from only 16 of the 30 rats because data from this phase of the experiment for the other 14 were previously analyzed in Chapter 2. As in that study, across conditioning sessions, this independent cohort of 16 rats drank increasing doses of ethanol (main effect of session: F11, 154=19.73, p<0.001; Figure 3.8 C). Out of these 16 rats, 12 were conditioned with 15E, and 4 were conditioned with 10E. Treated as a
93 factor, there was a main effect of ethanol concentration on ingested dose (F1, 14=19.73, p<0.002), but no significant interaction with session: rats provided 10E achieved lower doses on average than rats provided 15E, but the dose escalation pattern across conditioning sessions was similar. Doses were stable by session 10 (main effect of session considering only sessions 10-12: NS). Across sessions 10-12, the 4 rats on 10E ingested (mean ± sem) 0.45 ± 0.04 g/kg/session whereas the 12 rats on 15E ingested (mean ± sem) 0.67 ± 0.06 g/kg/session. Collapsing across concentration, the rats ingested (mean ± sem) 0.62 ± 0.05 g/kg/session.
3.6.5 No houselight CS conditioning without ethanol US experience
Data from the 7 rats that failed to drink reliably during the conditioning task despite drinking in the homecage underscore the importance of verifying that ingested ethanol is pharmacologically active. Over the last week of homecage alcohol access, these rats ingested doses (mean ± sem) of 2.8 ± 0.5 g/kg/24 hr. Out of the 7 rats, 5 were drinking 10E, 2 were drinking 15E. Across conditioning sessions, these rats ingested doses not expected to produce detectable levels of ethanol in blood (Figure 3.9 A). As a consequence, houselight illumination did not acquire the ability to elicit robust alcohol seeking (indexed by sipper site approach level) (Figure 3.9 B). These data further support the idea that the US in our conditioning task is ethanol’s post-ingestive pharmacology. There was no cue conditioning in the absence of pharmacologically active ingested doses.
94 3.7 FIGURES
ABTrial Session 5 s Trial 1 2 3 4 5 6 7 8 preCS CS1 CS2 CS3 CS4
Houselight ITI ITI 280 s variable ITI Sipper
C Ethanol Sipper Session Dry Sipper Session Trial
1 2 3 4 5 6 7 8 3 2 1
ApproachLevel 0 CS1 CS2
preCS Trial Phase
Figure 3.1. Dynamics of reactivity to houselight illumination.
A–B: Schematic representations of a session and trial. C: Mean ± S.E.M. sipper site approach level across trials phases (pre-CS, CS1, and CS2) paneled by trial for 30 adult, male Long-Evans rats. The maximum approach level per trial phase was 4 (see Behavior Measurements in main text Methods for videoscoring details). Data from conditioning session 12 are represented by black circles. Data from the dry sipper test session 24 h later are represented by white circles. Ambient ethanol odor was absent for dry sipper test trials.
95 10 Ethanol Sipper Session 8 Dry Sipper Session 6 4 2
Licking Latency (s) Latency Licking 0 12345678 Trial
Figure 3.2. Dynamics of reactivity to sipper presentation.
Mean ± S.E.M. latency (sec) to start licking across trials for 25 of 30 adult, male Long- Evans rats (data were missing for 5 of 30). Maximum latency was 10 sec, the total duration of sipper availability. Data from conditioning session 12 are represented by black circles. Data from the dry sipper test session 24 h later are represented by white circles. Ambient ethanol odor was absent for dry sipper test trials.
96 Ethanol Sipper Session Trial Dry Sipper Session
1 2 3 4 5 6 7 8 15
10
Licks 5
0 12345 Bin (2 s)
Figure 3.3. Dynamics of reactivity to oral ethanol receipt.
Mean ± S.E.M. licks per 2-sec bin paneled by trial for 25 of 30 adult, male Long-Evans rats (data were missing for 5 of 30). The sipper was available for 10 sec total, hence 5 bins per trial. Data from conditioning session 12 are represented by black circles. Data from the dry sipper test session 24 h later are represented by white circles. Ambient ethanol odor was absent for dry sipper test trials.
97 Ethanol (mg/dL) Ethanol Ethanol (g/kg)
Figure 3.4. Ethanol in blood after a conditioning session.
Relationship between blood ethanol concentrations detected at the end of a conditioning session and ingested ethanol doses. Data were from 24 of 30 adult, male Long-Evans rats. Solid line represents the regression line. Dashed lines represent the upper and lower 95% confidence limits around the regression line.
98 A Latency (s) Latency
B Licks
C Ethanol (g/kg) Ethanol
Approach Level
Figure 3.5. Houselight cue-elicited appetitive reactivity predicts drinking.
Relationships of latency to start licking per trial (A), total licks per trial (B), and ingested dose per session (C) to houselight-elicited sipper site approach level per trial (maximum = 4) on average across conditioning sessions 10–12. Data were from 25–30 adult, male Long-Evans rats (lick data were missing for 5 of 30). Solid lines in each panel represent the regression line. Dashed lines represent the upper and lower 95% confidence limits around the regression line.
99
Figure 3.6. Drinking in the homecage.
Panel A: Timelines for homecage alcohol drinking phase. Ethanol bottles contained 15% ethanol (v/v in tap water; 15E) except as noted under Behavioral Methods in the main text Methods section. Panel B: Mean ± sem fluid ingested from the ethanol bottle as a percentage of total fluid for 16 adult, male Long-Evans rats (data for the other 14 of 30 were previously analyzed). Panel C: Mean ± sem ingested ethanol doses for the same.
100 Figure 3.7. Conditioning of reactivity to houselight illumination.
Panels A-C: Protocol, session, and trial-level timelines for conditioning phase. Panel D: Mean ± sem sipper site approach level per trial across conditioning sessions (8 trials/session) paneled by trial phase for 16 of 30 adult, male Long-Evans rats (data for the other 14 were previously analyzed. The maximum approach level per trial was 4.
101 Figure 3.8. Drinking in the conditioning chamber.
Panel A: Mean ± sem latency (s) to start licking per trial across conditioning sessions (8 trials/session) for 25 of 30 adult, male Long-Evans rats (data were missing for 5 of 30). Panel B: Mean ± sem total licks per trial across conditioning for the same 25 of 30. Panel C: Mean ± sem ingested ethanol doses across conditioning sessions for 16 of 30 (data for the other 14 were previously analyzed. Ingested doses above the dashed line (0.30 g/kg) would be expected to be pharmacologically active.
102
Figure 3.9. Pharmacologically active ingested doses required to condition reactivity to houselight illumination.
Panel A: Mean ± sem ingested ethanol doses across conditioning sessions for 7 adult, male Long-Evans rats that drank reliably in the homecage, but not conditioning task. Ingested doses below the dashed line (0.30 g/kg) would be expected to be pharmacologically inactive. Panel B: Mean ± sem sipper site approach level per trial across conditioning sessions (8 trials/session) paneled by trial phase for the same 7 rats. The maximum approach level per trial was 4.
103 Chapter 4. Alcohol-associated antecedent stimuli elicit alcohol anticipation in a non-dependent rat model and activate the insula
4.1 ABSTRACT
Alcohol self-administration produces brain and behavior adaptations that facilitate a progressive loss of control over drinking and contribute to relapse. One possible adaptation is the ability of certain cues to trigger alcohol-appetitive (seeking) states. We previously showed that this adaptation can be modeled using our novel Pavlovian alcohol conditioning paradigm. However, in our previous work we did not demonstrate whether this adaptation represents a consequence of repeated alcohol exposure or alcohol- associative learning and memory. Here we tested the associative basis of cued alcohol- appetitive states by characterizing appetitive behaviors in adult male rats trained with houselight illumination that was explicitly paired or unpaired with alcohol sipper presentation. We also characterized consummatory behaviors in the same rats. Finally, we explored the brain basis of cued alcohol-appetitive states using c-Fos immunohistochemistry. Our findings confirmed the associative basis of cued alcohol- appetitive states and the existence of a dose threshold for the conditioning effects of ingested alcohol. The cued alcohol-appetitive state also appeared to exert some control over consummatory behavior. Cued alcohol-appetitive states were mapped onto the insula. Thus, we show that a key brain and behavioral adaptation to alcohol self-administration is not the result of merely repeated alcohol exposure, but rather associative learning & memory.
4.2 INTRODUCTION
Classical conditioning allows sensory stimuli to become associated with alcohol availability, ingestion, and/or pharmacology. Conditioned behavioral and physiological
104 reactivity to these alcohol-predictive cues contributes to the risk for relapse to problem drinking. We recently developed a rat model of this alcohol cue reactivity (Chapter 2), and close inspection of our model suggested that multiple antecedent stimuli were likely conditioned as alcohol-predictive cues (Chapter 3). Here, we verify whether reactivity to the target alcohol-predictive cue, at least, stems from associative learning and whether memory for that cue-alcohol association maps onto brain regions that are implicated in alcohol addiction. In our paradigm, conditioning trials involve illumination of a houselight followed by brief access to an alcohol sipper. Houselight illumination appears to gain the ability to elicit anticipatory approach to the sipper (viz., an alcohol-appetitive state). If this response reflects a learned association with alcohol, then it should only be acquired when illumination predicts alcohol access (the classic “Paired” conditional-unconditional stimulus (CS-US) arrangement). However, if the same alcohol-seeking response is acquired when alcohol access is explicitly “unpaired” with illumination by presenting the sipper only during the interval between illuminations (“Unpaired” CS/US arrangement), then it stems from something other than associative learning (e.g., sensitization). In the same paradigm, sipper presentation appears to gain the ability to initiate drinking bouts and oral alcohol receipt appears to gain the ability to increase drinking speed within bouts. However, both stimuli are always experienced during houselight illumination. As such, it is possible that what look like responses to two other distinct cues (sipper presentation, oral alcohol receipt) actually represent facilitation of consummatory behavior by the association of houselight illumination with alcohol access. If so, then once the houselight cue-alcohol association is formed, rats in the “Paired” cue group should initiate drinking bouts faster than rats in the “Unpaired” cue group. Additionally, only rats in the “Paired” cue group should show within-bout drinking acceleration. 105 Many therapies for alcohol use disorder (e.g., naltrexone, cue exposure, counterconditioning) are predicated on the idea that maladaptive alcohol-associative memories (implicit or not) drive relapse. Knowing whether alcohol-related behavior stems from associative or non-associative memory is important because different approaches (behavioral and pharmacological) are needed to target associative and non-associative aspects of behavior. Ideally, we would know how (associative v. non-associative), as well as where alcohol-related cue memories are encoded in the brain. Consequently, in the present study, using the same rats in which we characterized behavior and verified blood ethanol, we evaluated expression of the immediate-early gene product c-Fos as an index of cellular activity in brain regions that may be involved in maintaining and/or expressing alcohol-related cue memories, with a focus on those regions implicated in cue-induced relapse to alcohol-seeking (Koob & Volkow, 2010).
4.3 METHODS & MATERIALS
4.3.1 Subjects
Adult male Long-Evans rats were used (Envigo; Indianapolis, IN, USA). Upon arrival, rats weighed 250-275 g. All were singly housed in a temperature- and humidity- controlled room (22±2 ºC; 12hr light cycle). The homecage contained Sani-Chips® bedding and a Bio-Serv Gummy Bone (polyurethane; 5 cm L x 2.5 cm W). Metal wire cage-tops were used. Standard chow pellets were loaded into a large cup inside the cage. Tap water was provided via gravity-fed sipper inserted at approximately 45º from the cage top. Chow and water were replenished daily. Bedding was replaced weekly. All procedures took place during the light phase of the light/dark cycle. The colony room was adjacent to the procedure rooms. Ethanol (v/v) solutions were prepared every 3 days from 95% ethyl alcohol (ACS/USP grade, Pharmco-AAPER, Brookfield, CT, USA) and tap water. 106 Solutions were kept and served at room temperature (20 ºC). All procedures were approved by the Institutional Animal Care and Use Committee at the University of Texas at Austin, and conducted in accordance with NIH guidelines.
4.3.2 Behavioral Methods
4.3.2.1 Paired and Unpaired Cue-Ethanol Conditioning
All conditioning took place in conditioning chambers housed in sound attenuating cubicles equipped with a digital video camera (for detailed description of the apparatus, see Chapter 2. After familiarization with ethanol in the homecage (see Supplemental Information, 4.6 below), 2 groups matched on ingested doses were created. For one group (assigned to our usual conditioning procedure), houselight illumination was explicitly paired with alcohol sipper presentation (creating group “Paired”). For the other group, the houselight stimulus was explicitly unpaired with alcohol sipper presentation (creating group “Unpaired”). There were 12 conditioning sessions (1/day). Each session consisted of an 8-trial block of houselight illuminations on a variable intertrial interval (ITI). The ITI was selected randomly from a list (160 s, 240 s, 240 s, 250 s, 320 s, 320 s, 350 s, 360 s) until all values were exhausted before any value was repeated. The session started—the first ITI was selected—after the conclusion of a 5 min pre-session wait period. Session start was signaled by cubicle exhaust fan onset. The session ended once the final (9th) ITI (selected after the 8th trial) had elapsed and was signaled by exhaust fan offset. On average, session duration was 32-36 min. Sessions were given across consecutive days and at approximately the same time every day by the same single experimenter. During each trial, the houselight was illuminated for 20 s. In group Unpaired, there was no consequent event. However, in group Paired, the retractable bottle assembly was 107 activated 10 s into the illumination to present the metal sipper such that alcohol access and illumination co-terminated. For group Unpaired, sipper presentations instead occurred mid-ITI, beginning in ITI 2 and ending in ITI 9. Houselight illumination onset, offset, and ITIs were yoked between groups. Retractable bottle assembly activations were yoked within groups. Licking the sipper produced 10E or 15E (whichever solution the rat was drinking at the end of homecage pre-exposure). The sipper contained a ball bearing to prevent fluid spill upon insertion and retraction. When inserted, the tip was typically in the plane of the wall. In other words, the sipper did not protrude far into the chamber. At most, 500 ms elapsed between activation of the bottle assembly and availability of the sipper. Rats were acclimated to the conditioning chambers and stimuli 48 hr after the last homecage drinking session. Rats were first familiarized with the retractable magazine in the chamber by giving a single session in which the sipper was presented for 35 min, during which time rats were free to lick out unsweetened ethanol. The next day, rats were habituated to houselight illumination in the chamber by giving a single session in which the houselight was illuminated 8 times (using the same 280 s variable ITI selection process later used in conditioning). During this session, the bottle assembly was never activated and ethanol was absent from the room.
4.3.2.2 Brain Collection Day
After 5-7 more conditioning sessions—given to ensure that daily drinking opportunity expectancies and within-session behavior patterns were stable—4 groups matched for ingested doses across all conditioning sessions were created. On brain collection day, rats in 2 groups (Paired Run, Unpaired Run) were weighed and transferred
108 into the conditioning chambers for a conditioning session. Rats in 2 other groups (Paired Not Run, Unpaired Not Run) were not handled and stayed in the homecage. All brains were collected 90 min from the beginning of the conditioning session given to the Run groups. All rats were anesthetized with isoflurane gas and administered euthanasia III solution (Med-Pharmex, Inc., Ponoma, CA, USA). Following euthanasia, tissues were fixed by perfusing phosphate buffered saline (pH 7.2) (PBS) then 4% para- formaldehyde w/v in PBS (fixative solution). Brains were kept in 20% sucrose m/v in fixative solution overnight. Brains were flash-frozen on dry ice the next day and stored at
-80ºC until processing for Fos immunohistochemistry.
4.3.2.3 Behavioral Measurements
Trials from conditioning sessions 1-12 were sampled for appetitive behavioral state from digital video recordings by making instantaneous observations every 1.25 s starting 5 s before houselight onset as in Chapter 2 such that there were 4 observations per trial phase. Trial phase or bin “-1” refers the 5 s period before houselight onset and trial phase or bins 1-4 refer to 5 s periods across the houselight illumination. At each observation, the mutually exclusive rating options were “sipper site approach” (approaching, attending to, or exploring the sipper insertion hole, including sniffing, gnawing, and clawing at the hole), “orienting” (rearing: both forepaws off the floor, supported by hindlimbs) or “other” (e.g., grooming, resting). Sipper licking was recorded automatically using a contact lickometer circuit. Behavioral state observations were made by highly trained judges (intra- and inter- rater agreement ≥95%). However, since within-trial events differed dramatically, it was impossible to blind raters to “Paired” v. “Unpaired” status, thus bias was possible. In order to corroborate “sipper site approach” state observations, after the 12th conditioning session, we customized the metal panel on which the retractable bottle assembly was mounted. The
109 portion of the panel bearing the sipper hole was cut, trimmed, and seated in a polylacticacid plastic frame (7.11 cm L, 0.32 cm W, 3.71 cm H) in order to electrically isolate it from the rest of the conditioning chamber. The exposed metal surface (6.91 cm L, 0.32 cm W, 3.66 cm H) was then wired into a second contact lickometer circuit, allowing automated recording of forepaw contact with the area around the sipper hole. The dose of ethanol ingested by each rat was also monitored during each homecage and conditioning session. Drinking solution intake was measured as the mass difference in bottle weight pre- and post-session after correcting for spillage. The grams of solution ingested were then converted to g ethanol and ingested dose was expressed as g/kg body weight for each rat. For every 24 hr homecage drinking session, bottles on an empty control cage were used to measure loss due to evaporation and spillage and correct solution intake values across all subjects. For every conditioning session, a weighboat underneath each bottle assembly collected spillage such that solution intake values were corrected at the level of each individual subject.
4.3.2.4 Fos Immunohistochemistry
Brain sectioning, tissue processing, and c-Fos immunostaining was performed as in (Lee et al., 2005). For details, see Supplemental Information (4.6 below).
4.3.3 Statistical Analysis & Data Visualization
Behavior data were analyzed using mixed factorial analysis of variance (ANOVA). The link between ingested dose and blood ethanol was evaluated using Pearson’s correlation test. Fos data were analyzed by running ANOVA within structures considering the between-subject factor of group (Paired v. Unpaired), the within-subject factor of brain region (e.g., in the Accumbens ANOVA, shell v. core), and their interaction. Known Fos
110 expression differences between structures (e.g., dorsal striatum v. basolateral amygdalar complex) and missing data precluded ANOVA considering all sampled structures. Separate ANOVA were done for the “Run” and “Not Run” conditions because our primary interest was differential induction of Fos in groups Paired and Unpaired and we did not have true control groups (e.g., conditioning-naïve and/or ethanol-naïve rats). The threshold for statistical significance was p<0.05. Follow-up analyses were conducted in stages. At the highest stage, ANOVA was used to test simple effects. At lowest stage, paired or independent samples t-test was used to compare means, if necessary. Bonferroni correction was applied at each follow-up stage to keep the Type 1 error rate ≤ 5%. All analysis was done in R version 3.41 (R Core Team, 2017) using the car package (Fox & Weisberg, 2011). Data were plotted in R using the ggplot2 package (Wickham, 2009) and finalized in Inkscape version 0.92.2 (Inkscape Team, 2017).
4.4 RESULTS
4.4.1 Acquisition of alcohol drinking and behavioral reactivity
A total 35 rats were obtained for this study. Of those screened, 29 ingested doses ≥ 1 g/kg/24hr on average over the last week of homecage drinking, and were retained for conditioning. Of those conditioned, 17 ingested doses ≥ 0.30 g/kg/session on average across the last 3 sessions—the dose threshold for conditioning effects of ingested ethanol we observed in our previous study (Chapter 3). The other 12 ingested doses consistently below that threshold. Behavioral reactivity and drinking data across conditioning sessions for both subsets are provided in Supplemental Information (4.6 below). The main text presents trial-by-trial behavioral reactivity data within conditioning session 12 —two sessions into the asymptote on alcohol drinking and conditioning observed in our previous study (Chapter 3)—for the 17 rats that drank above the dose threshold. After 1-2 more 111 conditioning sessions, we determined “end-of-session” blood ethanol concentrations in order to verify equivalent exposure. These blood ethanol data are presented in Supplemental Information (4.6 below).
4.4.2 Ethanol-directed reactivity to houselight illumination depends on relationship between ethanol access and houselight illumination
Given the timeline of events within trials, their repetition within conditioning sessions, and the presumably post-ingestive nature of the unconditional/reinforcing stimulus, group Paired and Unpaired alike may learn to associate houselight illumination with ethanol access. The classic conditioned response to reward-predictive cues is anticipatory/preparatory reward-seeking. In our paradigm, this would be houselight illumination-elicited ethanol sipper site approach and contact (scored approach state). To characterize this form of reactivity in our paradigm, we analyzed ethanol (sipper site)- directed approach and contact behavior during houselight illumination on a per trial basis for 9 well-trained rats in group Paired and 8 well-trained rats in group Unpaired. Ethanol access-anticipatory behavior patterns differed by cue group (group x trial phase x trial interaction: F14, 210=3.61, p<0.001; Figure 4.1 A). Group Unpaired exhibited a negligible and invariant level of approach to the sipper site (trial phase, trial, and trial phase x trial effects: NS). In contrast, group Paired exhibited robust levels of sipper site approach that varied within trials differently across trials (trial phase x trial interaction: F14, 112=4.44, p<0.001). Specifically, approach level varied by trial phase within trials 1-4 (simple effects of trial phase: F2, 16≥7.43, p<0.001), but not trials 5-8 (simple effects of trial phase: NS). Generally, sipper site approach was elicited by houselight onset and its frequency increased across the illumination period in trials 1-4. In keeping, rats in group Paired exhibited more
112 houselight illumination-elicited sipper site approach (CS1 and CS2) in trials 1-4 than trials
5-8 (t8≥3.95, p<0.005). To confirm scored approach state results, which can be subject to rater bias, we used a modified lickometer to measure sipper site/faceplate contact, a component of the ethanol seeking behavior, directly in 7 Paired and 6 Unpaired well-trained rats (group sample sizes smaller due to equipment limitations). In agreement with scored approach state results, we found that the number of contacts varied across trials (F7, 77=15.44, p<0.001) in a way that depended on trial phase (F14, 154=2.90, p<0.001) and group (F7,
77=6.90, p<0.001). Group Unpaired rats exhibited some variation in sipper site contact frequency across trials, but it was not statistically significant after Bonferroni correction
(trial main effect: F7, 35=2.65, NS; trial phase main effect and trial phase x trial interaction: F<1.5, NS). In contrast, sipper site contact frequency in group Paired manifested the same within-trial and across-trial patterns as sipper site approach state frequency (trial phase x trial interaction: F14, 84=2.28, p<0.02; Figure 4.1 B). A similar per-trial analysis of the classic overt attentional response (orienting) to houselight illumination for well-trained rats in group Paired and Unpaired is provided in Supplemental Information (4.6 below).
4.4.3 Dynamics but not form of reactivity to ethanol sipper presentation depends on relationship between ethanol sipper presentation and houselight illumination
Ethanol sipper presentation involves auditory and visual stimuli, so it is conceivable that sipper presentation could condition approach to the sipper site and initiation of consummatory sipper licking (i.e., drinking bouts). To characterize reactivity to sipper presentation, we analyzed the latency to make forepaw contact with the sipper site/faceplate (an index of sipper-elicited sipper site approach; Paired group n=7; Unpaired
113 group n=6 due to equipment limitations) as well as the latency to start licking the sipper (Paired group n=9; Unpaired group n=7 due to data loss) in well-trained rats. We found that the latency to make initial contact with the sipper site/faceplate after retractable bottle assembly activation (i.e., after the noise immediately preceding sipper insertion) was similar between groups overall (group main effect: F1, 11<1, NS), but varied across trials differently between groups (group x trial interaction: F7, 77=3.86, p<0.002) (Figure 4.2 A). Specifically, latency did not vary significantly by trial for group Unpaired (simple effect of trial: NS), but increased across trials for group Paired (simple effect of trial: F7, 42=5.82, p<0.001; trials 1-4 v. 5-8: t6=5.56, p<0.002). Thus, sipper presentation was able to elicit sipper site approach and contact in both groups, although within-session dynamics were different between groups. We also found that the latency to start licking the sipper was similar between groups overall (group main effect: F1, 14=1.3, NS), but varied across trials differently between groups (group x trial interaction: F7, 98=3.577, p<0.002) (Figure 4.2 B). Rats in group Paired were faster to start licking in trials 1-3 than 4-8 (simple effect of trial: F7, 56=6.856, p<0.001). In contrast, latency to start licking was invariant across trials for rats in group
Unpaired (simple effect of trial: F7, 42<1, NS). Thus, sipper presentation was able to elicit rapid initiation of drinking bouts (consummatory licking) in both groups, although within- session dynamics were different.
4.4.4 Dynamics but not form of reactivity to oral ethanol receipt depends on relationship between oral ethanol receipt and houselight illumination
Sensation of ethanol’s orosensory stimulus properties is arguably the most reliable predictor of ethanol’s post-ingestive pharmacology. Indeed, oral ethanol receipt may serve as a conditional stimulus for both groups in our paradigm and most likely controls ingestion
114 rate. Consequently, we characterized reactivity to oral ethanol receipt by analyzing the lick rate (licks per 2 s) within and across sipper presentations for 9 well-trained rats in the Paired cue group and 7 out of 8 well-trained rats in Unpaired cue group. Equipment malfunction led to data loss for 1 rat in this latter group. We found that lick rate patterns varied by bin and by trial depending on cue group
(group x bin interaction: F4, 56=5.25, p<0.05; group x trial interaction: F7, 98=3.76, p<0.05; bin x trial interaction: F28, 392=1.42, p=0.079; group x bin x trial interaction: F28, 392=1.39, p=0.093). Specifically, lick rates varied by bin within trials differently across trials for rats in group Paired (simple bin x trial interaction: F28, 224=2.05, p<0.001), but not group
Unpaired (simple bin x trial interaction: F28, 168<1, NS) (Figure 4.3). On average across bins, lick rate decreased over trials for rats in group Paired (simple main effect of trial: F7,
56=8.63, p<0.05), but not group Unpaired (simple main effect of trial: F7, 42<1, NS). On average across trials, lick rate varied by bin in group Unpaired (simple main effect of bin:
F4, 24=66.12, p<0.001). Specifically, lick rate increased across bins 1-2 (t6=-10.83, p<0.001) and maintained that rate over bins 3-5 (remaining 6 s of sipper presentation; bin 2 v. 3, 3 v. 4, and 4 v. 5: NS). The rats in group Paired exhibited the same within-trial pattern in trials 1-5 (simple effects of bin: F4, 32≥4.53, p<0.006; bin 1 v. 2 comparisons within trials
1-4: t8<-3.62, p<0.01, in trial 5: t8=-2.79, NS after Bonferroni correction; bin 2 v. 3, 3 v. 4, and 4 v. 5: NS for every trial). In trials 6-8, Paired group rats’ lick rates increased only gradually over bins 1-5, if at all (simple effects of bin in trials 6-8: F4, 32≤2.40, NS). Thus, the initial receipt of oral ethanol solution was similarly able to accelerate the rate of consummatory licking within trials in most trials for both groups, but this response decayed across trials in group Paired.
115 4.4.5 Different brain regions are responsive to Paired v. Unpaired cue-ethanol conditioning
To begin mapping the substrates of ethanol-associated cue memories in our models, we obtained brain tissue for all 17 rats that consistently drank ≥ 0.30 g/kg and evaluated expression of the immediate-early gene product c-Fos. Following immunostaining for c- Fos protein, sections were imaged and Fos+ cells counted. For each brain region, cell counts were averaged across sampling regions, atlas levels, and hemispheres to index regional activation. We found no significant difference between group Paired and Unpaired (group main effect and group x sub-region interaction: NS) in either the Run or Not Run condition for mean Fos+ cell counts in the following brain regions: the medial and lateral divisions of the orbitofrontal cortex (Figure 4.4 A), the prelimbic and infralimbic divisions of the medial prefrontal cortex (Figure 4.4 B), the core and shell compartments of the nucleus accumbens (Figure 4.4 C), the medial and lateral aspects of the dorsal striatum (Figure 4.4 D), the medial and lateral divisions of the amygdalar central nucleus (Figure 4.4 E), and the substantia nigra pars compacta/ventral tegmental area complex (Figure 4.4 F). However, we did find that in the Run condition, there was a significantly greater mean Fos+ cell count in group Paired across the anterior and posterior divisions of the insular cortex (group main effect: F1, 6=13.17, p<0.02; group x sub-region interaction: F1,
6<1, NS; Figure 4.4 G). In the Not Run condition, mean Fos+ cell counts did not differ significantly between groups Paired and Unpaired (group main effect and group x sub- region interaction: F1, 7<1, NS). In the basolateral complex of the amygdala (Figure 4.4 H), we found significant group x sub-region interaction effects for both the Run (F2, 10=5.87, p<0.025) and Not Run condition (F2,14=3.96, p<0.05). In the Run condition, the mean Fos+ cell count differed by
116 region for group Paired (simple effect of region: F2, 4=8.02; specifically, basal and basomedial > lateral nucleus), but not Unpaired (F2, 5=1.45). However, this within-group by-region difference did not survive Bonferroni correction and none of the simple effects of group within regions were significant (even before Bonferroni correction). In the Not Run condition, group Unpaired had much greater mean Fos+ cell count in the BMA (simple effect of group: F1, 7=6.61); however, this too did not survive Bonferroni correction. In addition, neither simple effect of region within group was significant (even before Bonferroni correction) in the Not Run condition.
4.5 DISCUSSION
In the present study, we characterized the form and dynamics of behavioral reactivity of rats to specific alcohol-related stimuli in an oral alcohol conditioning task to determine whether reactivity was driven by associative or non-associative memory. In the same rats, we also verified blood ethanol and then used c-Fos expression as an index of cellular activation to map what brain areas may contribute to alcohol-related stimulus reactivity in the oral alcohol conditioning task.
4.5.1 Form of learned reactivity depends on the cue-alcohol relationship
As in other studies (Chaudhri et al., 2010; Remedios et al., 2014), fluid/food deprivation and sweetener were not necessary to either initiate or maintain alcohol drinking by adult male rats. In fact, a period of intermittent access in the homecage was sufficient to promote alcohol drinking and apparent habituation of initial taste aversion (Figure 4.6 A-B). After this period, rats were presented with an alcohol sipper intermittently in a different context (a conditioning chamber). Sipper presentation was accompanied by the sound of bottle assembly motor activation. Some rats were also provided with an alcohol
117 sipper-anteceding visual signal (houselight illumination; group Paired). Others were exposed to the same visual stimulus explicitly unpaired with alcohol sipper presentation (group Unpaired). These conditioning stimulus arrangements were designed to test whether any resulting behavioral reactivity to houselight illumination reflected its learned association with alcohol access. In keeping with the correspondence between the two stimulus arrangements, rats in both groups learned to approach the sipper quickly upon its presentation to initiate and sustain consummatory licking across the alcohol access period (Figure 4.8 A).
Consequently, rats drank increasingly larger doses across conditioning sessions (Figure 4.7 A) and alcohol was detectable in their blood after a session as a function of ingested dose (Figure 4.7 B; for extended discussion of blood alcohol levels in our paradigm see extended Chapter 3). However, in keeping with the key difference between the two stimulus arrangements, anticipatory approach to the site of alcohol access was only conditioned as a reaction to houselight illumination in group Paired (Figure 4.8 B). This is strong behavioral evidence that this cue-triggered alcohol-appetitive state reflects cue-alcohol associative memory, and not adaptation to repeated alcohol exposure per se. In keeping with our suggestion that conditioning stems from alcohol’s post-ingestive pharmacology (see extended discussion in Chapter 3), anticipatory approach was not conditioned in group Paired rats that consistently drank below 0.30 g/kg/session (Figure 4.10 A and C). We also observed this dose threshold for conditioning effects of ingested alcohol in our previous study (Chapter 3, Figure 3.9). It is worth mentioning that although the stimulus arrangement for group Unpaired was meant to eliminate the capacity of houselight onset to serve as a predictor for alcohol access, it was possible for these rats to have learned that houselight offset predicted alcohol access. This latter learning could have manifested as conditioning of the overt attentional 118 response to illumination (orienting) (Holland, 1980; Delamater & Holland, 2008). There was some behavioral evidence for this adventitious conditioning in the Unpaired group (Figure 4.9). Thus, given equivalent alcohol ingestion, the stimulus arrangement in group Paired conditioned an appetitive response whereas the stimulus arrangement in group Unpaired may have conditioned an attentional response.
4.5.2 Dynamics of learned reactivity depend on the cue-alcohol relationship
Well-trained rats in group Paired exhibited a decrease in houselight illumination- elicited alcohol-directed approach and contact across trials (Figure 4.1 A-B), an increase in latency to initiate drinking across trials (Figure 4.2), and a decrease in overall drinking rate across trials (Figure 4.3). This replicates our previous finding (Chapter 3, Figure 3.1). We previously suggested that this within-session behavior pattern might reflect the slow- onset of alcohol’s sedative-like effects (Chuck et al., 2006; Frye & Breese, 1981). However, this explanation is no longer tenable because in the present study, we observed that well-trained rats in group Unpaired exhibited no trial-by-trial variation in either their latency to initiate drinking or their overall drinking rate (Figure 4.2-4.3) even though they drank just as much alcohol as rats in group Paired. Another explanation for the within-session behavior pattern in group Paired is that the momentary incentive value of alcohol decreased across trials as a function of its slow- onset post-ingestive pharmacology (Samson et al., 1998, 2000). Alternatively, it is possible that dislike of alcohol’s taste was renewed across trials. It is thus plausible that reactivity to the houselight CS decreased across trials because this behavior was sensitive to changes in the incentive value of ingested alcohol or changes in the hedonic value of oral alcohol receipt. In either case, we would also expect within-session loss of consummatory vigor not only in group Paired, but also group Unpaired. However, we observed such only in the
119 former. Additionally, we have observed the same within-session behavior patterns in group Paired during a test session in which sipper licking no longer produced oral alcohol receipt (Chapter 3, Figures 3.2—3.3). One interpretation of this collection of findings is that in group Paired, the houselight CS can exert control over consummatory licking (which is instrumental for oral alcohol receipt and ingestion). This possibility would be in line with the known ability of alcohol-associated conditional stimuli to invigorate alcohol-directed instrumental responses (Corbit & Janak, 2007, 2016; Glasner et al., 2005; Krank 2003) and theory about how alcohol-associated conditional stimuli promote problem drinking (Tomie
& Sharma, 2013).
4.5.3 Insular cortex c-Fos expression in the rat depends on the cue-alcohol relationship
Overall, despite differences in study design, mean Fos+ cell counts in the present study were in line with those reported by others using rat models of oral alcohol conditioning (Dayas et al., 2007; Radwanska et al., 2008; Jupp et al., 2011). Our Fos expression findings corroborate the idea that some, but not all, brain regions involved in tests for alcohol cue-induced relapse-like behavior after extinction training are also those involved in maintaining or expressing alcohol-related cue memories (Figure 4.4 A-H). The ability of an alcohol-associated conditional stimulus (CS) to trigger alcohol approach behaviors has been previously shown to depend on excitatory drive onto glutamatergic cells in the basolateral amygdalar complex (BLA) (Chaudhri et al., 2010, 2013; Gass et al., 2011; Sciascia, et al., 2015; Millan et al., 2015) that can release somatomotor responses via striatonigral projections (Kreitzer 2009). Thus, we expected to see Fos induction in the BLA of group Paired, but not Unpaired after presentation of alcohol cues and alcohol in the conditioning chamber. Instead, we found that alcohol+cues
120 appeared to increase Fos expression in the BLA relative to the level of expression in rats that remained homecage, at least in group Paired, but Fos expression did not differ significantly between group Paired and Unpaired rats presented with alcohol+cues (Figure 4.4 H). The amygdalar central nucleus (CeA) can release endocrine, cardiac, and visceromotor responses (Veening et al., 1984; Zahm et al., 1999). Activation of the CeA has also been shown to be important for the anxiolytic effects of ingested alcohol in non- dependent rats (Sharko et al., 2013, 2016). Thus, we expected to see Fos induction in CeA of rats given the opportunity to drink alcohol on the day of brain collection (“Run” condition) relative to counterparts that remained in the homecage (“Not Run” condition). Instead, we found substantial Fos expression in both conditions (Figure 4.4 E). However, we know that the CeA is critical for processing negative reward prediction errors (Lee, Gallagher, & Holland, 2010). Plus, all rats in the present study may have learned to expect the opportunity to drink alcohol every day around the same time, so omission of the opportunity to drink alcohol would have produced a negative reward prediction error in the rats composing the “Not Run” condition. Thus, CeA Fos expression in “Not Run” rats may reflect processing of a negative alcohol reward prediction error whereas CeA Fos expression in “Run” rats may reflect the post-ingestive effects of alcohol. The insula provides excitatory input onto not only the BLA, but also the CeA (McDonald, 1998). Importantly, the interoceptive effects of ingested alcohol involve deactivation of the insula (Jaramillo et al., 2016). Thus, we expected to see decreased Fos expression in the insula of “Run” rats relative to “Not Run” counterparts. We found that alcohol appeared to decrease Fos expression in the insula of group Unpaired (“Run” relative to “Not Run” in Figure 4.4 F). In contrast, Fos expression in at least the posterior insula was increased in “Run” relative to “Not Run” rats in group Paired (Figure 4.4 F). 121 Additionally, Fos expression in the insula of “Run” rats in group Paired was twice as much as that of counterparts in group Unpaired (Figure 4.4 F). Since “Run” rats in groups Paired and Unpaired ingested equivalent alcohol doses on brain collection day, our findings suggest that either memory for the learned association of alcohol access with houselight illumination in group Paired involves the insula or that ingested alcohol has different effects in the insula of rats in group Paired and Unpaired. Our Fos findings come with critical caveats. First, we do not know the identity of the cells activated (i.e., expressing Fos) in each brain region. Projection neurons and interneurons, and their neurochemically-defined subtypes, play important roles in communication within and between brain regions. Furthermore, Fos induction also has been observed in astrocytes (Arenander et al., 1989; Edling et al., 2007; Hermann & Rogers, 2009). Second, our study considered only 4-5 rat brains per group. Third, we lack some control groups such as alcohol and/or conditioning-naïve control groups, and groups exposed to CS without alcohol ingestion. Fourth, since within-session behavior patterns differ between group Paired and Unpaired, we cannot rule out a pharmacokinetic contribution to observed differences in Fos induction. More work will be necessary to illuminate the brain bases of reactivity to alcohol drinking cues, including manipulation of putative substrates in order to confirm their involvement in alcohol-associative v. non- associative memory.
4.5.4 Conclusion
In the present study, we showed that in a rat model of the conditioning effects of ingested alcohol, behavioral reactivity to an antecedent visual stimulus signaling the opportunity to ingest alcohol resulted from alcohol-specific associative learning rather than non-specific effects of repeated exposure to alcohol or the visual stimulus. Memory for this
122 cue-triggered alcohol anticipation appears to involve at least the insula. Our findings highlight how alcohol-associated cues can come to control alcohol use and support continued investigation of the insula as a critical player in the progression of brain and behavioral adaptations to alcohol self-administration.
4.6 SUPPLEMENTAL INFORMATION
4.6.1 Fos immunostaining & analysis procedures
Brains were sliced on a freezing-microtome and 30 µm coronal sections were taken from prefrontal cortex through midbrain, and sequentially separated into 6 series. Series 1- 4 were cryoprotected and stored at -80°C. Sections from series 5 underwent Nissl staining to verify anatomical locations of adjacent immunostained sections. Sections from series 6 underwent c-Fos immunostaining. The primary antibody was rabbit c-Fos antibody (1:2500 dilution) (Santa Cruz Biotechnology, Dallas, TX, USA). After primary incubation (48 hr at 4°C), sections were rinsed in 0.1 M PBS and incubated with biotinylated secondary antibody, anti-rabbit (1:250 dilution) (Vector Laboratories, Burlingame, CA, USA), for 1 hour. Next, sections were rinsed with 0.1 M PBS and incubated with pre- formed avidin/biotin enzyme complex (ABC) (Vector Laboratories). After additional rinsing with 0.1M PBS, sections were color reacted using 3,3-diaminobenzidine (DAB) with nickel sulfate to visualize c-Fos. Sections were imaged using an Olympus BX61 bright-field light microscope (Waltham, MA, USA) at 10x magnification. Images of each brain region were captured using QCapture (QImaging, Surrey, BC, CA) with 2x2 binning. The resulting images were analyzed by creating circular counting frames in ImageJ (NIH, Bethesda, MD, USA). Counting frame placements were chosen based on Swanson’s rat brain anatomy atlas (2004). The area of each circular counting frame was calculated to 0.15
123 mm2. Fos+ cells were counted within these sampling regions (counting frames) by raters blind to experimental conditions. Using Swanson’s rat brain anatomy atlas (2004), the following structures were sampled for analysis (anterior-posterior coordinates given relative to bregma; AP): (1) orbitofrontal cortex (lateral and medial) (AP: +5.20 to +3.20 mm), (2) medial prefrontal cortex (prelimbic and infralimbic) (AP: +4.85 to +2.15 mm and +3.20 to +2.15 mm, respectively), (3) nucleus accumbens (shell and core based on Paxinos et al., 2009) (AP: +2.15 to +0.95 mm), (4) dorsal striatum (lateral and medial) (AP: +2.15 to +0.95 mm), (5) insula (anterior and posterior based on Shi & Cassell, 1998) (AP: +4.85 to -2.45 mm), (6) amygdala (basolateral and central complexes) (AP: -1.53 to -2.85 mm), and (7) substantia nigra pars compacta and ventral tegmental area (AP: -4.60 to -5.25 mm). The location and number of sampling regions per atlas level per brain region analyzed are shown in Figure 4.5.
4.6.2 Ethanol drinking in the homecage
Rats received 24 hr access to unsweetened ethanol in the homecage (15% ethanol in tap water; v/v; 15E) every MWF for the next 5 weeks starting the week after arrival as in (Cofresí, et al., 2017). Rats who failed to drink during the first week were provided 5% and then 10% ethanol in tap water (v/v; 5E, 10E) to promote drinking. Any rats drinking < 1 g/kg/24 hr across the last week were not retained for conditioning. Across homecage drinking sessions (Figure 4.6), rats in the Paired (n=9) and Unpaired (n=8) groups similarly drank an increasing percentage of their total fluid from the ethanol bottle (session main effect: F14,210=12.75, p<0.001; group main effect and group x session interaction: NS) (Figure 4.6 A). Ingested doses increased similarly between groups across homecage sessions (session main effect: F14,210=10.11, p<0.001; group
124 main effect and group x session interaction: NS) (Figure 4.6 B). Collapsing across group, rats (n=17) were drinking 51 ± 5 % of their total fluid (mean ± sem) from the ethanol bottle, ingesting doses of 3.4 ± 0.3 g/kg per 24 hr session across the last week of homecage access.
4.6.3 Ethanol drinking in the conditioning chamber
Both groups of rats (Paired and Unpaired) ingested similar doses across conditioning. Across sessions, ingested doses increased (F11, 165=37.71, p<0.001). ANOVA detected a significant interaction of session x group (group x session interaction: F11,
165=3.262, p<0.05), but follow-up revealed that while groups appeared to differ at session 1 and 8, which is trivial, these differences were not statistically significant after Bonferroni correction. In keeping, there were no group differences by the end of conditioning (group main effect and group x session interaction over session 10-12: NS) (Figure 4.7 A). Additionally, the cumulative dose ingested across conditioning sessions was similar between groups (t15=0.527, NS) (data not shown). Collapsing across group, rats (n=17) were drinking (mean ± sem) 0.49 ± 0.03 g/kg per session by the end of conditioning. To determine the relationship between ingested doses and blood ethanol levels, we took blood samples at the end of a conditioning (1-2 sessions after the 12th session in the protocol). As on any day, rats had unlimited chow and water in the homecage until they were transferred into conditioning chambers for a conditioning session. Body weights ranged from 409 to 505 g. Time between the 1st and 8th sipper presentation in a session was 34-37 min due to the variable ITI. Rats were removed from the chamber immediately after the 8th sipper presentation and anesthetized with isoflurane gas. Blood was then collected from the lateral saphenous vein (3 replicates per rat). Ethanol concentration (mg/dL) in 10 µL whole blood mixed with 90 µL saturated saline was determined using gas chromatography with flame ionization detection (GC-FID) as in (Carrillo et al., 2008).
125 Sampling time ranged from 8 to 12 min after the 8th sipper presentation. Blood ethanol concentration (BEC) at this time was significantly correlated with the total ingested dose (Pearson’s r=+0.80, t15=5.14, p<0.001) (Figure 4.7 B). This relationship was independent of the contingency between ethanol access and houselight illumination. When looking at these data it is important to remember that rats were neither food nor water restricted before the sampled conditioning session or any other session; thus, stomach contents and hydration state (both important determinants on BEC) vary freely day to day. Additionally, it is important to the remember that “sipping” opportunities are spaced roughly 4 min apart. Thus, we believe that these data provide, at best, a snap-shot of possible BECs, especially given that our sampling time probably captures some time past peak on the descending limb of the BEC time-curve.
4.6.4 Consummatory sipper licking across conditioning
Sipper contact was measured directly using a lickometer. Equipment malfunction resulted in failure to record sipper licking during at least one session for 1 rat in group Unpaired, reducing sample size to 7 for these analyses. For these analyses, “trial” refers to sipper presentations, which occurred at different times during sessions for the Paired and Unpaired groups. We found that across sessions, there was a decrease in the average latency to start drinking per trial (F11, 154=19.582, p<0.001), and a corresponding increase in the average size of drinking bouts (F11, 154=2.787, p<0.001) (Figure 4.8 A-B). ANOVA detected that the decrease in latency and increase in bout size varied by group (session x group interaction:
F11, 154≥3.707, p<0.05). As was the case for ingested doses, however, groups appeared to differ only at session 1 and 8, which is trivial, and those differences were not statistically significant after Bonferroni correction for multiple comparisons. In keeping, there were no
126 significant group differences by the end of conditioning (group effects, session effects, & group x session interactions over sessions 10-12: NS).
4.6.5 Acquisition of conditioned sipper site approach reaction to houselight illumination
Rats differed in development of a sipper site approach reaction to houselight illumination over the course of conditioning depending on whether ethanol sipper access occurred during trials (cue-ethanol Paired, n=9) or occurred halfway into the inter-trial intervals (cue-ethanol Unpaired, n=8) (group x trial phase x session interaction: F22,
330=2.512, p<0.001) (Figure 4.8 C). Sipper site approach frequency per trial varied by appetitive trial phase (5 s bin before houselight onset, 1st and 2nd 5 s bin post-onset) across sessions only for rats in the Paired group (trial phase x session interaction: F22, 176=2.225, p<0.05). In these rats, sipper site approach per trial during 10 s of houselight illumination increased in frequency across sessions (simple effects of session: F11, 88>=6.125, p<0.001) whereas approach per trial before houselight onset remained at floor across sessions (simple effect of session: NS). In contrast, sipper site approach frequency per trial remained at floor across trial phases and sessions for rats in the Unpaired group (trial phase, session, & trial phase x session interaction: NS).
4.6.6 Habituation of orienting reaction to houselight illumination
The rat’s overt attentional/orienting response to houselight illumination is to rear (scored orienting state). Rats differed in habituation of the orienting reaction to houselight illumination over the course of conditioning depending on whether ethanol access occurred during trials (cue-ethanol Paired, n=9) or occurred halfway into the inter-trial intervals
(cue-ethanol Unpaired, n=8) (group x session interaction: F11, 165=2.17, p<0.02; group x trial phase: F4, 60=4.84, p<0.002; session main effect: F11, 165=14.72, p<0.001; trial phase main 127 effect: F4, 60=16.13, p<0.001; Figure 4.9 A). Collapsing across sessions, orienting frequency per trial was similarly low between groups before houselight onset and during the first half of illumination (1st and 2nd 5 s bin post-onset) (simple effects of group within each trial phase: NS). However, orienting per trial during the last quarter of illumination (4th 5 s bin post-onset) was different: greater in group Unpaired than Paired (simple effect of group:
F1, 15=41.12, p<0.001). Collapsing across trial phases, orienting frequency per trial within each group changed across sessions (simple effects of session: F11, 88≥3.40, p<0.001). We evaluated the dynamics of orienting at asymptote by analyzing this behavior on a per-trial basis in session 12. This houselight-directed behavior differed by cue group
(group x trial phase x trial interaction: F28, 420=2.60, p<0.001). Specifically, group Paired exhibited a negligible and invariant level of orienting to the houselight (trial phase, trial, and trial phase x trial effects: NS). In contrast, group Unpaired oriented to the houselight, but the level of response was highly variable within and across trials (trial phase x trial interaction: F28, 196=2.70, p<0.001). At the beginning of the session (trials 1-3), rats in group Unpaired appeared to orient toward the time of light offset (the 4th 5 s bin of houselight illumination) (Figure 4.9 B).
4.6.7 No houselight CS conditioning without ethanol US experience
Data from 12 rats (6 Paired, 6 Unpaired) that failed to drink reliably during the conditioning task despite drinking in the homecage underscore the importance of verifying that ingested ethanol is pharmacologically active. Over the last week of homecage ethanol access, these 12 rats ingested doses (mean ± sem) of 2.61 ± 0.61 g/kg/24 hr (data not shown). Across conditioning sessions, these rats ingested doses consistently below 0.30 g/kg/session (Figure 4.10 A; group main effect: F1, 10<1, NS; session x group interaction: F11, 110<1, NS). Based on our blood ethanol data, these rats were not expected to have
128 experienced detectable levels of ethanol in blood at any point during the session. Although the orienting response to houselight illumination was habituated in both Paired and Unpaired rats (Figure 4.10 B), houselight illumination did not acquire the ability to elicit anticipatory sipper site approach (viz., ethanol seeking) in group Paired (Figure 4.10 C). These data further support the idea that the unconditional stimulus in our conditioning task is ethanol’s post-ingestive pharmacology. There was no conditioning of ethanol-directed behavior in the absence of pharmacologically active ingested doses.
129 4.7 FIGURES A. Anticipatory Sipper Site Approach in Session 12
EtOH soln EtOH Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 4 Paired (n=9) Unpaired (n=8) 3
Locomotion 2
Approach 1 clawing, gnawing, nosing hole 0 -1 1 2 CS Bin (5s)
B. Anticipatory Sipper Site Contacts in Session 12
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 EtOH soln 3 Paired (n=7) Unpaired (n=6) 2 Faceplate Contact 1 Contacts 0 -1 1 2 CS Bin (5s)
Figure 4.1. Ethanol sipper-seeking reaction to houselight illumination.
A: Mean ± sem level of anticipatory sipper site approach state response to houselight illumination across trial phases (5 s bin before light onset followed by two bins post-light onset but pre-sipper onset) within trials in conditioning session 12 for adult, male Long- Evans rats. Black and white squares represent group Paired (n=9) and Unpaired (n=8), respectively. B: Mean ± sem total anticipatory contacts with the sipper site (faceplate) in response to houselight illumination across trial phases within trials. Black and white squares represent group Paired (n=7 out of 9) and Unpaired (n=6 out of 8), respectively. Sample sizes reduced by equipment limitations. A-B: Approach state data (maximum response level was 4) were derived from offline manual videoscoring whereas contact data were collected online using a modified lickometer.
130 A. Sipper Site Contact Latency in Session 12
20 Paired (n=7) EtOH soln Unpaired (n=6) 15 Faceplate Contact 10
5 Latency (sec) Latency
0 12345678 Trial
B. Sipper Licking Initiation Latency in Session 12
10 Paired (n=9) Unpaired (n=7) EtOH soln 8 6 4
Latency (sec) Latency 2 0 12345678 Trial
Figure 4.2. Reactivity to sipper presentation.
A: Mean ± sem latency (s) to contact the sipper site (faceplate) following bottle assembly activation (noisy sipper onset signal) across trials. Black and white squares represent group Paired (n=7 out of 9) and Unpaired (n=6 out of 8), respectively. Sample sizes reduced by equipment limitations. B: Mean ± sem latency (s) to start licking (initiate drinking bout) across trials in conditioning session 12. Black and white squares represent group Paired (n=9) and Unpaired (n=7 out of 8 due to equipment malfunction), respectively.
131 Lick Rate Reactivity to Oral Ethanol in Session 12
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 16 Paired (n=9) Unpaired (n=7) 12
8 Licks
4
0 12345 Bin (2s)
Figure 4.3. Reactivity to oral ethanol receipt.
Mean ± sem licks across bins (2 s) within sipper presentations in conditioning session 12. Black and white squares represent group Paired (n=9) and Unpaired (n=7 out of 8 due to equipment malfunction), respectively.
132 A. OFC B. mPFC C. Accumbens Run Not Run Run Not Run Run Not Run 20 P U P U 20 P U P U 20 P U P U 15 15 15 10 10 10 5 5 5 0 3 3 0 Fos+ Cell Fos+ Fos+ Cell 0 Fos+ Cell ILC ILC PLC PLC lOFC lOFC nAcS nAcS nAcC nAcC mOFC mOFC D. Striatum E. CeA F. DA Midbrain Run Not Run Run Not Run Run Not Run 20 P U P U 60 40 P U P U 15 45 P U P U 30 10 30 20 5 15 10 3 3 0 0 Cell Fos+ 0 Cell Fos+ Fos+ Cell Fos+ SNc SNc VTA VTA DLS DLS DMS DMS lCeA lCeA mCeA mCeA
G. Insula H. BLA
Run Not Run Run Not Run 20 P U P U 60 15 45 P U * P U 10 * 30 * 5 15 0 333 Fos+ Cell Fos+ 0 Fos+ Cell Fos+ LA LA BA BA aIC aIC pIC pIC BMA BMA
Figure 4.4. Brain c-Fos expression after a Paired or Unpaired cue-ethanol conditioning session or its omission in well-trained rats.
Group-level mean ± sem of Fos-positive cell counts (averaged across sampling region, level, and hemisphere within individuals) across specific structures in the adult, male Long- Evans rat brain. See Supplemental Information (4.6) for immunostaining details. Data from rats that underwent conditioning on brain collection day (“Run” condition) and rats that remained in homecage on brain collection day (“Not Run”) are shown in separate panels for each brain structure. Dark gray bars represent data from group Paired. White bars represent data from group Unpaired. Unless otherwise indicated, sample sizes were: Run Paired n=4, Run Unpaired n=4, Not Run Paired n=5, and Not Run Unpaired n=4. Black- filled asterisk indicates Bonferroni-corrected p<0.05, white-filled asterisk indicates p<0.05 before correction.
133
Figure 4.5. c-Fos study.
Location and number of Fos+ cell sampling regions (0.15 mm2 each) per brain region per hemisphere shown on representative plates from Swanson’s rat brain atlas.
134 A. Changes in Preference
100 Paired (n=9) Unpaired (n=8) 75 50 25
(% Total Fluid) Total (% 0 Ethanol Solution Ethanol 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Session
B. Changes in Ingested Dose
6 Paired (n=9) Unpaired (n=8) 4
2
Ethanol (g/kg) Ethanol 0 12345678910 11 12 13 14 15 Session
Figure 4.6. Drinking in the homecage.
A: Timelines for homecage alcohol drinking phase. Ethanol bottles contained 15% ethanol (v/v in tap water; 15E) except as noted in the main text. B: Mean ± sem fluid ingested from the ethanol bottle as a percentage of total fluid for adult, male Long-Evans rats. Black and white squares represent group Paired (n=9) and Unpaired (n=8), respectively. C: Mean ± sem ingested ethanol doses for the same.
135 A. Ingested Doses Across Conditioning
0.6 Paired (n=9) Unpaired (n=8) 0.4
0.2 Ethanol (g/kg) Ethanol
0.0 1 2 3 4 5 6 7 8 9 10 11 12 Session
B. Ethanol in Whole Blood v. Ingested Dose
60 Paired (n=9) 50 Unpaired (n=8) 40 30 20
Ethanol (mg/dL) Ethanol 10 0 0.0 0.2 0.4 0.6 0.8 1.0 Ethanol (g/kg)
Figure 4.7. Drinking in the conditioning chamber.
A: Mean ± sem ingested ethanol doses across conditioning sessions for adult, male Long- Evans rats. Black and white squares represent group Paired (n=9) and Unpaired (n=8), respectively. Dashed horizontal line shows a priori study inclusion criterion (≥0.30 g/kg across sessions 10-12). B: Relationship between blood ethanol concentrations detected at the end of a conditioning session and ingested ethanol doses for the same 17 rats. Regression line and 95% confidence limits shown as solid and dashed lines, respectively.
136 Alcohol Sipper Licking Across Conditioning A 10 B 60 8 50 6 40 4 30 20 Paired (n=9) 2 Licks/Trial 10 Paired (n=9) Unpaired (n=7) Unpaired (n=7) Latency (s)/Trial Latency 0 0 1357911 1357911 Session
Acquisition of Anticipatory Sipper Site Approach
C CS bin -1 CS bin 1 CS bin 2 3 Paired (n=9) Unpaired (n=8) 2 1 Approach 0 1357911 Session
Figure 4.8. Conditioning task acquisition.
A-B: Mean ± sem latency (s) to start licking (A) and number of licks (B) per trial across conditioning sessions (8 trials/session) for adult, male Long-Evans rats. Black and white squares represent group Paired (n=9) and Unpaired (n=7 out of 8; data loss due to equipment malfunction), respectively. C: Mean ± sem levels of sipper site approach per trial across conditioning sessions (8 trials/session) paneled by trial phase (5 s bin before light onset followed by two bins post-light onset, but pre-sipper onset) for the same rats. Black and white squares represent group Paired (n=9) and Unpaired (n=8), respectively. The maximum response level was 4.
137 A. Orienting to Houselight Illumination Across Sessions
CS bin -1 CS bin 1 CS bin 2 CS bin 3 CS bin 4 2 Paired (n=9) Unpaired (n=8) 1 Orienting 0 1357911 Session B. Orienting to Houselight Illumination in Session 12
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 2.5 Paired (n=9) 2.0 Unpaired (n=8) 1.5 1.0 Orienting 0.5 0.0 -1 1 2 3 4 CS Bin (5s)
Figure 4.9. Orienting reaction to houselight illumination.
A: Mean ± sem levels of orienting (rearing) state response to houselight illumination per trial across conditioning sessions (8 trials/session) paneled by trial phase (5 s bin before light onset followed by four bins post-onset) for adult, male Long-Evans rats. B: Mean ± sem level of orienting response across trial phases within trials in conditioning session 12 for the same rats. A-B: Black and white squares represent group Paired (n=9) and Unpaired (n=8), respectively. Orienting state data (maximum response level was 4) were derived from offline manual videoscoring.
138 A. Ingested Doses Ineffective for Conditioning
0.6 Paired (n=6) Unpaired (n=6) 0.4
0.2 Ethanol (g/kg) Ethanol 0.0 1357911 Session B. Habituation of Orienting to Houselight Illumination
CS bin -1 CS bin 1 CS bin 2 CS bin 3 CS bin 4 2 Paired (n=6) Unpaired (n=6) 1 Orienting 0 1357911 Session C. Failure to Acquire Anticipatory Sipper Site Approach
CS bin -1 CS bin 1 CS bin 2 3 Paired (n=6) 2 Unpaired (n=6) 1 Approach 0 1357911 Session
Figure 4.10. No acquisition of conditioned approach without ingestion of pharmacologically-active ethanol doses.
A: Mean ± sem ingested ethanol doses across conditioning sessions for adult, male Long- Evans rats. Black and white squares represent group Paired (n=6) and Unpaired (n=6), respectively. Dashed horizontal line shows a priori study inclusion criterion (≥0.30 g/kg across sessions 10-12). B-C: Mean ± sem levels of orienting to the houselight (B) and sipper site approach (C) per trial across conditioning sessions (8 trials/session) paneled by trial phase (for B: 5 s bin before light onset followed by four bins post-onset; for C: 5 bin before light onset followed by 2 bins post-light onset but pre-sipper onset) for the same rats. Black and white squares represent group Paired (n=6) and Unpaired (n=6), respectively. The maximum response level was 4.
139 Chapter 5. Cue-alcohol associative learning in female rats and examination of estrous cycle in established limited access free-choice drinking
5.1 ABSTRACT
The ability of certain cues to trigger alcohol-appetitive (seeking) states is believed to facilitate progressive loss of control over drinking. We have shown that development of this behavioral adaptation reflects associative learning & memory in adult male rats. However, we do not know whether the same will be true for similarly aged females because preclinical evidence suggests that alcohol affects them differently. Adult Long-Evans female rats were allowed to drink unsweetened alcohol in the homecage and subsequently trained to self-administer in a conditioning chamber. For group Paired, the chamber houselight was illuminated to signal access to an alcohol sipper. For group Unpaired, alcohol sipper access was not predicted by illuminations. Next, alcohol access in the homecage was renewed and vaginal lavage was done to examine the potential influence of estrous cycle on drinking behavior. Ingested doses did not increase significantly from week 1 to 5 of pre-conditioning homecage alcohol access, but alcohol solution preference did. In group Paired, an alcohol approach reaction was conditioned. No such reaction was conditioned in group Unpaired despite equivalent exposure to alcohol. Across post- conditioning homecage sessions 1-8, both groups showed increased alcohol preference. Across post-conditioning sessions 9-16, alcohol preference and doses were similar between lavaged rats and no-extra-handling controls. Doses and preference across the 9-day observation period for lavaged rats did not appear to vary systematically as a function of estrous cycle stage. Cue-triggered alcohol-appetitive states in adult female rats do not represent an adaptation to repeated alcohol exposure per se, but rather reflect associative
140 learning about alcohol-predictive cues. Drinking in rats that had already been drinking for several months was independent of the estrous cycle and additional handling required to determine cycle stage.
5.2 INTRODUCTION
Certain environmental cues trigger alcohol-appetitive (seeking) states and play a key role in facilitating progressive loss of control over drinking. Importantly, progressive loss of control over drinking may occur faster in women than men (Diehl et al., 2007; Ehlers et al., 2010; Mann et al., 2005; Randall et al., 1999; Schuckit et al., 1995a, 1998; but see also: Alvanzo et al., 2011; Keyes et al., 2010; Lewis & Nixon, 2014). Despite this, many studies including our own (Chapters 2-4) were done exclusively in male rats, and therefore, little is known about alcohol cue conditioning in female rats. We first ask a basic question: is alcohol-related behavior in female rats the result of repeated alcohol exposure alone or associative learning about predictive stimuli such as the sight, smell, and taste of alcoholic beverages? To answer this question in the present study, we characterized appetitive and consummatory behavior in female rats trained to drink unsweetened alcohol from a sipper explicitly paired or unpaired with a visual cue (houselight illumination), all in the presence of ambient alcohol odor. We also verify that ingested alcohol in our conditioning paradigm produces alcohol in blood. Finally, we determine whether the conditioning paradigm affects later free-choice alcohol drinking and preference. According to some reports, women’s drinking may vary over the menstrual cycle (Harvey & Beckman, 1985; Mello, Mendelson, & Lex, 1990). Similarly, alcohol drinking and related behaviors in intact female rats may be affected by fluctuating gonadal hormone levels across the 4-5 day estrous cycle. However, determining cycle stage requires vaginal
141 lavage, an invasive procedure that may itself affect the acute response to ingested alcohol. To answer the question of whether repeated vaginal lavage may affect alcohol drinking, we measured drinking behavior daily while performing vaginal lavage after the cue-alcohol conditioning was completed. We also analyzed data to evaluate whether the estrous cycle can affect alcohol drinking and preference. In summary, the first goal of the present study was to determine whether cue-trigger alcohol-appetitive states in female rats resulted from repeated alcohol exposure alone or associative learning about alcohol-predictive cues. The second goal was to determine whether vaginal lavage can affect free-choice alcohol drinking and preference. The third goal was to evaluate the influence of the estrous cycle on free-choice alcohol drinking and preference.
5.3 METHODS & MATERIALS
5.3.1 Subjects
Subjects were adult female Long-Evans rats (Envigo; Indianapolis) weighing 200- 225 g at arrival. Rats were singly housed in shoebox-style plexiglass homecages containing Sani-Chips® bedding and a Bio-Serv Gummy Bone (polyurethane; 5 cm L x 2.5 cm W). Metal wire cage-tops were used. Standard chow pellets were loaded into a large cup inside the cage. Tap water was provided via gravity-fed sipper inserted at approximately 45º from the cage top. Chow and water were replenished daily. Bedding was replaced weekly. Cages were located in a temperature and humidity controlled room (22±2 ºC) All procedures took place 4-5 hr into the light phase of a 12 hr light/dark cycle unless otherwise indicated. Drinking solutions were prepared from 95% ethyl alcohol (ACS/USP grade, Pharmco- AAPER) and tap water every 3 days. These were kept and served at room temperature (20
142 ºC). All procedures were approved by the Institutional Animal Care and Use Committee at the University of Texas at Austin, and conducted in accordance with NIH guidelines.
5.3.2 Behavioral Methods
5.3.2.1 Pre-conditioning ethanol drinking in the homecage
The pre-conditioning procedure was described in Chapter 2. Briefly, rats were provided a bottle of unsweetened ethanol (15% ethanol in tap water; v/v; 15E) and a new bottle of water for 24 hr every MWF for 5 weeks. Bottle placement on the cage-top alternated (ethanol on left- v. right-side) across sessions. Rats that failed to drink in week 1 were provided 5% and then 10% ethanol in tap water (v/v; 5E, 10E) to promote drinking. Any drinking < 1 g/kg/24 hr across week 5 were not retained for conditioning.
5.3.2.2 Ethanol-reinforced classical conditioning
The conditioning chambers used were described in Chapter 2. The conditioning procedures were described in Chapter 4. Briefly, rats were assigned to “Paired” or “Unpaired” conditioning such that the resulting groups were matched for ingested doses across the 5 weeks of pre-conditioning drinking sessions. Rats in both groups were trained on the retractable ethanol sipper and habituated to conditioning chamber houselight illumination. Rats then underwent cue conditioning across 12 consecutive days. Each conditioning session consisted of 8 trials. The inter-trial interval (ITI) was variable (mean: 280 s, min: 160 s, max: 360 s). The session started (the first ITI was selected) after the conclusion of a 5 min wait period and was signaled by exhaust fan onset. The session ended when the final ITI (selected after trial 8) elapsed and was signaled by exhaust fan offset. During each trial, the houselight was illuminated for 20 s. In the Unpaired group, there was no consequent event whereas in the Paired group, the retractable bottle assembly was
143 activated 10 s into the illumination to present the metal sipper such that ethanol access and illumination co-terminated. Sipper presentations for the Unpaired group occurred mid-ITI, beginning in ITI 2 and ending in ITI 9. Houselight illumination onset, offset, and ITIs were yoked between groups. Sipper presentations were yoked within groups. Licking the sipper produced 10E or 15E, whichever the rat was drinking at the end of the pre-conditioning phase.
5.3.2.3 Blood collection & ethanol analysis
After the 12th conditioning session, 1-2 additional sessions were given. At the end of one of these sessions, blood was sampled from the lateral saphenous vein while the rat was under isoflurane anesthesia. Ethanol concentration (mg/dL) in the blood sample was determined using gas chromatography with flame ionization detection as in (Carrillo et al., 2008).
5.3.2.4 Post-conditioning ethanol drinking in the homecage
After blood sampling, rats received no more sessions in the conditioning chambers. Instead, ethanol was once again made available in the homecage. Every day for 8 days, rats were provided with a bottle of 15E and a new bottle of water for 0.5 hr. Bottle placement on the cage-top alternated (ethanol on left- v. right-side) across sessions.
5.3.2.5 Vaginal lavage & estrous cycle stage determination
Rats were assigned to vaginal lavage or no additional handling such that the resulting groups were matched for ingested doses across the 8 post-conditioning drinking sessions and contained a similar number of rats from group Paired and Unpaired. Vaginal lavage was performed 5.5 hr after the drinking sessions starting on the 8th day of post- conditioning homecage access. We adapted the procedures described by Goldman, Murr, 144 & Cooper (2007). First, rats were gently restrained using a familiar handling towel. Then, the vaginal orifice/canal was quickly flushed with 40-80 µL fresh saline using a P200 pipette. Next, the lavage sample was deposited on a frosted, non-subbed slide and immediately inspected under a light microscope at 10x magnification. Finally, we assigned estrous cycle stages based on the relative proportion of different cell types in the sample. Samples containing primarily cornified epithelial cells (angular/irregular shape, jagged border) were assigned “estrus.” Samples containing primarily nucleated epithelial cells (large round shape, regular border) as if on beaded strands or in clumps were assigned
“proestrus.” Samples containing primarily leukocytes (tiny round cells) were assigned as “diestrus,” and samples containing a mixture of leukocytes and cornified cells were assigned as “metestrus.”
5.3.2.6 Behavior Measurement
Trials from conditioning sessions 1-12 were sampled for behavior from digital video recordings. As in Chapter 2, instantaneous observations were made every 1.25 s starting 5 s before houselight illumination such that there were 4 observations per 5 s bin. At each observation, the rater noted the absence or presence of mutually-exclusive behavioral states (sipper site approach: approaching or exploring the sipper insertion hole; orienting to light: both forepaws off the floor, supported by hindlimbs; other: grooming, resting). Sipper licking was automatically recorded using a contact lickometer circuit. A second, modified contact lickometer circuit was used to automatically record forepaw contacts with the area of the chamber wall immediately around the sipper insertion hole independently of sipper licking, as described in Chapter 4. Infrared photo-beams were used to track general locomotion in the stimulus rich (houselight fixture and sipper hole) v. poor (bare wall) zones of the conditioning chamber.
145 The dose of ethanol ingested by each rat was also monitored during each homecage and conditioning sessions. For every homecage drinking session, bottles on an empty control cage were used to measure loss due to evaporation and spillage and correct drinking solution intake values across all subjects. For every conditioning session, a weighboat underneath each bottle assembly collected spillage and drinking solution intake values were corrected at the level of each individual subject. Drinking solution intake was measured as the corrected mass difference in bottle weight pre- and post-session. To obtain the ingested ethanol dose, the amount (g) of pure ethanol consumed was computed and expressed relative to body weight (kg) each rat.
5.3.3 Statistical Analysis
Mixed factorial analysis of variance (ANOVA) was used for behavior and drinking data. Follow-up was done in stages. At highest stage, simple effects were tested using ANOVA. At the lowest stage, independent or paired t-tests were used. Bonferroni correction for multiple comparisons was applied at every follow-up stage. Pearson’s correlation test was used to evaluated the relationship between blood ethanol and ingested dose. The threshold for statistical significance was p<0.05.
5.4 RESULTS
Of 20 rats obtained for the study, 19 were conditioned on the basis of a priori retention criterion: ingested dose ≥ 1 g/kg/24hr on average across the last week of the pre- conditioning phase. Of the 19 rats conditioned, 17 provided data fit for primary analyses based on our a priori inclusion criterion: ingested dose ≥ 0.30 g/kg/session on average across the last 3 conditioning sessions. The 2 rats that failed to meet the latter criterion were both in group Unpaired.
146 5.4.1 Drinking in the homecage before ethanol cue conditioning
Rats in group Paired (n=10) and Unpaired (n=7) were matched for drinking across the pre-conditioning phase. Ingested ethanol doses did not increase significantly across homecage sessions in either group (session main effect, group main effect, and group x session interaction: NS; Figure 5.1 A). Collapsing across group, rats (n=17) ingested 3.65 ± 0.53 g/kg/session across sessions 1-3 and 4.96 ± 0.74 g/kg/session across sessions 13-15. However, in both groups, ethanol solution preference (% total daily fluid drank from ethanol bottle) increased significantly across sessions (session main effect: F14,210=2.68, p<0.01, Figure 5.1 B), indicating attenuation of initial aversion to the taste of unsweetened ethanol. Collapsing across group, rats (n=17) drank (mean±sem) 33 ± 4 % of their total daily fluid from the ethanol bottle across sessions 1-3 and 48 ± 4 % across sessions 13-15.
5.4.2 Acquisition of houseight cue-triggered alcohol appetitive state in group Paired, but not Unpaired
Groups differed in sipper site approach frequency during the appetitive trial phases across training (group x session interaction: F11,165=5.94, p<0.001; group x trial phase interaction: F2,30=5.18, p<0.05). For rats in the Paired group, sipper site approach frequency increased over sessions (simple effect: F11,99=12.03, p<0.001) and as a function of houselight illumination period (simple effect: F2,18=4.78, p<0.05; collapsing session, trial phase preCS < CS1 < CS2: t9>5.25, p<0.0001). In contrast, sipper site approach frequency remained at floor across trial phases and sessions for rats that underwent the Unpaired procedure (simple effects of session & trial phase: NS). As can be seen in Figure 5.2 A (right panel), the difference in sipper site approach level was clearest in trial phase CS2
(collapsing session, simple effect of group: F1,15=19.78, p<0.001). To confirm these findings, we also analyzed sipper site (faceplate) contact frequency, which was measured automatically using a modified lickometer circuit, and 147 thus, free of rater bias. Results were similar to those presented above. For rats in the Paired group, sipper site contact frequency during trial phases CS1 and CS2 increased over sessions (F11, 99≥5.64, p<0.001) whereas contact during trial phase preCS remained at floor (F11, 99<1, NS). In contrast, sipper site contact frequency during every trial phase remained at floor across sessions for rats that underwent the Unpaired procedure (F11, 99<1, NS). As can be seen in Figure 5.2 B (right panel), the difference in sipper site approach level was clearest in trial phase CS2 (collapsing session, simple effect of group: F1,15=5.78, p<0.05). By session 12, rats in group Paired made 3-5 sipper site contacts per trial on average in trial phase CS2 whereas rats in group Unpaired made no contacts per trial during the same.
5.4.3 Acquisition of similar reactions to sipper presentation in group Paired and Unpaired
Rats in group Paired and Unpaired alike learned to interact with the ethanol sipper. Note that equipment malfunction resulted in failure to record sipper licking during at least one session for 1 rat in group Unpaired, reducing sample size to 6 for these analyses.
There was a decrease across sessions in average latency to start licking per trial (F11,
154=12.58, p<0.001), and this varied by group (F11,154=2.05, p<0.05). There was a concomitant increase across sessions in average licks per trial (F11, 154=16.57, p<0.001), and this also varied by group (group x session interaction: F11,154=3.15, p<0.05). Although groups appeared to differ over sessions 1-3 (simple main effects: F1,14≥5.36; Figure 5.3 A- B), those differences were not statistically significant after Bonferroni correction. Additionally, there were no significant group differences in either average latency to start licking or average licks per trial by the end of conditioning (group, session, & group x
148 session interactions over sessions 10-12: NS before and after Bonferroni correction; Figure 5.3 A-B).
5.4.4 Drinking in the conditioning chamber across ethanol cue conditioning
Rats in group Paired and Unpaired drank similarly across the conditioning phase. Ingested dose increased significantly across sessions similarly between groups (session main effect: F11,165=26.08, p<0.001; group main effect and group x session interaction: NS). Despite apparent initial group differences in ingested doses (sessions 1-5), there were no significant group differences by the end of conditioning (session main effect, group main effect, and group x session interaction over sessions 10-12: NS; Figure 5.3 C). Additionally, the cumulative dose ingested across sessions by rats in group Paired (mean±sem: 4.95 ± 0.64 g/kg; n=10) and Unpaired (mean±sem: 6.20 ± 0.89 g/kg; n=7) was similar (t15=1.17, NS). Collapsing across group, rats (n=17) were drinking (mean±sem) 0.72 ± 0.05 g/kg/session by the end of conditioning.
5.4.5 Similar blood ethanol concentrations after a conditioning session
Blood samples were obtained for the 17 rats that met our a priori minimum drinking criteria across conditioning session 10-12. Blood ethanol concentration (BEC) at the end of the conditioning session was significantly related to ingested dose (Pearson’s r = +0.76, t15=4.60, p<0.001; Figure 5.4). Blood sampling time ranged from 8 to 11 min after the 8th sipper presentation. Body weights ranged from 260 to 318 g. Ingested dose ranged from 0.35 to 1.2 g/kg with a mean±sem of 0.72 ± 0.05 g/kg. BEC ranged from 0 to 38.5 mg/dL with a mean±sem of 15.9 ± 3.4 mg/dL. Groups Paired and Unpaired did not differ in BEC, ingested dose, the relationship between dose and BEC, sampling time, or body weight.
149 5.4.6 Vaginal lavage-required extra handling did not alter established daily drinking pattern
Rats underwent vaginal lavage (n=10) or no extra handling (n=9) 6 hr after the 8th post-conditioning homecage drinking session and 6 hr after every subsequent drinking session during the post-conditioning phase. Thus, after session 8, rats in group “Lavaged,” but not “Control,” experienced vaginal lavage 18 hr prior to every 0.5 hr drinking session. Experimental groups for this phase were made to be matched for ingested doses and ethanol solution preference across post-conditioning homecage sessions 1-8 (group main effect and group x session interaction: NS). This matching also produced equivalency on ingested doses across the conditioning and pre-conditioning phases (group and group x session interactions: F<1, NS). The number of group Paired and Unpaired rats in each handling condition was similar, and group Paired and Unpaired did not differ across post- conditioning homecage sessions 1-8 (see Supplemental Information, 5.6 below; Figure 5.7). We found that once the rats acclimated to daily limited access in the homecage (across sessions 1-8), ingested doses and ethanol solution preference exhibited little change across sessions 9-16, which correspond to sessions 1-8 in the lavage/no handling experiment (session main effect: F7, 119=2.03, p=0.056, NS; Figure 5.5 A-B). Importantly, we found that the extra handling required to perform vaginal lavage did not affect drinking (Figure 5.5 A-B)—neither the pattern of ingested doses or ethanol solution preference across sessions (lavage x session interactions: F7, 119≤1.67, NS) nor the overall dose or preference level (lavage main effect: F1, 17<1, NS).
5.4.7 Estrous cycle stage and daily drinking pattern
We were curious if estrous cycle stage information could help explain the established pattern of post-conditioning daily ethanol drinking in the homecage. Day-by- 150 day ingested dose and preference data for the freely-cycling rats that did and did not undergo vaginal lavage are provided in Figures 5.8—5.9). Out of the 10 freely-cycling rats that underwent daily vaginal lavage, 1 rat was determined to be in estrus across 5 consecutive days (Figure 5.8 top row, first panel), so her data were excluded from analyses. The remaining 9 rats completed 2 cycles in the 9 observation days. ANOVA on ingested doses (Figure 5.6 A) detected neither a significant within- subject main effect of observation day nor a significant within-subject or between-subject main effect of estrous cycle stage. Similar results were obtained when we analyzed ethanol solution preference (Figure 5.6 B). ANOVA detected neither a significant within-subject main effect of day nor a significant within-subject or between-subject main effect of estrous cycle stage on preference. We also asked whether maxima and minima for ingested dose and preference across the 9-day observation period were significantly associated with estrous cycle stage using X2 tests for independence. They were not. Since all 19 rats were lavaged on the last day of the experiment, we also analyzed drinking data from that day alone (see Supplemental Information, 5.6 below). Despite increased power to detect an effect that day, there was still no significant effect of cycle stage on ingested dose or preference (Figure 5.10).
5.5 DISCUSSION
In the present study, we had the following goals: (1) determine whether cue-trigger alcohol-appetitive states in female rats resulted from repeated alcohol exposure alone or associative learning; (2) determine whether vaginal lavage can affect free-choice alcohol drinking and preference; and (3) evaluate the influence of the estrous cycle on free-choice alcohol drinking and preference.
151 5.5.1 Pre-conditioning free-choice alcohol drinking & preference
As in studies by Morales, McGinnis, & McCool (2015) and Butler and colleagues (2014), adult female rats drank just as much alcohol at the start as at the end of the 5-week pre-conditioning homecage drinking period in the present study (Figure 5.1 A). Unlike in those studies, our female rats appeared to lose their initial aversion to the taste of unsweetened alcohol across the 5-week access period (Figure 5.1 B). This minor discrepancy is most likely attributable to our use of a lower alcohol concentration in the drinking solution (10-15% alcohol v/v in tap water in our study compared to 20% alcohol v/v in their studies).
5.5.2 Acquisition of alcohol cue reactivity
After acquisition of voluntary drinking, we tested for alcohol-associative learning. The only difference between the two groups (Paired and Unpaired) was the presence of a positive contingency between houselight illumination (CS) and alcohol access only in group Paired. In both groups, rats learned to react to sipper presentation with rapid initiation of vigorous consummatory licking (Figure 5.3 A-B). Rats in both groups ingested similar doses of alcohol across conditioning (Figure 5.3 C), and experienced similar blood alcohol levels (Figure 5.4; for an extended discussion of blood alcohol levels in this paradigm, see: Cofresí et al., 2018). During the 5-min pre-session periods, both groups moved around more in the stimulus-rich than stimulus-poor side of the conditioning chamber (Figure 5.11 A) and made a similar number of sipper site contacts (Figure 5.11 B). However, only rats in group Paired acquired houselight illumination-elicited anticipatory sipper site approach and contact behavior (Figure 5.2 A-B). This is strong behavioral evidence that cue-triggered alcohol-appetitive (seeking) states arise from alcohol-associative learning and not repeated alcohol exposure alone. Additionally, it
152 confirms that associative learning about antecedent conditional stimuli for alcohol access is not restricted to males (Chapter 3). Despite equivalent alcohol exposure, rats in group Unpaired did not develop cue- triggered alcohol-directed behavior. However, we did observe persistence of orienting during houselight illumination in group Unpaired (Figure 5.12), which may indicate either conditioning of this overt attentional response to houselight offset as predictor of alcohol access (Holland, 1980; Delamater & Holland, 2008) or alcohol exposure-induced adaptations in the amygdalar central nucleus circuitry that normally controls conditioning of this response (Han et al., 1997; Lee et al., 2005). We observed the same in male rats (Chapter 3). In conclusion, we found that the alcohol-appetitive state in group Paired reflected associative learning. We could not determine whether the persistent attentional response in group Unpaired reflected associative learning or alcohol exposure-induced sensitization, a non-associative learning process. Our findings underscore the importance of Pavlovian conditioning processes in alcohol self-administration. Multiple stimulus sequences and contingencies are at play in human drinking episodes, which creates the opportunity for a mixture of associative and non-associative learning.
5.5.3 Post-conditioning free-choice alcohol drinking & preference: effects of vaginal lavage
It has been shown not only that repeated vaginal lavage can affect the acute (locomotor) response to experimenter-administered cocaine, but also that rats will show a conditioned place preference to vaginal lavage (Walker et al., 2002), suggesting that it might be rewarding. Alternatively, vaginal lavage may be stressful to female rats (Sharp et al., 2003). Stress is known to affect drug-related behavior in rodents including alcohol
153 drinking (Shaham & Stewart, 1995; Le et al., 2005, Meyer et al., 2013). For these reasons, it was imperative to examine whether vaginal lavage could affect free-choice alcohol drinking and preference. We found that vaginal lavage did not affect daily ingested dose or preference (Figure 5.5 A-B). Results may vary if lavage is performed closer in time to alcohol-related experiences or before drinking is stable. In our study, lavage was done 5.5 hr after each 0.5 hr drinking opportunity, and 18 hr elapsed before the next opportunity. Additionally, drinking was established long before rats were subjected to the procedure. One recent study suggests that lavage may be performed immediately after drinking opportunities before drinking is stable without affecting ingested dose and preference (Priddy et al., 2017). More replications of this null finding are warranted before it can be accepted as a true negative.
5.5.4 Post-conditioning free-choice alcohol drinking & preference: effects of the estrous cycle
Female rats are known to exhibit greater free-choice alcohol drinking and preference than males (Lancaster & Spiegel, 1992; Juárez & Barrios de Tomasi, 1999). Unlike males, females are subject to cyclic fluctuations in gonadal hormone levels (Goldman, Murr, & Cooper, 2007), and these may produce brief periods where taste reactivity is altered or alcohol’s reinforcing properties are enhanced (Roberts et al., 1998; Ford, Eldridge, & Samson, 2002). However, when we tested for an effect of estrous cycle stage (diestrus, proestrus, estrus, metestrus) on free-choice alcohol drinking and preference, we found little to no effect (Figure 5.6 A-B). Thus, once established, free- choice alcohol drinking and preference in female rats may be controlled more strongly by factors other than the estrous cycle.
154 Our findings do not mean, however, that the estrous cycle has zero influence on alcohol-related behavior. Torres and colleagues (2014) found that alcohol-related place learning in adult female rats required the estrous cycle, but that cycle stage had no effect on expression of that learning. To the extent that place learning is form of cue learning, we might assume that conditioning of alcohol cue reactivity may require the estrous cycle, but that expression of cue reactivity may be relatively unaffected by cycle stage. However, relapse-like expression of alcohol and drug cue-reactivity by female rats has been shown to be sensitive to gonadal hormones and their metabolites (Roberts et al., 1989; Kippin et al., 2005; Fuchs et al., 2005; Feltenstein, Henderson, & See, 2011; Anker & Carroll, 2010; Bertholomey, Nagarajan, & Torregrossa, 2016; but see Randall, Stewart, & Besheer, 2017). Thus, a more thorough investigation of alcohol-related behavior in freely-cycling female rats is warranted.
5.5.5 Conclusion
In the present study, we showed that alcohol-related behavioral reactivity in adult female rats is not merely due to repeated alcohol exposure, but rather due to learning about alcohol-associated cues. Using the same rats, we found no effect of vaginal lavage on ingested dose or preference relative to no additional handling in a free-choice limited- access paradigm. Vaginal lavage allowed us to see that the estrous cycle plays at best a minor role in determining established (maintenance-phase) free-choice alcohol drinking and preference in female rats.
155 5.6 SUPPLEMENTAL INFORMATION
5.6.1 Free-choice ethanol drinking and preference in the homecage after ethanol cue conditioning
Paired and Unpaired group rats drank similarly in the post-conditioning phase. Ingested ethanol doses and ethanol solution preference varied across the first 8 limited access (30 min) daily homecage sessions (session main effects: F7, 119≥4.10, p<0.01), but not in a meaningful way (Figure 5.7). Additionally, the pattern across sessions and the overall level were independent of former conditioning arrangement (group main effect and group x session interaction: NS; Figure 5.7). All rats were offered 15E for these homecage sessions, so we also tested for any effect of their former (cue conditioning phase) drinking solution (10E/15E). Rats that drank 10E during the conditioning phase did not drink or prefer 15E any less than rats that drank 15E during the cue conditioning phase (solution main effects and solution x session interactions: NS). Rats that subsequently underwent vaginal lavage (6 hr after each session) exhibited day-by-day fluctuations in dose and preference level that did not co-vary with estrous cycle stage (Figure 5.8). Rats that did not undergo vaginal lavage (except 6 hr after the last session) exhibited similar day-by-day fluctuations in dose and preference level (Figure 5.9). On the last day of the lavage experiment, we chose to lavage all 19 rats (including those formerly in the control group) in order to have greater power to detect any possible between-subject effect of estrous cycle stage on drinking. Linear regression analysis of dose and preference data from this day did not detect significant linear, quadratic, or cubic trends across the levels of cycle stage (beta t-tests and overall model F-test: p>0.10, NS, Figure 5.10 A-B).
156 5.6.2 Acquisition of similar pre-session alcohol-directed behavior in Paired and Unpaired
Overall, Paired and Unpaired rats exhibited similar levels of locomotion (measured by infrared photo-beam breaks) in the conditioning chamber during the 5 min pre- conditioning session wait period (ambient ethanol odor present, before fan onset) (F1, 15<1, NS; Figure 5.11 A, left and right panels). There was no significant within-subject change in pre-session locomotion across sessions (group x session interaction: F11, 345<1, NS; session main effect: F11, 345<1, NS; Figure 5.11 A, left and right panels). Collapsing session, there was a statistically significant within-subject effect of chamber side such that rats moved more in the stimulus rich side (where the houselight fixture and hole in the wall for sipper presentation are located; side main effect: F1, 345=111.25, p<0.001; Figure 5.11 A, left versus right panel). This within-subject bias toward locomotion in the stimulus rich side exhibited some between-subject variation due to group, but it was not statistically significant (group x side interaction effect: F1, 345=3.00, p=0.08). Neither the within-subject effect of chamber side nor its interaction with the between-subject effect of group varied as a function of session (F<1, NS). Similar results were obtained when we analyzed sipper site contacts (i.e., forepaw contact with the faceplate around the sipper insertion hole) during the pre-session wait period. Paired and Unpaired rats exhibited a similar amount of contact overall (F1, 15≤1.6, NS; Figure 5.11 B). Unlike with the measure of general locomotion/chamber side bias, there was a consistent increase in pre-session sipper site contacts across sessions in both groups (group x session interaction: F11, 165<1.5, NS; session main effect: F11, 165=2.22, p<0.02; Figure 5.11 B). Collapsing group, rats (n=17) made 2 times as many pre-session sipper site contacts in session 12 (50 ± 16) than session 1 (25 ± 5).
157 5.6.3 Total v. partial habituation of orienting reaction to houselight cue in Paired v. Unpaired
Within-subjects, the frequency of orienting to houselight illumination differed by trial phase (main effect: F4, 60=6.36, p<0.001) and decreased across sessions (main effect:
F11, 165=11.75, p<0.001; trial phase x session interaction: F22, 660=2.29, NS). Paired and Unpaired rats showed similar within-subject patterns (group x trial phase, group x session, group x trial phase x session interactions: F≤1.8, NS). However, Paired and Unpaired groups differed in overall orienting frequency (main effect: F1, 15=39.18, p<0.001). As can be seen in Figure 5.12, orienting was almost totally habituated in group Paired, but persisted somewhat in group Unpaired, especially during the last quarter of houselight illumination (CS bin 4).
158 5.7 FIGURES
A. Pre-Conditioning Ingested Doses
Paired (n=10) 8 Unpaired (n=7) 6 4 2 Ethanol (g/kg) Ethanol 0 1 3 5 7 9 11 13 15 Session
B. Pre-Conditioning Preference 100 Paired (n=10) Unpaired (n=7) 75 50 25 (% Total Fluid) Total (% Ethanol Solution Ethanol 0 1 3 5 7 9 11 13 15 Session
Figure 5.1. Initiation of free-choice ethanol drinking.
Mean±sem ethanol doses (A) and preference (B) across the 15 pre-conditioning homecage two-bottle choice sessions (10-15E v. water for 24-hr on MWF across 5 weeks) shown for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively.
159 A. Sipper Site Approach
preCS bin CS bin 1 CS bin 2 4 Paired (n=10) 3 Unpaired (n=7) 2
Approach 1 0 1357911 Session
B. Sipper Site Contact
preCS bin CS bin 1 CS bin 2 5 4 Paired (n=10) 3 Unpaired (n=7) 2
Contacts 1 0 1357911 Session
Figure 5.2. Cue-conditioned appetitive response acquisition.
Mean±sem level of sipper site approach (A) and contacts (B) paneled by trial phase (preCS bin: 5 s bin before houselight onset; CS bins 1-2: 1st and 2nd 5 s bin of illumination) shown across conditioning sessions (8 trials/session, 1 session/day, 12 consecutive days) for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively. Approach data (maximum response level was 4) were derived from offline manual videoscoring. Contact data were collected online using a modified lickometer.
160 A. Drinking Start Speed 10 8 6 4 Paired (n=10)
Latency (s) Latency 2 Unpaired (n=6) 0 1357911 Session B. Drinking Bout Size
60 Paired (n=10) Unpaired (n=6) 40
Licks 20
0 1357911 Session C. Ingested Doses
1.00 Paired (n=10) 0.75 Unpaired (n=7) 0.50 0.25 Ethanol (g/kg) Ethanol 0.00 1357911 Session
Figure 5.3. Consummatory response across appetitive cue-conditioning.
Mean±sem (A) latency to start licking and (B) number of licks per trial on average across trials per session shown across conditioning sessions (8 trials/session, 1 session/day, 12 consecutive days) for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=6 out of 7 due to equipment malfunction), respectively. C: Ingested dose (g/kg) per session shown across conditioning sessions in all the animals. Horizontal line shows a priori inclusion criterion (dose ≥0.30 g/kg/session across sessions 10-12).
161
Ethanol in Whole Blood v. Ingested Dose 60 Paired (n=10)
40 Unpaired (n=7)
20 Ethanol (mg/dL) Ethanol
0 0.00.25 0.50 0.75 1.0 1.25 Ethanol (g/kg)
Figure 5.4. Ethanol in blood after a conditioning session.
Relationship between blood ethanol concentrations detected after the end of a conditioning session (8 10-s drinking opportunities spaced ≈4-min apart) and ingested ethanol doses for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively. Regression line and 95% confidence limits shown by solid line and shaded area, respectively.
162 A. No Lav. Effect on Dose 1.00
0.75
0.50
0.25 Control (n=9) Ethanol (g/kg) Ethanol Lavaged (n=10) 0.00 13572468 Session
B. No Lav. Effect on Preference 100
75
50
25 Control (n=9) (% Total Fluid) Total (%
Ethanol Solution Ethanol Lavaged (n=10) 0 13572468 Session
Figure 5.5. No effect of vaginal lavage handling on established limited access free-choice ethanol drinking.
Mean±sem ethanol doses (A) and preference (B) across the second 8 post-conditioning homecage two-bottle choice sessions (15E v. water, 1 session/day, 30-min session) shown for adult, female Long-Evans rats. Pink squares and green circles represent group Lavaged (5.5 hr after every session; n=10) and Control (no extra handling; n=9), respectively. Groups were matched on all prior drinking.
163 A. No Estrous Cycle Effect on Dose 1.00
0.75
0.50
0.25 Ethanol (g/kg) Ethanol 0.00 PEMD Estrous Cycle Stage
B. No Estrous Cycle Effect on Preference 100
75
50 (% Total Fluid) Total (%
Ethanol Solution Ethanol 25
0 PEMD Estrous Cycle Stage
Figure 5.6. No effect of estrous cycle on established limited access free-choice drinking.
Mean±sem ethanol doses (A) and preference (B) in post-conditioning homecage two-bottle choice sessions (15E v. water, 1 session/day, 30-min session) across the estrous cycle (stage: P=proestrus, E=estrus, M=metestrus, D=diestrus; determined 5.5 hr after the session) for adult, female Long-Evans rats (n=9 out of 10 lavaged rats). 164
A. Post-Conditioning Ingested Doses
Paired (n=10) 1.25 Unpaired (n=7) 1.00 0.75 0.50 0.25 Ethanol (g/kg) Ethanol 0.00 12345678 Session
B. Post-Conditioning Preference
100
75
50
25 Paired (n=10) (% Total Fluid) Total (% Ethanol Solution Ethanol Unpaired (n=7) 0 12345678 Session
Figure 5.7. Re-initiation of free-choice ethanol drinking under limited access conditions.
Mean±sem ethanol doses (A) and preference (B) across the first 8 post-conditioning homecage two-bottle choice sessions (15E v. water, 1 session/day, 30-min session) shown for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively.
165 Estrous Cycle & Ethanol Drinking - Lavaged Rats Rat ID Cycle Stage Cycle Ethanol(g/kg) (% Total Fluid) Total (% EthanolSolution
35179
Figure 5.8. Estrous cycle and ethanol drinking in lavaged rats.
Top row: Estrous cycle stage (D=Diestrus, M=Metestrus, E=Estrus, P=Proestrus) in adult, female Long-Evans rats that underwent daily vaginal lavage 5.5 hr after two-bottle choice sessions (15E v. water, 1 session/day, 30-min session). Midde row: Ingested dose (mean±sem g/kg) per session per day. Bottom row: Ethanol solution intake as mean±sem % total fluid per session per day.
166 Estrous Cycle & Ethanol Drinking - Non-Lavaged Rats Rat ID
?
35179
Figure 5.9. Estrous cycle and ethanol drinking in non-lavaged rats.
Top row: Estrous cycle stage (?=Unknown, M=Metestrus, E=Estrus, P=Proestrus) in adult, female Long-Evans rats that did not undergo daily vaginal lavage 5.5 hr after two-bottle choice sessions (15E v. water, 1 session/day, 30-min session) except on the last day. Midde row: Ingested dose (mean±sem g/kg) per session per day. Bottom row: Ethanol solution intake as mean±sem % total fluid per session per day.
167 A. Ingested Dose and Estrous Cycle Stage
1.00
0.75
0.50
0.25 Ethanol (g/kg) Ethanol 0.00 DPEM Estrous Cycle Stage
B. Preference and Estrous Cycle Stage
100
75
50
25 (% Total Fluid) Total (% Ethanol Solution Ethanol 0 DPEM Estrous Cycle Stage
Figure 5.10. No estrous cycle effect on the last day of free-choice drinking.
Ethanol doses (A) and preference (B) in the final post-conditioning homecage two-bottle choice session (15E v. water, 30-min) shown for all (n=19) adult, female Long-Evans rats as a function of estrous cycle stage determined 5.5 hr after the session (stage: D=diestrus, P=proestrus, E=estrus, M=metestrus). Individual rats represented by small black-filled circles. Mean±sem across rats found in each stage represented by larger gray-filled triangles.
168 A. Pre-session Locomotion
Stimulus Poor Zone Stimulus Rich Zone 80 Paired (n=10) 60 Unpaired (n=7) 40 20 0 Beam Breaks/5 min Breaks/5 Beam 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112 Session
B. Pre-Session Sipper Site Contact
80 Paired (n=10) Unpaired (n=7) 60
40
Contacts/5 min Contacts/5 20
0 1 2 3 4 5 6 7 8 9 10 11 12 Session
Figure 5.11. Pre-session waiting period behavior across conditioning.
A: Locomotor behavior measured as mean±sem infrared beam breaks in the stimulus poor zone (left panel) versus stimulus rich zone (houselight fixture, hole in the wall for sipper presentation) (right panel) of the conditioning chamber during the 5-min period before exhaust fan onset and conditioning session start shown across sessions for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively. B: Mean±sem forepaw contact with the metal plate around the sipper insertion hole (measured using a modified lickometer circuit) during the same 5-min period shown across sessions for the same rats. Ambient ethanol odor was always present.
169 Overt Attentional Response to Houselight Illumination
2 preCS bin CS bin 1 CS bin 2 CS bin 3 CS bin 4 Paired (n=10) Unpaired (n=7) 1
Orienting 0 1357911 Session
Figure 5.12. Orienting response to houselight illumination across conditioning.
Mean±sem level of orienting paneled by trial phase (preCS bin: 5 s bin before houselight onset; CS bins 1-4: 5 s bins across the 20 s period of illumination) shown across conditioning sessions (8 trials/session, 1 session/day, 12 consecutive days) for adult, female Long-Evans rats. Black and white triangles represent group Paired (n=10) and Unpaired (n=7), respectively. Orienting data (maximum response level was 4) were derived from offline manual videoscoring.
170 Chapter 6. Conclusion
In this chapter, I conclude by summarizing key findings across my experiments, acknowledging open questions relevant to the potential, translation, and application of the memory updating strategy to alcohol cue exposure therapy, and pointing potential ways forward.
6.1 DEMONSTRATED POSITIVE EFFECT OF RETRIEVAL + EXTINCTION IN THE REINSTATEMENT MODEL OF RELAPSE
In Chapter 2, I showed that conducting extinction of an alcohol-predictive cue during reconsolidation of memory for that cue prevented alcohol odor-induced reinstatement of reactivity to that cue otherwise observed after standard extinction treatment in a preclinical rat model of human alcohol cue reactivity that I developed. The ability of this memory retrieval + extinction approach to prevent reinstatement of the cue- elicited appetitive response also allowed it to decrease the likelihood of subsequent sipper licking, a built-in Pavlovian-to-instrumental (PIT)-like effect in the model.
6.1.1 Need to replicate this effect in other models of relapse
My findings with alcohol cue memory retrieval + extinction are promising, but need to be replicated in principle in other models of relapse. This can be done using the experimental rodent model of human alcohol cue reactivity that I developed or similarly rigorous paradigms.
6.1.1.1 Stress-induced reinstatement
In Chapter 1, I noted that stress precipitates lapse and promotes relapse in people with alcohol use disorder (AUD), and these are mediated by craving (Bonnie, Law, Daglish, et al., 2016). In turn, craving is most easily elicited by alcohol-associated cues.
171 Additionally, stress can prompt people to behave based on “habit” (Schwabe & Wolf, 2011). For these reasons, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent stress-induced reinstatement of extinguished cue reactivity. In rodent models, stress-induced reinstatement or stress-potentiated cue-induced reinstatement can be tested using acute physical stress (e.g., foot shock) or acute pharmacological stress (e.g., injection of the alpha-2 adrenergic antagonist, yohimbine) (e.g., Lê, Harding, Juzytsch, et al., 2005; Liu & Weiss, 2002, 2003).
6.1.1.2 Context-induced reinstatement
In Chapter 1, I noted that extinction, one of the major forms of response-inhibitory learning taking place in cue exposure therapy (CET), is highly context-dependent (Bouton, 2004; Bouton, Winterbauer, & Todd, 2012). When people with AUD return to alcohol- associated contexts (e.g., the places at which they drank most frequently), the original reactions to cues are reinstated as if extinction had not occurred. In part, this may be due to potentiated reactivity to alcohol-associated cues in alcohol-associated contexts (Remedios, Woods, Tardif, et al., 2014). For these reasons, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent context-induced reinstatement of extinguished cue reactivity. In rodent models, context-induced reinstatement or “renewal” involves training alcohol-associated cues in one environment, extinguishing those alcohol-associated cues in a different environment, and testing in the original self-administration environment (e.g., Zironi, Burattini, Aicardi, et al., 2006).
6.1.1.3 Priming-induced reinstatement
People with AUD experience especially intense urges to drink more alcohol after ingesting 1-2 standard drinks (Ludwig, Wilker, & Stark, 1974). In fact, even among people
172 without AUD, those with riskier/heavier/hazardous drinking patterns are more likely to activate positive alcohol use outcome expectancies during the ascending limb (Dunn & Earleywine, 2001). The reason for this may be that a small amount of alcohol on the brain “primes” the brain’s motivational systems (de Wit, 1996), including those involved in expressing memory for alcohol-predictive conditional stimuli. For these reasons, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent alcohol priming-induced reinstatement of extinguished cue reactivity. In rodent models, priming-induced reinstatement paradigms involve testing under extinction conditions after injection of a fixed amount of drug (e.g., Lê, Quan, Juzytch, & Fletcher, 1998).
6.1.1.4 Long-term spontaneous recovery
People with AUD sometimes find themselves reacting to alcohol-associated cues in old ways simply as a function of the passage of time. Additionally, there is the idea that alcohol craving can “incubate” over time (Li, Wu, Xin, et al., 2015). In Chapter 2, I showed that conducting extinction of an alcohol-predictive cue during reconsolidation of memory for that cue prevented short-term spontaneous recovery of reactivity to that cue otherwise observed after standard extinction treatment in my preclinical rat model of human alcohol cue reactivity. The ability of this memory retrieval + extinction approach to prevent short- term spontaneous recovery of the cue-elicited appetitive response also allowed it to decrease the likelihood of subsequent sipper licking, a built-in Pavlovian-to-instrumental (PIT)-like effect in the model. However, spontaneous recovery models of relapse often test spontaneous recovery after much longer intervals than I did (after weeks to months of “rest” instead of only one day). People with AUD often experience long intervals between treatments or between booster sessions, allowing time for natural forgetting of recently
173 learned response-inhibiting memories. For these reasons, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent long-term spontaneous recovery of extinguished cue reactivity. In rodent models, long-term spontaneous recovery paradigms involve testing under extinction conditions after various lengths of “rest” from treatment (e.g., Robbins, 1990).
6.1.1.5 Reconditioning rate test
One of the classic ways of demonstrating that extinction is not un-learning or de- conditioning involves measuring how quickly an extinguished reaction is re-acquired or re-conditioned (Bouton et al., 2004). Ideally, CET would prevent the re-acquisition of problematic behaviors. It may be too much to ask that any extinction-based treatment alone prevent reconditioning because these treatments do not alter the reinforcing properties of alcohol itself. However, it would be counterproductive to facilitate reconditioning, which is a valid concern with any memory manipulation-based treatment. For this reason, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent or retard reconditioning of reactions to treated cues. In rodent models, this is as simple as training an alcohol-predictive cue, extinguishing that cue (non-reinforcement), and then retraining that cue. Rodents given standard extinction treatment or no intervening treatment can be used as control subjects. Alternatively, the reconditioning rate in retrieval + extinction treated rats can be compared to age-matched conditioning-naïve (alcohol- experienced) rats being conditioned at the same time.
6.1.1.6 Post-treatment Pavlovian to instrumental transfer (PIT) test
Conditioned reactivity to alcohol-associated cues is believed to invigorate alcohol use and influence alcohol use-related decisions in the moment through an interaction
174 known as Pavlovian to instrumental transfer (PIT) (Tomie, 1996; Holmes, Marchant, & Coutureau, 2010). The ultimate goal of alcohol CET is to reduce the power of alcohol- associated cues to drive alcohol use. In Chapter 2, I found that the memory retrieval + extinction approach attenuated not only the cue-elicited appetitive response, but also the likelihood of subsequent sipper licking, a built-in PIT-like effect in my model. However, it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent PIT relative to standard extinction of the same cues in the classic paradigm, which involves separately trained Pavlovian and instrumental responses.
6.1.2 Need to test the retrieval + extinction effect for other alcohol-related memories
In Chapter 4, I confirmed that alcohol cue reactivity in my preclinical rodent model stems from alcohol-associative learning, which is believed to be the basis for alcohol cue reactivity in humans. I also obtained evidence supporting the idea that expression and/or maintenance of memory for the alcohol-associated cue in my model may involve at least the insular cortex. In Chapter 5, I demonstrated that alcohol-associated cue reactivity in my preclinical rat model is not a sex-specific phenomenon, which is important because in humans, both sexes exhibit maladaptive alcohol cue reactivity. Thus, the preclinical rodent model of human alcohol cue reactivity that I developed recapitulates many features of the human condition or endophenotype fairly well. However, it does not recapitulate its entirety. For this reason, it remains necessary to either adapt my model in ways that allow it to model alcohol-related memory of various ages, strength, and types or to develop entirely new rodent models of alcohol-related memory for specific memory ages, strength, and types that are just as, if not, more valid and rigorous than mine.
175 6.1.2.1 Over-trained cue memory and/or longer histories of drinking
Different brain regions may come to dominate expression and/or maintenance of memory for the alcohol-associated cues after over-training. People with AUD have much longer histories of drinking heavily/hazardously. Plus, as I noted in Chapter 1, greater cue- elicited activation in specific brain areas such as the insula and dorsal striatum may index AUD severity. In rodent models, reflex-like alcohol-directed behavior appears to depend on the dorsal striatum (Corbit, Nie, & Janak, 2012). The same rodents exhibit stronger PIT effects (Corbit & Janak, 2016a). Additionally, overtraining a cue causes shifts in the form of cue-conditioned reactions that may facilitate excessive engagement with alcohol self- administration devices (Srey, Maddux, & Chaudhri, 2015).
6.1.2.1.2 Cue memory in context of physical dependence or models of severe AUD
Different brain regions may come to dominate expression and/or maintenance of memory for the alcohol-associated cues after the development of physical dependence on alcohol and/or more severe forms of AUD. Koob’s theory of addiction holds that this stage is accompanied by a shift from positive to negative reinforcement of behavioral patterns. In this situation, cues previously associated with only alcohol’s rewarding properties may also become associated with relief from acute withdrawal. Alternatively, the brain regions involved may be compromised due to alcohol-related neurotoxicity. If the former case is true, then care must be taken to teach rodents that alcohol self- administration cures mild-to-moderate alcohol withdrawal symptoms. Studies in which the former is not done may be asking and answering a slightly different question (e.g., are alcohol-related memory processes enhanced/impaired in the alcohol-dependent brain) but may still serve as excellent models for alcohol-related neurocognitive impairment seen in people with severe AUD that has consequences for treatment (Loeber, Duka, Welzel, et
176 al., 2010; Bates, Bowden, & Barry, 2002). In either case (negative reinforcement or neurocognitive impairment), it remains important to test whether retrieval + extinction of alcohol-associated cues will prevent or reduce relapse in a model of severe AUD. As such, the basic (pre-extinction) alcohol cue reactivity model should be implemented in rodents made physically dependent on alcohol via an alcohol-enriched liquid diet or chronic intermittent alcohol vapor exposure paradigm (e.g., Macey, Schulteis, Heinrichs, & Koob, 1996; Rogers, Wiener, & Bloom, 1979).
6.2 POST-INGESTIVE EFFECTS ARE REQUIRED FOR CERTAIN FORMS OF ALCOHOL CUE REACTIVITY
In Chapters 3-4, I showed that rats drinking below a certain dose level (0.30 g/kg/0.5 hr) did not develop any alcohol cue reactivity over the course of chronic oral alcohol self-administration. The age, body weight, and sex of the rodent and temporal parameters of the drinking opportunity may all determine whether orally self-administered alcohol accumulates in blood in sufficient quantities to serve as a stimulus for learning. In other words, pharmacokinetic considerations are important to alcohol-related memory formation. In fact, there is additional evidence from human subjects and non-human animal models alike for the role of pharmacokinetics in the acquisition of alcohol cue reactivity. The strongest evidence from non-human animals for the role of pharmacokinetics in alcohol-related memory formation comes from the fact that the development of conditioned place preference versus aversion in rodents depends on the timing of place experience (viz., contextual cue presentation) relative to the timecourse of blood alcohol concentration (BAC). Places experienced before and during asymptotic ascent to intoxicating BAC tend to acquire the ability to elicit aversion reactions whereas places experienced only after ascent to the same BAC may acquire the ability to elicit preference
177 reactions (e.g., Cunningham, Clemans & Fidler, 2002). Additional evidence from non- human animals for the role of pharmacokinetics in alcohol-related memory formation comes from the fact that places experienced before and during asymptotic ascent to much lower BAC may be able to acquire preference reactions, but only with extensive conditioning (e.g., Bozarth, 1990). Additional evidence for the role of pharmacokinetics in alcohol-related memory formation also comes from controlled conditioning studies in human subjects without alcohol use disorder where both low (≈0.2 g/kg) and moderate (≈0.5 g/kg) doses ingested relatively rapidly (within 20 min) are able to promote conditioning of appetitive reactions (Field & Duka, 2002; Staiger & White, 1988), but only moderate doses may be able to promote conditioning of compensatory reactions (Dafters & Anderson, 1982; Glautier, Drummond, & Remington, 1994; Staiger & White, 1988). Evidence for the role of pharmacokinetics also comes indirectly from the ability of the same alcohol dose ingested relatively rapidly (within 20 min) to enhance people’s memory for stimuli presented before ascent to intoxicating blood alcohol concentration but to impair people’s memory for stimuli presented after ascent (Parker, Birnbaun, Weingartner, et al., 1980; Parker, Morihisa, Wyatt, et al., 1981; Ray & Bates, 2006; Weafer, Gallo, & de Wit, 2016a,b)— unless the ascent occurs rapidly and immediately after stimulus presentation during initial encoding instead of the memory consolidation phase (Weafer, Gallo, & de Wit, 2016a,b). Given that positive affective states (high or low in arousal depending on social context) often precede alcohol’s post-ingestive pharmacology in humans, it is possible that alcohol’s pharmacological impact on memory formation may facilitate the development, and stamping in, of alcohol cue-elicited “wanting” reactions over a person’s drinking history. In line with this idea, humans without AUD who drink hazardously or heavily appear to have more accessible positive alcohol use outcome expectancies (Hartzler & 178 Fromme, 2003) and may be more likely to activate both implicit and explicit positive outcome expectancies during the initial rise in blood alcohol concentration (Dunn & Earleywine, 2001).
6.3. RESISTANCE OF ALCOHOL CUE REACTIVITY TO EXTINCTION
Alcohol cue reactivity in people with AUD is notoriously treatment-resistant and susceptible to post-treatment return. In Chapters 2-3, I showed that alcohol cue reactivity in my preclinical rodent model resists even extensive treatment with standard extinction and recovers spontaneously after even a single day break in treatment. It is possible that the reason why alcohol cue reactivity in my model resists standard extinction treatment is that my procedure produces not only learning of the houselight, but also the sipper presentation as alcohol-associated cues, in which case, the way I chose to conduct treatment (houselight + dry sipper, no alcohol) requires two-phase extinction: first, extinction of the sipper as an alcohol cue, then extinction of the houselight as an alcohol/sipper cue. The idea is that sipper presentation, as a stimulus, acquired conditioned reinforcing properties as a consequence of its direct association with alcohol ingestion across training (Tomie, 1996) and thus, it is able to reinforce houselight-elicited sipper site approach even in the absence of subsequent alcohol ingestion for at least some days/number of trials. If it does, then houselight cue-elicited sipper site approach should decay more quickly when houselight presentation is not followed by sipper presentation than when it is. However, this possibility does not invalidate my initial findings with the retrieval + extinction procedure. In fact, this possibility raises the relevance of my findings given that it implies a hierarchy of interrelated cue-alcohol associations in the same animal. Alcohol and drug
179 use in humans with and without substance use disorders is believed to rely on a similarly complex system of drug-related memories (Hogarth, Balleine, Corbit, & Killcross, 2013).
6.4 NEED TO KNOW MECHANISMS OF RETRIEVAL + EXTINCTION IN ORDER TO OPTIMIZE
A major impediment to optimizing the memory reconsolidation-based approach to CET for maximal benefit in the AUD clinic is that we do not know the behavioral and biological mechanisms by which this treatment works.
6.4.1 Behavioral mechanisms
One way in which the alcohol cue memory retrieval + extinction treatment may work at the behavioral level is by altering attentional processing of the cue. Testing for these behavioral mechanisms is fairly straightforward. In both humans and nonhuman animal models, the level of orienting to the cue can be monitored for changes over the course of treatment. Overt (locomotor) and covert (autonomic) orienting reactions can be measured. Hints that this may be a behavioral mechanism of retrieval + extinction treatment stems from studies of retrieval + extinction treatment of cue-conditioned food “wanting” and cue-conditioned fear reactions in rodents. First, Olshavsky and colleagues (2013a,b) showed that rodents with sign-tracking (cue-directed) phenotypes benefited more from retrieval + extinction of cue-conditioned food “wanting” and cue-conditioned fear reactions than rodents without that phenotype. Secondly, Olshavsky and colleagues (2013a) reported that all rodents whose cue-conditioned food “wanting” reactions were treated with retrieval + extinction exhibited increases in the frequency of overt attentional reactions to the treated cue across extinction and memory testing. Whether this also took place in my study (Chapter 2) remains to be determined.
180 6.4.2 Neurobiological mechanisms
Neither persistent attenuation of alcohol cue reactivity nor altered overt or covert attentional processing of the cue tell us whether the retrieval + extinction treatment worked via reconsolidation-based memory updating. To do so, we must show, ideally, that pharmacological interference with specific memory reconsolidation processes disrupts treatment outcomes. However, the biological processes underlying consolidation of a new memory (e.g., extinction) and reconsolidation of an existing memory are very similar (as noted in Chapter 1), making it difficult to differentiate between reconsolidation-based original memory updating and potentiation of extinction memory formation as mechanisms for the observed anti-relapse effects (Lee, Nader, & Schiller, 2017). As more research into the basic biology of consolidation v. reconsolidation takes place, we may be able to pharmacologically isolate one versus another. For now, however, we can at least show that retrieval + extinction engages the brain differently than standard extinction treatment. This has been done for retrieval + extinction of cue-conditioned fear. Retrieval + extinction treatment of conditioned fear has been shown to involve different post-translational modification of synaptic proteins than standard extinction (Monfils et al., 2009), lead to removal of synaptic proteins involved in maintaining long-term synaptic efficacy (Clem & Huganir, 2010), and to engage different brain networks than standard extinction (Lee, Haberman, Roquet & Monfils, 2016). Similar work should be undertaken to decipher the mechanisms for the anti-relapse effect of alcohol cue retrieval + extinction. The alcohol cue memory reconsolidation literature offers some clues about which brain regions and cellular processes therein may be involved. For example, von der Goltz and colleagues (2009) showed that reconsolidation of alcohol cue memories acquired over the course of oral self-administration requires protein synthesis. Barak and colleagues (2013) showed that reconsolidation of alcohol cue memories acquired over the course of 181 oral self-administration involves the mammalian target of rapamycin (mTOR) and its downstream targets in the amygdala. Schramm, Everitt, & Milton (2016) have shown that adrenergic signaling in the amygdala may also be involved in reconsolidation of alcohol cue memories acquired over the course of oral self-administration. Discovering the neurobiological substrates for the anti-relapse effect of alcohol cue memory retrieval + extinction would give us a way of measuring whether memory updating took place and if so, to what extent, in procedure optimization studies.
6.5 TRANSLATION & CLINICAL APPLICATIONS
Retrieval + extinction has been shown to prevent cue-triggered craving in treatment-seeking people with a heroin use disorder (Xue et al., 2012) and treatment- seeking people with a tobacco use disorder (Germeroth et al., 2017). In the latter application, there was also a harm reduction effect (fewer cigarettes smoked per day), which may have been related to the retrieval + extinction effect on cue-triggered craving. In non-treatment-seeking heavy/hazardously drinking people, retrieval + counterconditioning reduced alcohol cue reactivity in the laboratory and showed promise in reducing harm (viz., decreasing drinking intensity/frequency) outside the laboratory (Das, Lawn, Kamboj, 2015). However, no one has yet translated and tested whether the alcohol cue retrieval + extinction procedure will work in humans with or without alcohol use disorder. If the potential of benefits of adopting this approach to alcohol CET can be demonstrated in the human laboratory, then there would be a stronger basis for further clinical testing.
182 6.5.1 Issues that might come up in studies with human subjects
A major issue in clinical application is the extent to which the treatment provider should be allowed to counsel the person during the retrieval session, retrieval-extinction interval, or extinction session. In order for retrieval + extinction approach to CET work well, interactions between the person and treatment provider may need to be minimized during the CET session. It may be necessary to return to “pure” CET, which is how extinction is done in non-human animal models, and conduct CET and relapse prevention or communication skills training during separate sessions. Another issue concerns people’s cue reactivity in these “pure” CET sessions. Ideally, the person must not try to actively inhibit their reactions to alcohol cues. In doing so, they run to the risk of engaging the prefrontocortical systems involved in standard extinction (viz., new inhibitory learning). Instead, people may need to be advised (before the session starts) to fully experience their alcohol cue-elicited reactions, including craving. That is, they may need to experience autonomic reactivity without resistance. They may need to allow alcohol-related thoughts and feelings bubble up, even if these thoughts & feelings are aversive to them (Smith-Hoerter, Stasiewicz, & Bradizza, 2004). Perhaps the most important practical/parametric issue that needs to be resolved in a human laboratory study is when to administer massed cue extinction relative to the initial cue memory retrieval episode. The existing studies of retrieval + extinction effects in human subjects have used a wide retrieval-to-extinction interval (10 min to 5 hr). However, the human long-term memory reconsolidation window may be different than what was observed in non-human animal models. Both the human and non-human animal model literature relevant to retrieval + extinction suggests that expectancy violation is necessary to initiate the reconsolidation process for many memories, including memory for alcohol cues. This requirement 183 indicates that deception and/or extensive-intensive drug cue exposure (videos, pictures, in vivo) may be necessary. Thus, human laboratory studies may also need to determine how extensive or intensive cue exposure needs to be as well as how large of an expectancy violation is necessary.
6.6 CONCLUSION
Modifying alcohol cue exposure therapy to harness memory reconsolidation remains a promising way to directly decrease the ability of alcohol-associated cues to drive lapses and relapse. This modified approach should continue to be investigated in the human and non-human animal model laboratories.
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