Ance of Adult Rats Exposed to Elevated Levels of Kynurenic Acid During Gestation in A

Home , Methyllycaconitine

Performance of Adult Rats Exposed to Elevated Levels of Kynurenic Acid during Gestation in a

Rodent Target Detection Task: A Translational Model for Studying the Effects of Cognitive

Training

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the

Graduate School of The Ohio State University

David Anthony Phenis

Neuroscience Graduate Program

The Ohio State University

2018

Dissertation Committee

John P. Bruno, Advisor

Julie D. Golomb

Kathryn M. Lenz

Derick H. Lindquist

Copyrighted by

David Anthony Phenis

2018

Abstract

Cognitive deficits in executive functions such as attention and cognitive control form a core symptom cluster in schizophrenia that is most predicative of functional outcomes for patients, such as the ability to return to work. Unfortunately this class of symptoms is poorly treated with currently available neuroleptics and so far adjunctive treatment with potential pro- cognitive compounds has not yielded improvements in global cognition. Not only are alternative treatment strategies necessary, but there is a need for better validated preclinical tasks and animal models. The current work seeks to validate the rodent Target Detection Task (rTDT) and the embryonic kynurenine (EKYN) model as a platform for assessing the efficacy of cognitive training via prior experience in a cognitively demanding task. The central hypothesis guiding the experiments in this dissertation is that gestational elevations of kynurenine will induce a profile of translationally relevant attentional deficits in the rTDT and these deficits can be reversed with cognitive training. The first aim consisted of a validation of the rTDT. It was found that rTDT acquisition follows a stable and repeatable pattern. Additionally, rTDT performance is sensitive to manipulations of stimulus parameters including the reduction of stimulus duration and contrast. These manipulations result in predictable impairments in sensitivity, or the ability to discriminate between target and non-target stimuli. The rTDT was also shown to be sensitive to pharmacological challenges with agents that impair glutamatergic and cholinergic neurotransmission. These neurotransmitter systems are known to be essential for intact

ii attentional processing. The second aim consisted of a validation of the EKYN model. EKYN animals, compared to control animals, showed disruptions of attentional processing and cognitive control. These deficits did not present during task acquisition but emerged upon challenge with task parameters that enhanced cognitive load in either the rTDT or the Maze Set

Shifting task. EKYN animals were vulnerable to reductions in stimulus duration in the rTDT and vulnerable to extradimensional set shifts in the Maze Set Shifting task. The third aim consisted of a proof-of-concept for modeling cognitive training with prior experience in cognitively demanding tasks. To assess the generalization of the effect of cognitive training a fully crossed design was used with task order counterbalanced. EKYN rTDT training rescued deficits in cognitive flexibility in the EKYN animals. Interestingly this protective effect was specific to

EKYN animals who were trained in the full rTDT compared to EKYN animals who were exposed to a simple reward-stimulus pairing. In contrast both EKYN maze trained and maze exposed animals showed a protective effect against the attentional deficits shown by EKYN animals in the rTDT. In conclusion the current work (1) further validates the rTDT as a translationally relevant task that challenges animals in the cognitive domains of attention, cognitive control and perception, (2) further validates the EKYN animal model as a naturalistic neurodevelopmental model that induces deficits in attentional processing and cognitive flexibility similar to the cognitive deficits present in patients with schizophrenia, (3) is the first to show, in a strongly validated animal model of schizophrenia, the efficacy of cognitive training in adulthood to reverse cognitive deficits.

iii

KEYWORDS: rodent target detection task, schizophrenia, embryonic kynurenine, kynurenic acid, cognitive deficits, attentional processes, cognitive control, cognitive remediation therapy, cognitive training, maze set shifting task

Acknowledgments

I would first like to thank my advisor Dr. John Bruno for his fostering of my critical thinking skills and independence. His advice and knowledge were invaluable and constantly challenged me to not only be a better scientist, but a better person. Thank you also to my committee members Julie Golomb, Kathryn Lenz, and Derick Lindquist, whose unique insight helped focus the current work and greatly improved the experimental design. I am grateful for my advisor and committee’s patience and support through this trying experience. I would next like to thank all members of the Bruno lab past and present all of which who helped my development as a scientist. I would like to highlight the contribution of Dr. Valentina Valentini, her unparalleled mastery of techniques was matched only by her teaching ability and always welcoming demeanor. Thank you also to undergraduates Jared Boss and Jackson Schumacher whose contributions always made life a little easier in the lab. Thank you to Dr. Robert Schwarcz and his lab who donated their time and expertise for the measurement of Kynurenic Acid. Thank you to the Lenz lab for the use of their elevated plus maze. Thank you to all members of the

Behavioral Neuroscience department for access to lab resources and feedback throughout this process. I would like to acknowledge the members of ULAR who always played an important role in animal care. I would also like express my gratitude to my parents who have always been supportive. Finally thank you to my wife MJ who has endlessly endured all of the highs and lows of this undertaking, I would have never been able to finish without her. v

Vita

May 2011…………………………B.S. Biochemistry, Case Western Reserve University

Publications

Ghosal, K., Stathopoulos, A., Thomas, D., Phenis, D., Vitek, M. P., & Pimplikar, S. W. (2013). The Apolipoprotein-E-Mimetic COG112 Protects Amyloid Precursor Protein Intracellular Domain-Overexpressing Animals from Alzheimer’s Disease-Like Pathological Features. Neurodegenerative Diseases, 12(1), 51–58. http://doi.org/10.1159/000341299

Pershing, M. L., Phenis, D., Valentini, V., Pocivavsek, A., Lindquist, D. H., Schwarcz, R., & Bruno, J. P. (2016). Prenatal kynurenine exposure in rats: age-dependent changes in NMDA receptor expression and conditioned fear responding. Psychopharmacology, 233(21–22), 3725–3735. http://doi.org/10.1007/s00213-016-4404-9

Fields of Study

Major Field: Neuroscience Graduate Program

Table of Contents

Abstract ...... ii

Vita ...... vi

List of Tables ...... xi

List of Figures ...... xii

Chapter 1. Introduction ...... 1

1.1 Task Selection ...... 2

1.2 Animal Model Selection ...... 4

1.3 Treatment selection ...... 7

Chapter 2. Methods ...... 9

2.1 Animals ...... 9

2.2 Breeding and Kynurenine Supplementation ...... 9

2.3 Weaning and Distribution of Littermates across Experimental Conditions ...... 10

2.4 Kynurenic acid (KYNA) in PFC tissue ...... 10

2.5 Water deprivation...... 11

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2.6 Rodent Target Detection Task (rTDT) ...... 11

2.7 Maze Set Shifting Task ...... 13

Chapter 3: Parmetric and Pharmcological Validation of the rTDT ...... 16

3.1 Introduction ...... 16

3.1.1 Attentional Processes ...... 16

3.1.2 Preclinical Tasks of Attention ...... 17

3.1.3 Rationale ...... 19

3.2 Methods...... 20

3.2.1 Intact Parametric Challenge ...... 20

3.2.2 Intact Pharmacological Challenge ...... 20

3.2.3 Statistical Analyses ...... 21

3.3 Results ...... 22

3.3.1 Intact Animal Performance during rTDT Acquisition ...... 22

3.3.2 Increasing Cognitive Load in Intact Rats...... 23

3.3.3 Pharmacological Challenges in Intact Rats...... 25

3.4 Discussion ...... 28

Chapter 4: Effects of Elevated Gestational Kynurenine on Attention and Cognitive Control ...... 32

4.1 Introduction ...... 32

4.1.1 Consequences of Elevated Embryonic Kynurenine ...... 32

viii

4.1.2 Rationale ...... 33

4.2 Methods...... 34

4.2.1 EKYN rTDT Parametric Challenge ...... 34

4.2.2 Statistical Analyses ...... 34

4.3 Results ...... 35

4.3.1 Acquisition of rTDT task in ECON Controls and EKYN Animals Exposed to Prenatal

Kynurenine ...... 35

4.3.2 The Effects of Increasing Cognitive Load on Performance of ECON and EKYN

Animals in the rTDT Task ...... 36

4.3.3 Performance of ECON and EKYN Animals in the Plus Maze Set Shifting Task ...... 37

4.3.4 Levels of KYNA in Prefrontal Tissue Homogenates from Adult Littermate Controls 39

4.4 Discussion ...... 39

Chapter 5: Efficacy of Cognitive Training in Reversing Attention and Cognitive Control Deficits

...... 45

5.1. Introduction ...... 45

5.1.1 Selection of Tasks to Model the Effects of Cognitive Training ...... 45

5.1.2 Rationale ...... 46

5.2 Methods...... 46

5.2.1 Cognitive Training Full Cross Experimental Design...... 46

5.2.2 Statistical Analyses ...... 47

5.3 Results ...... 48

,5.3.1 Effects of Prior Cognitive Training in the Maze Set Shifting Task on the -Acquisition

of the rTDT Task in ECON and EKYN Animals ...... 49

5.3.2 Effects of Prior Cognitive Training in the Maze Set Shifting Task on Performance in

the rTDT under Conditions of Enhanced Cognitive Load in ECON and EKYN Animals .. 50

5.3.3 Effects of Prior Cognitive Training in the rTDT on Performance in the Plus Maze Set

Shifting Task in ECON and EKYN Animals ...... 51

5.4 Discussion ...... 53

Chapter 6: General Discussion...... 56

6.1 Discussion ...... 56

6.2 Translational Relevance of EKYN model and the rTDT ...... 57

6.3 Mechanism of Cognitive Training ...... 60

6.4 Future Directions ...... 62

6.5 Conclusions ...... 65

Bibliography ...... 66

APPENDIX A: TABLES AND FIGURES ...... 85

List of Tables

Table 1. Summary of Tasks Associated with Cognitive Domains identified by CNTRICS and

MATRICS ...... 86

Table 2. Distribution of Offspring of ECON and EKYN DAMs to Experimental Aims ...... 87

Table 3. Summary of Chapter 3 (Aim 1) Results: Validation of the rTDT ...... 88

Table 4. Summary of Parametric Challenge Parameters ...... 90

Table 5. Summary of Chapter 4 (Aim 2) Behavior Results: Effects of elevating Kynurenine during Gestation ...... 91

Table 6. Summary of Chapter 5 (Aim 3) Behavior Results: Effects of Cognitive Training ...... 92

List of Figures

Figure 1. Schematic of Disruptions of the Kynurenine Pathway (KP) of Tryptophan Degradation in Patients with Schizophrenia ...... 93

Figure 2. Summary of Experimental Design ...... 94

Figure 3. Schematic of Stage 4 of Rodent Target Detect Task (rTDT) and Signal Detection

Theory Measures ...... 95

Figure 4. Schematic of Maze Set Shifting Task ...... 98

Figure 5. Acquisition of Stage 3 of the rTDT in Intact Animals ...... 100

Figure 6. Acquisition of Stage 4 of the rTDT in Intact Animals ...... 101

Figure 7. Effects of Reduced Stimulus Duration on the Performance of Intact Animals in the rTDT ...... 102

Figure 8. Effects of Reduced Stimulus Contrast on the Performance of Intact Animals in the rTDT ...... 104

Figure 9. Effects of acute MK801 on the Performance of Intact Animals in the rTDT ...... 106

Figure 10. Effects of acute Mecamylamine on the Performance of Intact Animals in the rTDT108

Figure 11. Effects of acute Scopolamine on the Performance of Intact Animals in the rTDT ... 110

Figure 12. Acquisition of Stage 3 of the rTDT in EKYN and ECON Animals ...... 111

Figure 13. Acquisition of Stage 4 of the rTDT in ECON and EKYN Animals ...... 112

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Figure 14. Effects of Reduced Stimulus Duration on Performance of ECON and EKYN animals in the rTDT ...... 113

Figure 15. Effects of Set Shifts on Performance of ECON and EKYN animals in the Plus Maze

Set Shifting Task ...... 114

Figure 16. Extradimensional Set Shifts Errors of ECON and EKYN animals in the Plus Maze Set

Shifting Task ...... 115

Figure 17 Brain KYNA Acid Levels in ECON and EKYN animals ...... 116

Figure 18. Effects of Cognitive Training on the Acquisition of Stage 3 of the rTDT in ECON and

EKYN Animals ...... 117

Figure 19. Effects of Cognitive Training on the Acquisition of Stage 4 of the rTDT in ECON and

EKYN Animals ...... 118

Figure 20. Effects of Cognitive Training on the Performance of ECON and EKYN Animals in the rTDT During Reduced Stimulus Duration ...... 119

Figure 21. Effects of Cognitive Training on Performance of ECON and EKYN Animals in the

Plus Maze Set Shifting Task ...... 120

Figure 22. Effects of Cognitive Training on Extradimensional Set Shift Errors in ECON and

EKYN Animals in the Plus Maze Set Shifting Task ...... 122

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Chapter 1. Introduction

Schizophrenia is a debilitating psychiatric disorder with a lifetime prevalence of ~0.5% worldwide (Simeone et al., 2015). Cognitive impairments in executive functions, such as attention and cognitive control, form a core symptom cluster and endophenotype for the disease

(Gottesman et al., 2003; Heinrichs et al., 1998; Kerns et al., 2008). These deficits occur in ~98% of patients, are heritable, precede the onset of psychosis, and are present independent of the remission state of the illness {Reviewed in (Green et al., 2004a; Keefe et al., 2005)}. These deficits are most predictive of functional outcomes for patients (Gold, 2004; Green et al., 2000;

Green et al., 2004b) and the degree to which these deficits are attenuated with treatment is a rate limiting factor for positive outcomes in everyday functioning such as the likelihood of returning to work (Keith H. Nuechterlein et al., 2011). Unfortunately currently approved neuroleptics, including second generation antipsychotics, have minimal effects on cognition (Keefe et al.,

2007; Nielsen et al., 2015).

Significant resources have been invested into the identification of pharmaceuticals for the treatment of the cognitive deficits present in schizophrenia. Many potential pro-cognitive compounds (e.g. Encenicline, Memantine, Aspirin, Oxytocin, etc.) have been tested either alone or as adjunctive therapies in combination with neuroleptics {reviewed in (Garay et al., 2016;

Keefe et al., 2013)}. Although preclinical research and phase II clinical trials have shown enhancements in sub-domains of cognition, so far no pharmacological agent tested in stage three

1 clinical trials have proven to have an effect on global cognition (Choi, Til, & Kurtz, 2013;

Correll et al., 2017). Given the above evidence and the fact that many of the current compounds being tested in phase III trials have been proposed based on correlative evidence (e.g. inflammation appears in schizophrenia, aspirin treats inflammation therefore aspirin could be effective) rather than hypothesis driven preclinical data, it is unlikely that a pharmacological solution to cognitive deficits will be found in the near future (Talpos, 2017). Therefore not only are new treatment strategies necessary but it is imperative that the field is able to identify preclinical cognitive assessments and animal models with better translational relevance. The studies contained within this dissertation addressed this topic with three major aims; Aim 1:

Demonstrate the translational and construct validity of the rodent Target Detection Task (rTDT).

Aim 2: Demonstrate that the embryonic kynurenine animal model results in translationally relevant deficits in attention and cognitive control. Aim 3: Demonstrate that cognitive training via prior experience in cognitively demanding tasks has a cross-task protective effect against the deficits in attention and cognitive control induced in the embryonic kynurenine model.

1.1 Task Selection

The NEWMEDs initiative (Novel Methods leading to New Medications in Depression and

Schizophrenia) was established to validate a comprehensive battery of novel touchscreen tasks with a focus on the translational value of tasks that test the cognitive domains identified by the

MATRICS (Measurement And Treatment Research to Improve Cognition In Schizophrenia) and

CNTRICS (Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia) initiatives (Hvoslef-Eide et al., 2015). Touchscreen tasks, like other operant tasks, offer several

2 advantages compared to commonly used maze based-tasks; for example they can be easily implemented in both rats and mice in a standardized, automated, high-throughput, non-aversive, low-stress manner, that significantly reduces the chance of confounds related to unintentional experimenter influence (Bussey et al., 2012). The NEWMEDS battery was developed to have direct analogues to clinical touchscreen batteries such as the CANTAB (Cambridge

Neuropsychological Test and Automated Battery) that has been extensively validated, showing test-retest reliability, predictive value for patient functional status, and sensitivity to pharmacological agents (Barnett et al., 2010). Schizophrenic patients tested in CANTAB showed deficits in several cognitive domains including executive functions such as attention and cognitive control (Levaux et al., 2007). Table 1 summarizes the pre-clinical tasks identified by the NEWMEDS initiative and the associated CANTAB tasks used in humans categorized by the cognitive domains identified in MATRICS and CNTRICS.

In the clinic, various versions of human continuous performance tasks (CPT) are collectively the gold standard for assessing the attentional impairments present in schizophrenia (Bellani &

Brambilla, 2008; Kofler et al., 2013; J W Young & Geyer, 2015). Thus the rodent Target

Detection Task (rTDT) was developed by the NEWMEDS initiative to better encompass aspects of human CPTs compared to the traditionally used rodent operant tasks of attention including the

5 Choice Serial Reaction Time Task (5CSRTT), the 5 Choice Continuous Performance Task

(5C-CPT), and the Distractor Sustained Attention Task (DSAT). Each of these tasks has value, focusing on unique aspects of attention, but all are limited by the fact that they only require the detection of the presence or absence of a simple light stimulus rather than a visual discrimination of target stimuli from non-target stimuli as is the case with the rTDT. In one of the more

3 commonly used models of schizophrenia, which is based on the gestational administration of a mitotoxin, methylazoxymethanol acetate (MAM), animals showed no deficits in the 5-CSRT

(Featherstone et al., 2007), or the DSAT (Howe et al., 2015) but exhibited robust deficits in the rTDT (Mar et al., 2017). This suggests that rTDT may be more sensitive to detecting certain types of attentional deficits. More specifically the added difficulty of a target vs non-target discrimination has been indicated as a key variable in observing vigilance decrements in human

CPT (Parasuraman, 1979). Although the rTDT has high degree of face validity, it has been tested in only one developmental model of schizophrenia and therefore it is necessary to further validate this task in another well-validated animal model.

1.2 Animal Model Selection

When selecting an animal model it is important to consider the face, construct, and predicative validity of each model. Face validity considers the similarity of symptomology and the epidemiological significance of the experimental manipulation compared to known risk factors for schizophrenia. Construct validity is related to the degree in which the model fits the theoretically determined underlying mechanisms of symptomology. Predictive validity refers to how well an animal model translates to other species including the ability of the model to replicate the efficacy of pharmacological agents that were effective in humans. It should be noted that no one model will encompass the full extent of human disease and therefore the overall aims of this dissertation will be considered when choosing the animal model.

The face validity of the two most commonly used neurodevelopmental models of schizophrenia, the MAM model (Lodge et al., 2009), and the Neonatal Ventral Hippocampal

Lesion (NVHL) model (Tseng et al., 2009), are limited by the fact that they utilize developmental disruptions with compounds exogenous to the brain. By comparison the Maternal

Immune Activation (MIA) model {reviewed in (Meyer, 2014)} was strongly considered because of the convergence of epidemiological and clinical evidence identifying gestational exposure to infection as a risk factor for the development of schizophrenia {reviewed in (Brown & Derkits,

2010)}. This model was later eliminated after preliminary results in our lab showed no significant differences in the rTDT (unpublished data; Phenis 2017), possibly due to difficulties with inconsistent immune activation using Poly I:C.

On the other hand, the embryonic kynurenine (EKYN) model utilizes elevations of the endogenous molecule kynurenine to manipulate the existing kynurenine pathway of tryptophan metabolism. Changes in the kynurenine pathway are present in patients with schizophrenia and are summarized in Figure 1. Feeding rat dams kynurenine in wet mash during critical stages of development results in elevations of Kynurenic Acid (KYNA) in the brains of pups and as a consequence long term neurobiological, neurochemical, and behavioral deficits (Alexander et al.,

2013; Pershing et al., 2015), further described in the introduction to chapter 4. The EKYN model also takes into account the epidemiological evidence identifying maternal infection as a risk factor (Brown & Derkits, 2010) as there is some evidence that the inflammatory milieu present in schizophrenia inhibits indoleamine 2,3-dioxygenase (IDO) (MÜller & Schwarz, 2006), one of two enzymes that control the metabolism of kynurenine. As a result, kynurenine is produced by the enzyme tryptophan 2,3-dioxygenase (TDO), which is almost exclusively localized in astrocytes which in turn favors the conversion of kynurenine into the neuroactive KYNA, by kynurenine aminotransferase II (KATII). This theory is supported by the fact that in the

5 prefrontal cortex of post-mortem schizophrenic brains both kynurenine and KYNA are elevated while the expression of the enzyme that metabolizes kynurenine in microglia, kynurenine 3- monooxygenase (KMO) is suppressed indicating an overall shift away from the microglia branch of the pathway and towards overproduction of KYNA (Sathyasaikumar et al., 2011; Schwarcz et al., 2001). This is further supported by the fact that patients with schizophrenia show an almost two-fold increase in KYNA levels in cerebrospinal fluid (Erhardt et al., 2001). Collectively these data show the face validity of the EKYN model.

The construct validity of the EKYN model is revealed when considering the actions of

KYNA including its role as an endogenous negative allosteric modulator of the alpha-7 nicotinic acetylcholine receptor (α7nAChR) and at higher concentrations an antagonist of the glycine b site of the NMDAR (Erhardt et al., 2001; Lopes et al., 2007). This is especially important considering the evidence that the inhibition of these receptors directly contributes to the cognitive deficits present in schizophrenia (Timofeeva & Levin, 2011).

Several labs have used prenatal elevations of KYNA as a model of schizophrenia showing the replicability of the model. For example increases of KYNA by prenatal inhibition of

KMO in rats lead to disruptions of synaptic transmission, neuronal morphology, and plasticity

(Forrest et al., 2013; Khalil et al., 2014). KMO deletion in knockout mice also showed plasticity deficits including decreases in long term potentiation (Forrest et al., 2015; Giorgini et al., 2013).

The predictive validity of the EKYN model is further strengthened by that fact that certain schizophrenia-like symptomology, such as disruptions in pre-pulse inhibition (a marker of sensorimotor gating) is sensitive to rescue by antipsychotic administration (Erhardt, Schwieler,

Emanuelsson, & Geyer, 2004). This is consistent with the fact that KYNA levels were shown to

6 be normalized following chronic antipsychotic treatment in patients (Ceresoli-Borroni et al.,

2006; Rassoulpour et al., 2006). It is important to note that lack of efficacy of antipsychotic medications on the cognitive deficits present in schizophrenia, despite the normalization of

KYNA levels. This provides evidence that acutely elevated KYNA is not a necessary condition for cognitive deficits to persist.

Having provided evidence of the face, construct and predicative validity of the EKYN model it important to assess whether the model will present with deficits in the rTDT. In brief EKYN animals have shown to have cognitive deficits in both attention in the 5CSRTT (Hahn et al.,

2018) and cognitive flexibility (Pershing et al., 2015) in the Attentional Set Shifting Task

(ASST). Having identified a novel task sensitive to disruptions of attentional processes and cognitive control, and an animal model with face, construct, and predictive validity, the final selection to achieve the aims of the dissertation was to identify an alternative treatment strategy to pharmacological options which so far have shown limited effectiveness as describe earlier in this introduction.

1.3 Treatment selection

One alternative to pharmacological agents is the use of psychotherapeutic interventions such as cognitive remediation therapy (CRT) that consists of cognitive training in many of the cognitive domains that are affected in schizophrenia. CRT has been shown to produce moderate improvements in overall cognitive performance and improvements in functional outcomes such as social functioning and employment {Reviewed in (Barlati et al., 2013)}. Although CRT has been shown to yield durable improvements in global cognition and functioning (Wykes et al.,

2011), there have been some negative results, showing a lack of training generalization to untrained cognitive domains (Dickinson et al., 2010; Gomar et al., 2015). The modest enhancement of overall cognition found in CRT may not be sufficient to normalize performance in enough cognitive domains to result in real world improvements in quality of life (Buonocore et al., 2017). Given these mixed results it is clear that the critical components for the efficacy of cognitive training have yet to be identified (Kurtz et al., 2007a). Pre-clinically there have been very few attempts at modeling cognitive training, but an initial proof of concept was shown in the NVHL model (Lee et al., 2012). Therefore, there is a strong imperative to use EKYN deficits in the rTDT as a platform to test the efficacy of cognitive training.

The current work will be the first to examine the effects of prenatal elevations of kynurenine on performance in the rTDT, and whether cognitive training via prior experience in the Maze Set

Shifting task will be sufficient to protect animals from deficits in attentional processing.

Furthermore, to determine whether cognitive training has a generalize effect, a full cross with task order counterbalanced will be utilized. Figure 2 shows a summary of the experimental design broken down by experimental aim.

Chapter 2. Methods

2.1 Animals

All experimental animals were adult male Long Evans rats pair housed in clear plastic cages lined with corncob bedding under a standard 12-h light/dark cycle (lights on 0600-1800 hours) in temperature and humidity controlled AALAC-approved animal facilities. During all experiments standard rat chow was provided ad libitum. All experiments were carried out in accordance with protocols approved by The Ohio State University Institutional Laboratory

Animal Care and Use Committee and consistent with the NIH Guide for the Care and Use of

Laboratory Animals. Animals for intact experiments (intact cohort 1 and 2 used in Aim 1) were purchased from Charles River Laboratories, Inc. (Kingston, NY). Animals for the embryonic kynurenine model (embryonic kynurenine (EKYN) and embryonic control (ECON) used in Aim

2 and 3) were bred in The Ohio State University Vivarium (procedure described in section 2.4).

Breeder animals were purchased from Charles River Laboratories, Inc. (Kingston, NY).

2.2 Breeding and Kynurenine Supplementation

Generation of embryonic kynurenine (EKYN) model animals (used in Aim 2 and 3) followed the protocol previously established in our lab (Pershing et al. 2015). Breeder rats were paired on a 1:1 basis in the home cage of the male. Vaginal lavages were completed daily following pairing. The presence of sperm in the lavage was marked as embryonic day (ED) 0 and animals were separated and housed individually. Females were then transferred from the normal 9 rat pellet diet to a mash diet (Teklad Diets, Madison, WI) mixed with water (1:1 w/v) starting at

30 g/day. Food intake was monitored daily and adjusted (+-5g) to ensure a stable intake. Starting on ED 15 breeder moms either continued with unadulterated mash (embryonic control; ECON) or received mash spiked with 100mg L-Kynurenine sulfate (Sigma Aldrich, Milwaukee, MI) each day from ED15-22 (embryonic kynurenine; EKYN). The day dams gave birth was designated postnatal day (PD) 0, after which all animals were returned to standard rodent pellets.

On PD 2 litters were culled to 9 to 11 pups to standardize growth rates and to maximize the number of males available for experiments.

2.3 Weaning and Distribution of Littermates across Experimental Conditions

Following culling litters were not disturbed until weaning on PD21. At this time female pups and dams were euthanized using carbon dioxide gas. PD56 and onward rats were pair-housed by litter and assigned to experimental aims as summarized in Table 2.

2.4 Kynurenic acid (KYNA) in PFC tissue

Brain collection and KYNA analysis was completed following the protocol published by

Pocivavsek et al., 2014. One naïve sentinel pup from each litter that contributed to behavioral assays was analyzed (brains collected in adulthood PD 56-80). Additionally, each animal that was trained in the rTDT followed by the Maze Set Shifting task was analyzed (brains collected following behavior PD136-143), to determine if there were any differences in KYNA following cognitive training. Animals were euthanized with CO2 followed by rapid removal of the brain.

The prelimbic and infralimbic regions of the PFC were dissected out and rapidly frozen on dry ice and then stored at -80 °C. For kynurenic acid determination the tissue was thawed and sonicated in ultrapure water (1:10 w/v). 100ul of homogenate was acidified with 25ul of 6% 10 perchloric acid after which samples were centrifuged 12,000xg for 10 minutes. The supernatant was collected and 20ul was analyzed using high-performance liquid chromatography (HPLC).

KYNA was detected fluorometrically (excitation 344nm, emission 398nm; Perkin Elmer series

200) with retention time of 7 minutes.

2.5 Water deprivation

Prior to either the rodent Target Detection Task or the Maze Set Shifting task water availability was progressively restricted over 6 days (water deprived 12, 12, 20, 20, 22, 22 hr/day) and then water access was maintained at 1h/day in addition to water rewarded during task performance. During the period of progressive water restriction animals were habituated to handling.

2.6 Rodent Target Detection Task (rTDT)

Apparatus:

The target detection task used in this dissertation was modeled from the rodent continuous performance task published by Mar et al. 2017. A standard rat operant system (4 chambers; Med

Associates, St Albans, VT) was modified to include a touch-sensitive monitor (Conclusive

Solutions, UK) controlled by K-Limbic software (Conclusive Solutions, UK). Each operant system was contained within a sound-attenuating box with a fan for ventilation. The wall opposite each touchscreen was equipped with a central reward receptacle with water dropper, signal light and IR beam break sensor for registering head entries for reward retrieval.

Habituation:

During the last two days of progressive water restriction animals were introduced to the operant chambers in 20-minute habituation sessions. During this time the chamber was dark, droplets of water were periodically added to the reward receptacle and on the surface of the touchscreen.

Task Acquisition:

Animals performed daily sessions to acquire the rTDT in four stages. In stage 1 animals learned to touch a solid white square stimulus (7x7cm) located in the center of the touchscreen.

The stimulus is presented for a stimulus duration (SD) of 10 seconds. Correct touches, designated as hits, must be made either during stimulus presentation or within a 500ms limited hold (LH) period. If no touch is made during this period the trial is counted as a miss and there is a 2 second inter-stimulus interval (ISI) before the next stimulus presentation. During the ISI only a white frame outlining the response area is shown. Touches in the response box during the ISI are designated as ISI touches and reset the interval of the ISI. Following a hit the stimulus is removed and the signal light illuminates indicating that water reward has been dispensed.

Reward retrieval triggers the beam break sensor which turns off the signal light and initiates the

ISI before the next stimulus presentation. The testing session continue until either the animal has

100 hits or after 45 minutes. Criterion for progression to the next stage is that animals must achieve 100 hits in two consecutive sessions.

In stage 2 the white square was replaced with one of two possible target (S+) stimuli

(horizontal or vertical bars) counterbalanced across groups. The SD was reduced to 2s and the

LH was increased to 2.5s. Following reward retrieval a 5s ingestion period was added. Criterion for progression was 100 hits in two consecutive sessions.

In stage 3 a non-target (S-) stimulus (horizontal or vertical bars), different from that chosen in stage 2, is added to the stimulus set. The SD and LH remain the same while ISI is increased to

5s. On any normal trial there is a 50% chance of the presentation of the target (S+) or non-target

(S-) stimuli. If the animal makes a touch when the non-target is presented then the trial is counted as a false alarm (FA). False alarms trigger a correction trial in which the next stimulus presentation must be a non-target. Trials in which the animal withholds response to the non- target are counted as a correct rejection (CR). Given these four response possibilities (hit, miss, correct rejection, false alarm) signal detection theory (Stanislaw & Todorov, 1999) yields several measures of performance:

Hit Rate (HR) = (hits / (hits + misses))

False Alarm Rate (FAR) = (FA / (FA + CR))

Sensitivity (d’) = z (hit rate) – z (false alarm rate)

Response Bias (c) = -0.5*(z (hit rate) + z (false alarm rate))

In this case z is the normal distribution function. In stage 3 rats underwent a minimum of 5 sessions after which the criterion for progression was three consecutive sessions with a sensitivity score (d’) greater than 1.2. In Stage 4 three additional non-target stimuli were added to the stimulus set. Stage 4 has a variable SD 0.5-1.5s with a fixed LH of 2s and a variable ISI 3-

7s, with all other parameters remaining the same as stage 3. Figure 3 shows a schematic of the rTDT procedure under stage 4 conditions. These Stage 4 conditions are designated as the baseline task conditions.

2.7 Maze Set Shifting Task

Apparatus: 13

The Maze Set Shifting task used in this dissertation was modeled after the Plus Maze Set

Shifting task published by Moghaddam et al. 2005. The plus maze, constructed of wood and sealed with varnish, consisted of four arms connected to a central square. Each arm varied across two stimulus modalities, brightness (white vs black) and texture (rough vs smooth). A reward receptacle for water was added to the end of each arm. The maze was placed on a rotating platform. Each arm of the maze could be blocked off with a wooden barrier to alter the maze into a t-maze configuration. A standard animal cage was utilized as the holding cage during inter-trial intervals.

Habituation:

Once animals were fully water deprived, cage mates were transferred from their home cage to the holding cage outside of the maze. Each pair was then habituated to the plus maze and water retrieval. Water was added to each arm continuously until both animals were rapidly retrieving water from all arms. On the second day rats were individually habituated to the maze in its T configuration. Each rat underwent as many trials as necessary for them to receive reward in each of the 4 arms twice. The order of the start arm was pseudorandomized. For each trial the rat was placed in the center arm of the ‘T’ and allowed to explore one of two possible arms

(white rough, black rough, white smooth, black smooth). Once the animal made a choice they were given time to consume the water reward before being placed back in the holding cage. The inter-trial interval was approximately 15 seconds. With each new trial the maze was rotated so the start arm faced the experimenter and to discourage the use of cues outside of the maze.

During this second habituation day animals were pseudo-randomly rewarded to prevent any associations between arm stimuli and reward frequency.

Set Shift Task:

Task testing conditions were outlined in Figure 4. Testing consisted of three sessions, conducted every other day. On day 1 (Set 1) animals learned an initial discrimination either brightness (dark vs light) or texture (rough vs smooth). On day 3 (Set 2) rats had to switch to an alternative discrimination strategy. This ‘extradimensional’ shift required animals to attend to the stimulus dimension that was previously irrelevant on day 1 (i.e. dark ->rough, light->smooth, rough->light, smooth->dark). On day 5 (Set 3) the relevant dimension was the same as day 3 but now animals were required to complete a ‘reversal’ where the previously correct set of stimuli were now incorrect (i.e. dark ->light, light->dark, rough->smooth, smooth->rough). The order of which arms were correct for Set 1, 2, and 3, were fully counterbalanced across animals. For each set, animals were tested to a criterion of eight consecutive entries into a rewarded arm on two occasions (either consecutive or separate). The time and number of trials to criterion were recorded.

Chapter 3: Parmetric and Pharmcological Validation of the rTDT

3.1 Introduction

The introduction in chapter 1 outlined the criteria by which the rodent Target Detection Task

(rTDT) was selected for the current work, but to confirm the validity of this task a broader understanding of attentional processes and their disruption in rodent and clinical tasks of attention is needed.

3.1.1 Attentional Processes

Attention is a complex cognitive process whose disruption is a core component in the deficits present in many psychiatric disorders. Attention consist of a variety of components including the initiation of focus, sustained attention or vigilance, selective attention or cognitive control, and shifting attention (Riccio et al., 2002). These four elements are defined as follows

(Mirsky et al., 1991): Focus of Attention refers to the ability of individuals to consciously select stimuli in the environment such as in voluntary control of attention with visual selection.

Sustained Attention is the capacity of individuals to maintain focus over time, this is also referred to as vigilance. Vigilance in humans is known to decrease over time as measured by reductions in sensitivity, or d’, over time. Selective Attention is related to the ability of individuals to preferentially select and process relevant stimuli while suppressing irrelevant stimuli, this includes the ability to filter out distractors. Shifts in Attention refers to the ability to shift attention from one salient element of the environment to another, for example from one 16 sensory modality to another. The inability to flexibly shift is related to perseverative behavior in which a particular response is repeated despite the absence or cessation of a stimulus.

Given the wide array of processes that are associated with attention, the CNTRICS

(Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia) group chose to focus on the control of attention as the construct that is most impaired in schizophrenia

(Luck & Gold, 2008). CNTRICS selected three preclinical tasks to measure this construct:

5CSRTT(Robbins, 2002), 5C-CPT(Young et al., 2009), and DSAT (McGaughy & Sarter, 1995).

Our review of these tasks will focus on the sensitivity of these tasks to pharmacological challenge with standard reference compounds including muscarinic, nicotinic and NMDA receptor antagonists.

3.1.2 Preclinical Tasks of Attention

The 5CSRTT is a task of sustained attention which requires animals to divide attention over a set of five locations where a simple light stimulus is presented. Animals correctly respond by touching the lit location, with performance measured in terms of accuracy (% correct touches) and response latencies. Omissions and reward retrieval latencies act as a marker of motivation level. Premature responses, prior to stimulus presentation, are measured as a marker of animal impulsivity. Acute injection of MK-801, a NMDA receptor antagonist, was shown to reduce accuracy while increasing omissions and premature responding (Paine & Carlezon, 2009).

Studies of acute injections of mecamylamine, a general nicotinic antagonist, often found increases in omissions and response latency and sometimes found decreases in accuracy

(Robbins, 2002). Interestingly no deficits were found with specific nicotinic receptor antagonists including the alpha-7 specific antagonist methyllycaconitine (MLA) or the alpha4beta2 17 antagonist DHBE (Grottick & Higgins, 2000). Acute injections of scopolamine often show increases in omissions but less consistently show decreases in performance (Mirza & Stolerman,

2000; Robbins, 2002).

The 5C-CPT, like the 5CSRTT, requires animals to attend to a 5 location array with target responses occurring when animal touches the single location. The 5C-CPT adds a non-target condition in which the animal must inhibit responding when all five stimulus locations are lit.

This allows for signal detection analysis with four response categories; hits (animal touches target), misses (animal fails to touch target), false alarms (animal touches a non-target), and correct rejections (animal inhibits non-target response). Few studies have examined the sensitivity of the 5C-CPT to pharmacological challenge. Acute scopolamine administration in mice resulted in a decrease in sensitivity over time driven by reductions in target detection.

Interestingly, mice challenged with scopolamine showed a similar pattern of impairment compared to patients with schizophrenia tested in a reverse translated version of the 5C-CPT tested in Young et al., 2013.

The DSAT requires animals to respond to the presence of a single simple light stimulus presented for 25, 50, or 500ms. Animals are required to hit one lever when they detect the stimulus and the opposite lever in the absence of the light stimulus. Animals perform the task with and without a distractor condition, which increases the background noise by flashing the houselight in the chamber. Significant work in the non-distractor version of the task (SAT) shows that transient increases in cholinergic activity occur after successful signal detection, but cholinergic input is not necessary for performance in non-signal trials {reviewed in (Lustig et al.,

2013; Nuechterlein et al., 2009)}. Few studies have examined the effects of systemically

18 administered drugs. Mecamylamine resulted in increases in omissions and impaired the animals ability to discriminate between signal and non-signal events (Turchi, Holley, & Sarter, 1995).

Collectively these preclinical tasks of attention provide useful comparison points for the validation of the rTDT (See chapter 3 discussion).

3.1.3 Rationale

The central hypothesis guiding the experiments in this dissertation is that gestational elevations of kynurenine will present with a profile of translationally relevant attentional deficits in the rodent Target Detection Task (rTDT) and that these deficits can be reversed with cognitive training. The hypothesis is first explored in the current aim with a validation of the rTDT. The rTDT was identified by the Novel Methods leading to New Medications in Depression and

Schizophrenia (NEWMEDS) initiative as a touchscreen task with high translational potential for assessing attention and executive control (Hvoslef-Eide et al., 2015). The rTDT is a task of sustained visual attention and cognitive control and was designed to be analogous to human

Continuous Performance Tasks; both of which require the detection of targets from non-targets.

Despite the face validity of this task there have been relatively few publications utilizing it. No publications so far have tested Long Evans rats therefore it is necessary to establish the performance profile of intact animals during acquisition, baseline, parametric, and pharmacological challenge.

Hypothesis: If the rTDT is a valid task for identifying attentional deficits then it must show consistent and stable acquisition, show performance sensitive to increases in cognitive load by

19 parametric challenge, and must be sensitive to the acute effects of drugs known to interfere with the neural systems that are necessary for the performance of attentional tasks.

3.2 Methods

In this dissertation, intact animals were used to validate the rTDT. Intact animals acquired the rTDT as described in section 2.8. Animals were then challenged by changing the parameters of the baseline task. Following parametric challenge animals were injected with pharmacological agents that have previously been shown to disrupt performance in attentional tasks.

3.2.1 Intact Parametric Challenge

Modifications of these baseline task parameters were completed for two types of parametric challenge, the stimulus duration (SD) and stimulus contrast (SC) probe tests. The changes to stimulus parameters for each probe test are summarized in Table 4. For intact animal experiments, each animal completed a minimum of 13 sessions after which the criterion for the first probe test was a d’ score >1.2 on two consecutive sessions. For all subsequent probe tests and drug test points, a minimum of one baseline day with d’ score >1.2 was required. Intact animals (N=19) underwent 4 probe tests in order SD1, SD2, SC1, SC2.

3.2.2 Intact Pharmacological Challenge

Following all probe tests and two consecutive baseline sessions with a d’ score >1.2 animals underwent multiple drug test-points under baseline task conditions. Subsets of animals received a saline dose first, followed by a low and high dose of each drug. Low and high dose order was counterbalanced, and each dose was separated by a minimum of one baseline day with a d’ score 20

>1.2 required. In animals that received multiple drugs, drug order was counterbalanced, and each drug was separated by a minimum of a one-week washout period. Drug dose was selected based on doses known to cause deficits in rodent attentional task (reviewed in section 3.4). The drug doses and timing are listed below:

-Dizocilpine hydrogen maleate (MK801; Sigma-Aldrich, St. Louis, MO, USA) a N-Methyl-

D-aspartate receptor antagonist was mixed with sterile saline and injected intraperitoneal (N=17)

0, 0.05, 0.1mg/kg, 30 minutes prior to task performance.

-Mecamylamine hydrochloride (MEC; Sigma-Aldrich, St. Louis, MO, USA) a general nicotinic receptor antagonist was mixed with sterile saline and injected intraperitoneal (N=17) 0,

1, 5 mg/kg, 20 minutes prior to task performance.

-Scopolamine hydrobromide (SCOP; Sigma-Aldrich, St. Louis, MO, USA) a general muscarinic receptor antagonist was mixed with sterile saline and injected intraperitoneal (N=9)

0, .1, .2 mg/kg, 30 minutes prior to task performance.

3.2.3 Statistical Analyses

The d’ sensitivity parameter was used to compare the general acquisition performance of two cohorts of intact animals to ensure internal consistency in the rTDT task. A two-way repeated measures ANOVA with Sidak multiple comparison tests was completed for d’ for Stage 3 and

Stage 4 rTDT acquisition. For the parametric and pharmacological challenges a full profile of rTDT parameters were analyzed. One-way ANOVAs with Tukey Multiple comparison tests were completed for all of the following parameters: d’, c, HR, FAR, ISI touch inside stimulus box, ISI touch outside stimulus box, correct choice latency, incorrect choice latency, and retrieval latency.

For the parametric challenge separate One-way ANOVAs were used to compare reductions of 21 stimulus duration (SD1 and SD2 vs Baseline 1 and Baseline 2 respectively) and reductions of contrast (SC1 and SC2 vs Baseline 3 and Baseline 4 respectively). A separate One-way ANOVA was completed for each of the drugs (MK801, mecamylamine, and scopolamine). All statistical analysis was completed with GraphPad Prism (Version 6.07).

3.3 Results

The major findings of Chapter 3 are summarized in Table 3, which depicts the effects of various manipulations used to validate the use of the rTDT as a task that measures changes in attentional peformance. The rTDT was shown to have a stable acquisition across cohorts. The rTDT was shown to be sensitive to increases in cognitive load as a result of reductions in stimulus duration or stimulus contrast. The rTDT was shown to be sensitive to acute injections of drugs known to disrupt the neural systems involved in attentional processing.

3.3.1 Intact Animal Performance during rTDT Acquisition

Our results demonstrate the consistency in the acquisition of the rTDT task. Task acquisition can be represented by increases in d’ (sensitivity) over multiple sessions. Figures 5 and 6 show improvements in d’ over days during Stage 3 (F7, 196 = 47.06, P = 0.0001) and Stage

4 (F14, 322 = 5.564, P= 0.0001). Note that the same animals are represented in each stage (n= 17 per cohort).

Stage 3 is the first and simplest stage where animals are required to discriminate target from non-target; therefore rapid acquisition with large increases in d’ was expected. Figure 5 shows that performance improved from Day 1 to Day 8 in both cohort 1 (Day 1: 0.53 ± .1 Day 8:

1.68 ± .15) and cohort 2 (Day 1: 0.44 ± .11 Day 8: 2.1 ± .09). Importantly there were no overall differences between intact groups (P = 0.23) or groups as a function of day (P = 0.08).

Stage 4 is the final and most complex version of the task; therefore, slower acquisition approaching a performance ceiling was expected. Figure 6 shows that performance improved from Day 1 to Day 15 in both cohort 1 (Day 1: 0.98 ± .07 Day 15: 1.43 ± .18) and cohort 2 (Day

1: 0.98 ± .07 Day 15: 1.6 ± .09). Again there were no significant differences between intact groups overall (P = 0.66) or groups as a function of day (P = 0.33). Following stable acquisition of the rTDT, the validity of the task was assessed by parametric changes in stimulus variables as well as pharmacological challenges to neural systems known to be involved in mediating performance in such tasks.

3.3.2 Increasing Cognitive Load in Intact Rats

Reductions of stimulus duration (SD) and stimulus contrast (SC) were used to decrease stimulus detectability and to increase the cognitive load of the rTDT. These manipulations were predicted to result in a distinct profile of performance deficits. Only intact cohort 2 underwent these stimulus challenges (n=17). Figure 7 represents the statistically significant effects of varying SD on several measures of performance. The animals underwent two challenge days,

Stimulus Duration 1 (SD1= 0.5-1.0 s) and Stimulus Duration 2 (SD2 = .25-.75 s) described in

Table 4. The data from each challenge day were compared to each other and to the baseline session from the previous day. Importantly, all baseline sessions for all measures of performance were not significantly different; therefore, the baseline session prior to each challenge session were utilized as a standard baseline. Figure 7 shows that as stimulus duration is shortened, during

SD2, d’ is reduced (Panel A: F2, 45 = 21.22, P = 0.0001) due to a decrease in hit rate (Panel B: F3,

46 = 8.321, P = 0.0003) and a small increase in false alarm rate (Panel C: F3, 47 = 5.686, P =

0.0032); additionally, touches within the stimulus box during the ISI were increased (Panel D: F2,

40 = 14.93, P = 0.0001). In Panel A, the d’ of SD2 (1.08 ± 0.08) was significantly lower than SD1

(1.36 ± 0.07; P = 0.099) and baseline 2 (1.53 ± 0.06; P = 0.0001). In Panel B, the HR of SD2

(0.65 ± 0.02) was significantly lower than baseline 2 (0.75 ± 0.02; P = 0.0002). In Panel C, the

FAR of SD2 (0.25 ± 0.02) was significantly higher than baseline 2 (0.21 ± 0.02; P = 0.016). In

Panel D, the ISI touches of SD2 (239 ± 31) were significantly higher than SD1 (148 ± 20; P =

0.0004) and baseline 2 (142 ± 21; P = 0.008). Also measured but not reported: c (response bias), correct choice latency, incorrect choice latency, retrieval latency because there were no significant differences between baselines and challenge sessions.

Figure 8 represents the statistically significant effects of varying SC on several measures of performance. The animals underwent two challenge days: Stimulus Contrast 1 (SC1= 50% contrast) and Stimulus Contrast 2 (SC2 = 25% contrast). The data from each challenge day were compared to each other and to the baseline session from the previous day. Importantly, all baseline sessions for all measures of performance were not significantly different; therefore, the baseline session prior to each challenge session can be utilized as a standard baseline. Figure 8 shows a similar pattern to Figure 7. As stimulus contrast is reduced during SC2, d’ decreases

(Panel A: F2, 37 = 31.92, P = 0.0001) due to a small decrease in hit rate (Panel B: F2, 42 = 4.988, P

= 0.0085) and a large increase in false alarm rate (Panel C: F2, 40 = 19.01, P = 0.0001); additionally, ISI touches within the stimulus box were increased (Panel D: F2, 42 = 12.74, P =

0.0001). In Panel A, the d’ of SC2 (0.85 ± 0.1) was significantly lower than SC1 (1.33 ± 0.09; P

= 0.0001) and baseline 4 (1.5 ± 0.06; P = 0.0001). In Panel B, the HR of SC2 (0.65 ± 0.03) was significantly lower than baseline 4 (0.72 ± 0.02; P = 0.0466). In Panel C, the FAR of SC2 (0.34 ±

0.03) was significantly higher than SC1 (0.25 ± 0.03; P= 0.003) and baseline 4 (0.21 ± 0.02; P =

0.0002). In Panel D, the ISI touches of SC1 (187 ± 21) were higher than baseline 3 (118 ± 16; P

= 0.008) and SC2 (198 ± 28) was higher than baseline 4 (95 ± 12; P = 0.008), but there were no significant differences between SC1 and SC2. Also measured but not reported: c (response bias), correct choice latency, incorrect choice latency, retrieval latency because there were no significant differences between baseline and challenge sessions. Following both types of parametric challenge animals were pharmacology challenged with drugs known to produce deficits in tasks of attention and cognitive control.

3.3.3 Pharmacological Challenges in Intact Rats

Overall rTDT performance measures are sensitive to the acute effects of drugs that have been shown to interfere with the neural systems known to be necessary for performance in attentional tasks. The glutamatergic antagonist MK801 (NMDA receptor antagonist) was shown to induce deficits that may be a result of a general stimulatory effect. Figure 9 summarizes the statistically significant dose-related effects of MK801 (0, 0.05, and 0.1 mg/kg) on various measures of task performance in rats from intact cohort 1 (n= 17). In summary as the dose of

MK801 increases c decreases (Panel A: F2, 31 = 12.89, P = 0.0001) due to an increase in both hit rate (Panel B: F 2, 32 = 5.882, P = 0.0067) and false alarm rate (Panel C: F2, 29 = 16.66, P =

0.0001). In Panel A, c decreased for both the lower (-0.17 ± 0.1; P = 0.027) and higher dose (-

0.25 ± 0.11 P = 0.0011) compared to vehicle (0.12 ± .1). In Panel B, HR increased for both the lower (0.83 ± 0.03; P = 0.0297) and higher dose (0.83 ± 0.29; P = 0.0182) compared to vehicle 25

(0.75 ± 0.04). In Panel C, FAR increased for both the lower (0.27 ± 0.03; P=0.0028) and higher dose (0.3 ± 0.03; P=0.0004) compared to vehicle (0.18 ± 0.02). As MK801 dose increased, retrieval latency decreased (Panel E: F2, 27 = 15.07, P = 0.0001), and there was a trend towards an increase in ISI touches (Panel D: F1, 22 = 3.129, P = 0.0805). In Panel D, ISI touches increased for higher dose (136 ± 17; P=.0043) compared to vehicle (74 ± 9) but not for the lower dose (139

± 32; P=.1716). In Panel E, retrieval latency decreased for both the lower (1015 ± 45 ms;

P=0.002) and higher dose (1011 ± 41 ms; P=0.001) compared to vehicle (1096 ± 36 ms). Also measured but not reported: d’, correct choice latency, and incorrect choice latency because there were no significant differences between vehicle and either MK801 dose.

The cholinergic antagonist mecamylamine (nicotinic receptor antagonist) was shown to induce deficits that may be a result of a general sedative effect. Figure 10 summarizes the statistically significant dose-related effects mecamylamine (0, 1, and 5 mg/kg) on various measures of task performance in rats from intact cohort 1 (n=17). Figure 10 shows that as mecamylamine dose increases d’ decreases (Panel A: F1, 24 = 10.13, P = 0.0016) and c increases

(Panel B: F2, 31 = 12.89, P = 0.0001) due to a decrease in both hit rate (Panel C: F 1, 19 = 30.28, P

= 0.0001) and false alarm rate (Panel D: F2, 27 = 10.42, P = 0.0008). In Panel A, the higher dose

(1.46 ± 0.07) showed a lower d’ value compared to vehicle (1.82 ± 0.07; P = 0.0079) or the lower dose (1.77 ± 0.07; P = 0.012). In Panel B, the higher dose (0.82 ± 0.15) showed a higher c value compared to vehicle (0.08 ± 0.08; P = 0.0079) or the lower dose (0.08 ± 0.11; P = 0.012).

In Panel C, the higher dose (0.46 ± 0.05) showed a lower HR compared to vehicle (0.78 ± 0.03;

P = 0.0001) or the lower dose (0.76 ± 0.03; P = 0.0001). In Panel D, the higher dose (0.1 ± 0.03) showed a lower FAR compared to vehicle (0.17 ± 0.02; P = 0.016) or the lower dose (0.19

±0.02; P = 0.0036). The higher dose of mecamylamine increased both correct choice (Panel E:

F1, 22 = 17.65, P = 0.0001) and retrieval (Panel F: F1, 19 = 14.01, P = 0.0009) latency. In Panel E, the higher dose (996 ± 56 ms) showed a higher correct choice latency compared to vehicle (786

± 35 ms; P = 0.0009) or the lower dose (819 ± 43 ms; P = 0.0014). In Panel F, the higher dose

(1203 ± 52 ms) showed a higher retrieval latency compared to vehicle (1059 ± 41 ms; P =

0.0037) or the lower dose (1049 ± 38 ms; P = 0.0039). Also measured but not reported: ISI touches and incorrect choice latency because there because there were no significant differences between vehicle and either mecamylamine dose.

Scopolamine (muscarinic receptor antagonist) had a similar profile to mecamylamine, but further inspection of rTDT performance measures suggests the deficits cannot be explained by a general sedative effect. Figure 11 summarizes the statistically significant dose-related effects of scopolamine (0, 0.1, and 0.2 mg/kg) on various measures of task performance in rats from intact cohort 2 (n=9). In summary, Figure 11 shows that as scopolamine dose increases d’ decreases

(Panel A: F2, 15 = 11.41, P = 0.0011) and c increases (Panel B: F1.855, 14.84 = 15.83, P = 0.0003) due to a decrease in both hit rate (Panel C: F2, 15 = 27.76, P = 0.0001) and false alarm rate (Panel D:

F2, 12 = 4.817, P = 0.035). In Panel A, the higher dose (1.36 ± 0.09) showed a lower d’ value compared to vehicle (1.89 ± 0.09; P = 0.003) but did not differ from the lower dose (1.53 ± 0.08;

P = 0.2881). In Panel B, the higher dose (0.68 ± 0.11) showed a higher c value compared to vehicle (0.08 ± 0.1; P = 0.0032) or the lower dose (0.25 ± 0.07; P = 0.0053). In Panel C, the higher dose (0.5 ± 0.04) showed a lower HR compared to vehicle (0.8 ± 0.03; P = 0.0001) or the lower dose (0.7 ± 0.03; P = 0.0048). In Panel D, the higher dose (0.1 ± 0.2) showed a lower FAR compared to the lower dose (0.16 ± 0.02; P = 0.016), but not compared to vehicle (0.16 ± 0.03; P

=0.11). Also measured but not reported: ISI touches, correct choice latency, incorrect choice latency and retrieval latency because there were no significant differences between vehicle and either scopolamine dose. It is important to note that there were no significant differences in latency times, making it less likely that the deficits are the result of a purely sedative effect.

3.4 Discussion

Collectively these data show that the rTDT has a stable and reproducible acquisition, is sensitive to increase in cognitive load via parametric challenge and responds predictably to pharmacological challenges that are known to disrupt the neurochemical systems needed for attentional processing. This discussion section will focus on validating the rTDT by comparing these results to the rodent and human literature.

Figures 5 and 6 show that, within our lab, acquisition performance in the rTDT is consistent with animals learning the task and is reproducible from cohort to cohort. When comparing the acquisition of stage 4 in our animals to the previously published rTDT data (Mar et al., 2017), our animals show a similar pattern of increasing d’ occurring over fewer acquisition days (15 vs 20). This may be a result of our use of Long Evans (LE) animals compared to the albino Sprague Dawley rats. This hooded strain was chosen to eliminate any potential confounds related to discrimination of visual stimuli in touchscreen tasks. More specifically LE rats, compared to albino rat strains, show better visual acuity and faster acquisition in a visual discrimination reversal learning task (Kumar et al., 2015).

Figure 7 and 8 show that the manipulations of stimulus presentation, either with reductions in duration or contrast, result in an increased cognitive load for performing the task.

More specifically these manipulations put additional strain on attentional and perceptual systems.

Although reductions in stimulus duration or contrast show very similar patterns in their deficit profile (decreased d’, decreased HR, increased FAR and increased ISI touches), examining the magnitude of effect of each individual measure provides evidence that the decreases in d’ during

SD2 are primarily a result of a reduction in HR while the decrease in d’ during SC2 are primarily driven by increases in FAR. This conclusion was reached because the SC2 challenge session resulted in a large magnitude increase in FAR while the SD2 challenge session resulted in a very minor magnitude increase in FAR. This pattern replicates the pattern present in mice, which shows that reductions of stimulus duration result in decreases in d’ and HR with no change in

FAR, while reduction in contrast results in decreases in d’, HR and FAR (Kim et al., 2015). In our animals, reductions of stimulus duration and contrast both resulted, in similar magnitude increases in ISI touches. These pre-stimulus touches are a marker of general increase in animal impulsivity.

Figures 9, 10, and 11 shows that the rTDT is sensitive to the antagonism of either glutamatergic or cholinergic systems. This discussion will focus on comparisons of our rTDT results to the previous work of other labs who tested intact animals in the 5CSRTT, 5C-CPT, and

SAT by challenging with acute administrations of glutamatergic and cholinergic antagonists

(their results summarized in section 3.1.2). Collectively this previous work revealed that glutamatergic and cholinergic systems mediate different aspects of attentional processing, resulting in a unique profile of deficits for each drug tested. When comparing similar doses of

MK801 in the 5CSRTT (0.125 mg/kg) and rTDT (0.1mg/kg), both tasks yielded no changes in the ability of animals to detect targets (Paine et al., 2007) but did show increases in premature

29 responding or ISI touches. This evidence is consistent with general stimulatory effect of MK801.

At higher doses of MK801 in the 5CSRTT (0.25mg/kg), animals started showing impairments in accuracy and increases in omissions (Paine & Carlezon, 2009). This higher dose was not tested in the rTDT because of the likelihood of impaired coordination and locomotion.

When comparing the same dose of mecamylamine (5mg/kg) in the 5CSRTT and rTDT, both tasks showed impairments in the animal’s ability to detect targets (Jones et al., 1995).

Additionally, the increase in omissions in the 5CSRTT is consistent with animals having a bias against responding (increase in c, decrease in both HR and FAR) in the rTDT. Both tasks also showed a reduction in correct latency; together this is consistent with a general sedative effect. It should be noted that in our study the 5 mg/kg mecamylamine dose resulted in animals showing ptosis or a drooping of the eyelids. This effect was not mentioned in the 5CSRTT task, but in the

SAT task a higher dose mecamylamine (10 mg/kg) resulted in large increases in errors of omissions and long-lasting slowing of movement and ptosis (Turchi et al., 1995).

When comparing similar doses of scopolamine in the 5CSRTT (0.1-0.2mg/kg) and rTDT

(0.1-0.2mg/kg), the increase in omissions in the 5CSRTT is consistent with animal’s bias against responding (increase in C, decrease in both HR and FAR) in the rTDT. Studies with the 5CSRTT have sometimes shown decreases in accuracy which is consistent with the decrease in sensitivity

(d’) shown in the rTDT (Mirza et al., 2000; Robbins, 2002). When comparing similar doses of scopolamine in the 5C-CPT (0.3 mg/kg) and rTDT (0.2 mg/kg) both show decreases in sensitivity (d’) as a result of decreased responding to both targets and non-targets (increase in c).

It should be noted that although mecamylamine and scopolamine showed similar profiles in the rTDT, the higher dose of scopolamine did not result in ptosis and there were no significant

30 differences in either choice or retrieval latency. This indicates that the deficit caused by scopolamine cannot be explained by a purely sedative effect.

Patients with schizophrenia show a complex range of deficits in attentional processes

(further discussed in chapter 6). It is impossible to model a complex disease such as schizophrenia with an acute drug administration, but it is interesting to note that scopolamine in the rTDT had a similar profile to patients with schizophrenia tested in a reverse translated version of the 5C-CPT (J W Young et al., 2013). Patients with schizophrenia and rats challenged with scopolamine both showed decreases in sensitivity (d’) and hit rate. Unlike patients with schizophrenia our animals showed an increase in FAR and an increase in c. This difference could easily be explained by differences in perceptual demands between the two tasks.

Chapter 4: Effects of Elevated Gestational Kynurenine on Attention and Cognitive Control

4.1 Introduction

The introduction in chapter 1 outlined the criteria by which the embryonic kynurenine model was selected for the current work, but to confirm the validity of this model, a broader understanding of the behavioral consequences of prenatal elevations of kynurenine is needed.

4.1.1 Consequences of Elevated Embryonic Kynurenine

Elevations of kynurenine during gestation were shown to result in deficits in attentional processing and cognitive flexibility. Attentional processing was evaluated in the 5CSRTT which requires rats to divide attention across five stimulus locations. EKYN animals showed no significant differences in initial rate of task acquisition or response accuracy, but had an increased number of omission errors coupled with fewer anticipatory responses measured by responses during the inter-stimulus interval (Hahn et al., 2018). Cognitive flexibility was evaluated in the Attentional Set Shifting Task (ASST), a digging task that was designed to be analogous to the Wisconsin Card Sorting Task used in humans (Birrell & Brown, 2000). Food deprived animals learned to discriminate two pots differentiated by three sets of exemplars (three sensory modalities: digging material, smell, and texture). On the testing day, performance was measured as the number of trials required to reach criterion on seven stages. EKYN animals, compared to ECON animals, required more trials to reach criterion on the first reversal stage, in which the correct and incorrect exemplars within the same dimension are switched. EKYN 32 animals also required more trials to reach criterion on the extradimensional set shift in which the relevant and irrelevant modalities were switched (Pershing et al., 2015).

4.1.2 Rationale

Aim 1 provided not only a foundation for interpreting the results of rTDT, but evidence that the rTDT is sensitive to parametric manipulations that increase cognitive load and to acute disruptions of the neurochemical systems that underlie attentional processing. Of course, acute pharmacological challenge in intact animals cannot be expected to model a complex disease state such as schizophrenia given its neurodevelopmental origin. One such neurodevelopmental model that was previously used in the rTDT involves the administration of mitotic neurotoxin methylazoxymethanol acetate (MAM) to pregnant rat dams on gestational day 17. The MAM model produced robust decreases in d’, and increases in FAR, and ISI touches (refer to method section 2.6 for definitions of these parameters) during acquisition and baseline performance of the rTDT (Mar et al., 2017). These results are of interest, but it is necessary to test other models of schizophrenia in the rTDT. Unlike the artificial manipulation with an exogenous molecule in the MAM model, the Embryonic Kynurenine (EKYN) model is based upon a more naturalistic disruption of neurodevelopment via elevations of the endogenous molecule Kynurenic Acid

(KYNA). To date the EKYN model has been shown to induce broad monitoring deficits in the

5CSRTT (Hahn et al., 2018), but attentional tasks requiring attentional control have not directly been tested.

Hypothesis: If adult EKYN animals, who were exposed to elevated levels of kynurenic acid during gestation are tested in rTDT or the Maze Set Shifting task, then they will present with 33 impairments in attention and cognitive control consistent with the deficits found in patients with schizophrenia.

4.2 Methods

EKYN model animals and ECON controls were generated as described in section 2.2. On

PD3, maternal behavior was tested as described in section 2.3. Once reaching adulthood, animals were allocated to either KYNA tissue analysis (ECON N= 9, EKYN N=16), rTDT (ECON N=8,

EKYN N=8) or the Maze Set Shifting task (ECON N=8, EKYN N=8). Litter allocation of animals to each experiment is summarized in Table 2.

4.2.1 EKYN rTDT Parametric Challenge

Modifications of baseline task parameters were completed for two types of parametric challenge, the stimulus duration (SD) and stimulus contrast (SC) probe tests. The changes to stimulus parameters for each probe test are summarized in Table 4. For EKYN experiments

(Aim 2 and 3) there was no requirement for minimum d’ score. All animal groups completed 10 days of stage 4 under baseline conditions and then underwent six probe tests (In order: SD1,

SD2, SC1, SC2, SD3, SD4) separated by a single baseline session.

4.2.2 Statistical Analyses

All comparisons are between EKYN and ECON groups, unless otherwise noted. In the rTDT, the d’ sensitivity parameter was used to compare the general acquisition performance of the EKYN and ECON groups. A two-way RM ANOVA with Sidak multiple comparison tests was completed for d’ for Stage 3 and Stage 4 rTDT acquisition.

For the parametric challenge changes in d’ from baseline for the SD2 probe test were analyzed by an unpaired t-test. For the Maze Set Shifting task, trials to criterion for set 1, 2, and

3 were compared by two-way ANOVA with Sidak multiple comparisons test. Set 2 performance was additionally analyzed with unpaired t-tests to examine total number of errors, perseverative errors, and non-reinforced errors (Figure 16). Tissue levels of KYNA in prelimbic/infralimbic region of the PFC were compared by unpaired t-test. All statistical analysis was completed with

GraphPad Prism (Version 6.07).

4.3 Results

The major findings of chapter 4 are summarized in Table 5, which reveal that EKYN animals show deficits in both attention and cognitive flexibility when compared to ECON animals. Although EKYN animals show similar acquisition performance in the rTDT under baseline conditions, EKYN animals show deficits compared to ECON animals when challenged by reductions in stimulus duration. Although EKYN animals show similar acquisition of Set 1 in the Maze Shift Task, when challenged by an extradimensional shift, EKYN animals show deficits in cognitive flexibility compared to ECON animals.

4.3.1 Acquisition of rTDT task in ECON Controls and EKYN Animals Exposed to Prenatal Kynurenine

Our results show that EKYN and ECON animals have the same rate of acquisition for both stage 3 and stage 4 of the rTDT task. Task acquisition can be represented by increases in d’

(sensitivity) over multiple sessions. Figures 12 and 13 show that d’ increased over days for both

35 groups during Stage 3 (F7, 98 = 26.38, P = 0.0001) and Stage 4 (F9, 126 = 11.51, P= 0.0001). Note that the same animals are represented in each stage (n= 8 per group).

Stage 3 is the first and simplest stage where animals are required to discriminate target from non-target; therefore, rapid acquisition with large increases in d’ was expected. Figure 12 shows that performance improved from Day 1 to Day 8 in both ECON (Day 1: 0.46 ± .09 Day 8:

1.51 ± 0.15) and EKYN animals (Day 1: 0.34 ± .18 Day 8: 1.84 ± 0.2). Importantly, there are no overall differences between groups (P = 0.18) or groups as a function of day (P = 0.17).

Stage 4 is the final and most complex version of the task; therefore, slower acquisition approaching a performance ceiling was expected. Figure 13 shows that Performance improved from Day 1 to Day 10 in both ECON (Day 1: 0.82 ± 0.12 Day 10: 1.54 ± 0.13) and EKYN (Day

1: 0.67 ± 0.06 Day 10: 1.46 ± 0.15). Again, there were no significant differences between groups overall (P = 0.87) or groups as a function of day (P = 0.17). Following this assessment of baseline performance of the rTDT, the next step was to test whether the groups differed under increasing cognitive load.

4.3.2 The Effects of Increasing Cognitive Load on Performance of ECON and EKYN Animals in the rTDT Task

Reductions of stimulus duration (SD) and stimulus contrast (SC) were used to decrease stimulus detectability and to increase the cognitive load of the rTDT. Our results show that

EKYN animals, but not ECON controls, are vulnerable to these reductions in stimulus duration.

ECON and EKYN animals (n=8 per group) underwent a series of challenge sessions (SD1, SD2,

SC1, SC2, SD3, SD4) as summarized in Table 4. Data represent the difference in performance between the challenge session and the baseline of the previous day. Importantly, baseline performance was not significantly different for any of the performance measures; therefore, the baseline session prior to each challenge session was utilized as a standard baseline. Figure 14 shows the statistically significant effects of varying SD on measures of performance. Reductions of stimulus duration resulted in larger decreases in performance in the EKYN animals compared to the ECONS in the SD2 and SD3 sessions. There were no significant differences in the magnitude of decreased performance in ECON and EKYN animals during SD1, SC1, SC2, or

SD4. More specifically, Panel A shows that during SD2 the reduction in d’ is larger in the

EKYN animals (-0.71 ± 0.07) compared to the ECON animals (-0.26 ± 0.07; t = 4.433 df = 14, P

= 0.0006). Panel B shows that during SD2 the reduction in HR is larger in the EKYN animals (-

.24 ± 0.04) compared to the ECON animals (-0.11 ± 0.04; t = 2.23 df = 14, P = 0.0425). Panel C shows that during SD3 the reduction in d’ is larger in the EKYN animals (-0.72 ± 0.06) compared to the ECON animals (-0.34 ± 0.14; t = 2.43, P = 0.029). Also measured but not reported because there were no significant differences between groups: c (response bias), correct choice latency, incorrect choice latency, and retrieval latency.

4.3.3 Performance of ECON and EKYN Animals in the Plus Maze Set Shifting Task

Concurrently to rTDT experiments, in a separate group of animals, cognitive flexibility of EKYN and ECON animals was evaluated in the Plus Maze Set Shifting task. It was important to evaluate EKYN and ECON animals in the Set Shifting task in order to later study the effects of cognitive training with a fully crossed experimental design with task order counterbalanced. Our results demonstrate that the EKYN animals show deficits in 37 extradimensional set shifts whereas ECONs do not. An extradimensional and reversal set shifts were used to challenge the cognitive flexibility of animals. Figure 15 shows the number of trials animals (n=8 per group) took to reach criterion (8 consecutive correct choices twice) when completing an initial discrimination (Set 1), an extradimensional set shift (Set 2), and a reversal set shift (Set 3). There was an overall difference in groups (F1, 14 = 16.33, P = 0.0012) and group as a function of Set (F2, 28 = 3.81, P = 0.035). There were no significant differences between groups in learning the first discrimination (Set 1; P = 0.9912). EKYN animals took significantly more trials to reach criterion (70 ± 7) when performing an extradimensional set shift (Set 2) compared to ECON animals (40 ± 3; P = 0.0004). EKYN animals trended toward taking significantly more trials (66 ± 6) to reach criterion when performing a reversal set shift (Set 3) compared to ECON animals (49 ± 3; P = 0.055). Additionally, ECON animals required fewer trials to reach criterion when performing the extra-dimensional set shift (Set 2: 40 ± 3), compared to the initial discrimination (Set 1: 62 ± 3; P = 0.027). By comparison, EKYN animals did not show an improvement in performance going from Set 1 (64 ± 6) to Set 2 (70 ± 7). Further analysis was conducted to determine the distribution of errors made in Set 2.

Figure 16 shows that EKYN animals made more overall errors mainly as a result of an increase in perseverative errors. Figure 16 shows total errors and the breakdown of two possible types of error; perseverative errors and non-reinforced errors. In Panel A, EKYN animals made significantly more total errors (24 ± 3) than ECON (12 ± 1; t = 3.162, df = 9.44, P = 0.011) animals. In Panel B EKYN animals made significantly more perseverative errors (18 ± 3) than

ECON animals (11 ± 1; t = 2.386, df = 9.06, P = 0.041). In Panel C EKYN animals trended towards making more non-reinforced errors (6 ± 2) than ECON animals (2 ± 0.5; P = 0.0501).

4.3.4 Levels of KYNA in Prefrontal Tissue Homogenates from Adult Littermate Controls

Our results show that at the time of testing, KYNA levels were not elevated in EKYN animals compared to ECON animals. Figure 17 shows levels expressed as fm/mg of KYNA in tissue (ECON n = 9; EKYN n = 8; ECON Trained n = 8; EKYN Trained n=8). One EKYN animal was excluded from the data set because it was determined to be a statistical outlier via the

Grubbs Test (P = 0.05) The ECON and EKYN group samples were collected in adulthood

(postnatal day 56-80) from sentinel animals from the same litters that contributed to each behavioral task. ECON trained and EKYN trained group samples were collected following behavior (postnatal day 136-143) in the animals who completed training in the rTDT followed by testing in the Maze Set Shifting task. There was no overall effect of group (P = 0.1070). EKYN

Trained animals trended toward lower KYNA levels (14.7 ± 2.1) compared to ECON Trained animals (45.1 ± 16.9) but this effect did not reach statistical significance (P = 0.066). There were no significant differences in KYNA levels between the sentinel ECON animals (26.9 ± 3.3) and the sentinel EKYN animals (25.3 ± 4.0).

4.4 Discussion

Collectively these data show that EKYN animals, when compared to ECON animals, show normal task acquisition but present with deficits in attentional processes and cognitive flexibility when challenged with task parameters that enhance cognitive load in both the rTDT and the Maze Set Shifting task. This discussion section will focus on exploring the translational validity of the embryonic kynurenine animal model by comparing these results to the cognitive deficits presents in patients with schizophrenia. 39

In Figures 12 and 13 EKYN and ECON animals show improvement in acquisition performance in rTDT that is consistent with animals learning the task. Both ECON and EKYN animals show a similar pattern of increasing d’ during stage 4 (average range over 10 days: 0.74

– 1.5) compared to the intact cohorts used in aim 1 (intact cohorts 1 and 2 average range over 15 days: 0.97 – 1.52).

Figure 14 showed that EKYN animals were uniquely vulnerable to reductions in stimulus duration during SD2 and SD3 but show larger deficits than ECON animals during SD1, SD5 and during reductions of contrast SC1, SC2. It was expected that both ECON and EKYN animals would not show deficits during SD1 or SC1 since these manipulations did not cause deficits in the intact. What is surprising is that EKYN animals are more vulnerable to reductions in stimulus duration but not stimulus contrast. This would indicate that EKYN animal deficit presents as a reduction d’ from baseline as result of a decrease in HR with no change in FAR during conditions of enhanced cognitive load. This raises the question of why the increased magnitude deficit did not persist during the SD5. Examining the magnitudes of the decreases in d’ from baseline across each of stimulus duration tests (SD1, SD2, SD3, and SD4) reveals that lack of difference in SD4 is partially due to a larger magnitude decrease in ECON group, indicating during SD4 both groups have reached baseline level of decreased performance. Another possibility is that the EKYN deficit manifests with a completely variable stimulus presentation used in SD1-SD3 compared to SD4, which randomized presentation among only three values

(0.03, 0.06, 0.50 s).

To better understand the EKYN rTDT, it is important to compare our results to other rodent models of schizophrenia in the rTDT and to the human literature. MAM-E17 model

40 animals in the rTDT exhibited decreases in d’, increases in FAR and increases in ISI touches relative to sham controls across days during the acquisition of stage 4 of the rTDT (Mar et al.,

2017). These deficits in the MAM-E17 model persisted over several months of testing. This profile is very different from the deficits present in the EKYN animals, which did not present under baseline conditions but rather were only revealed under conditions of reduced stimulus duration. Additionally, the EKYN animals did not show any changes in the false alarm rate or

ISI touches. The EKYN deficit profile was more consistent with the performance of schizophrenic patients in reverse translated 5C-CPT (J W Young et al., 2013), which revealed deficits in sensitivity (d’) as a result of a reduction in target responses (HR) with no change in non-target responses (FAR). The attentional deficits present in schizophrenic patients are varied dependent on many factors including the task. Schizophrenic patients tested in the Identical Pairs version of the CPT (CPT-IP) demonstrated lower hit rate, higher false alarm rate and lower d’ compared to controls (Bismark et al., 2018).

Having discussed the effects of elevated gestational kynurenine on performance in the rTDT, the focus will now be shifted to the peformance of animals in maze shifting task as represented in Figure 15. EKYN and ECON animals were able to learn an initial discrimination

(Set 1), but EKYN animals compared to ECON animals showed deficits when challenged with an extradimensional set shift. These data replicate previous work in our lab which shows that

EKYN animals present with deficits in the extradimensional shift stage (Set 2) in the pots attentional set shifting task (Pershing et al., 2015). Figure 15 also shows a trend toward a deficit when EKYN animals are challenged with a reversal set shift. Interestingly, EKYN animals presented with a larger deficit in the reversal stage compared to the deficit in the

41 extradimensional shift stage of the pot attentional set shifting task (Pershing et al., 2015). The fact that EKYN animals show a more consistent deficit in the extradimensional shift is in line with the fact that patients with schizophrenia in the CANTAB ID/ED set shifting task sometimes show deficits in the extradimensional shift but not the reversal (Jazbec et al., 2007). This difference may be the result of the order in which each challenge was presented. In the Maze Set

Shifting task, the extradimensional shift stage occurs before the reversal while in the ID/ED task multiple reversals occur before the ED.

Figure 16 shows that EKYN animals show more total errors than ECON animals during the extradimensional set shift. This difference is partially driven by an increase in perseverative errors which is consistent with the types of errors that patients with schizophrenia make in the

Wisconsin Card Sorting Task (Li, 2004).

Collectively, our results further support the validity of the EKYN model. Having confirmed that EKYN animals present with deficits in attention in the rTDT and deficits in cognitive control in Maze Set Shifting task, it raised the question of whether there was a biomarker that would be predictive of the cognitive impairment. Thus, Figure 17 shows tissue levels of KYNA in two sets of EKYN and ECON animals: (1) In sentinel animals from the same litters that contributed to behavior collected at the time when littermates were starting behavioral testing (ages PD56-PD80); and (2) In the EKYN and ECON animals who underwent training in the rTDT followed by testing in the Maze Set Shifting task, collected following the end of behavioral testing (ages 136-143). Surprisingly, neither set showed differences between EKYN and ECON animals at the time of collection. This result did not replicate previous work in the lab that showed elevations of KYNA in EKYN animals compared to ECON animals (age PD56)

(Pershing et al., 2015), but this is not the first time our lab has not found differences in KYNA between EKYN and ECON animals (age ~PD56) (unpublished data: Valentini et al., 2017).

Further exploration of the literature reveals that the timeframe of elevations of KYNA in the

EKYN animals is complex. EKYN animals show elevations on gestational day 21, but no significant differences on PD 2 (Pershing et al., 2015). EKYN animals also show no significant differences on PD 32 (Pershing et al., 2016). One potential confound is that previous experiments used Wistar rats while the current work used Long Evans rats, which raises the possibility of cross-species differences in the timeframe of KYNA changes.

It is not surprising that the cognitive deficits in our EKYN animals persist in the absence of acute elevations of KYNA. In fact, the validity of the EKYN model is dependent on the damage to neurobiological systems that is a result of elevations of KYNA early in development. For example the negative allosteric modulation of KYNA upon α7nAChRs is particularly detrimental considering that early in development α7nAChRs are necessary for the normal formation of glutamatergic synapses (Lozada et al., 2012) and are involved in timing the transition of

GABAergic signaling from excitation to inhibition (Liu et al., 2006). There is also a plethora of evidence that suggests that disruption in excitatory/inhibitory balance, during key points in development, is an essential mechanism in the emergence of schizophrenia (D. Lewis, 1997).

Additionally, our lab has consistently found that the EKYN model presents with enduring biochemical, structural, and neurochemical deficits. EKYN animals compared to ECON animals showed decreases in the NR1 and NR2A subunits of the NMDA receptor (Pershing et al., 2016).

EKYN animals compared to ECON animals also displayed reductions in dendritic spine density on apical and basal dendrites in layer 2/3 of the medial prefrontal cortex (mPFC) (Pershing et al.,

2015). This is important considering that mPFC is an important part of the distributed system that underlies executive functions, including attention. Finally, mesolimbic evoked cortical glutamate, measured with a glutamate sensitive microelectrode array was significantly attenuated in EKYN animals compared to ECON animals (Pershing et al., 2015). Although these more sensitive biomarkers were outside the scope of the current work, there is little doubt that if tested, our EKYN animals would present with fundamental disruptions of both cholinergic and glutamatergic systems.

Although it is beyond the scope of this dissertation to determine the exact mechanism by which elevation of kynurenine during gestation cause deficits in cognition in adulthood, it is prudent to eliminate certain possible contributing factors. First, maternal body weights for ECON and EKYN dams were monitored over the course of gestation, and there were no significant differences between groups overall or group as a function of day. Second, Maternal Retrieval

Behavior was measured following the protocol published by Sabihi et al., 2014. There were no significant differences between ECON and EKYN dams in the latency to retrieve the first pup or the latency to retrieve all pups. Although this is only one measure of overall maternal care, it does provide initial evidence that maternal care differences are not responsible for the deficits seen in the EKYN animals. Third, anxiety like behavior was measured in the elevated plus maze, following the protocol published by Nelson & Lenz (2017). There were no significant differences between EKYN and ECON animals in anxiety-like behaviors. More specifically the time spent and the number of entries into the open and closed arms was not different between groups. Anxiety is a complex phenomenon, but this measure provides some evidence that the deficits present in the EKYN animals are not due to an anxiety effect.

Chapter 5: Efficacy of Cognitive Training in Reversing Attention and Cognitive Control Deficits

5.1. Introduction

The introduction in chapter 1 outlined the criteria by which cognitive training was selected as an alternative to pharmacological treatment strategies; however, to model cognitive training, a broader understanding of the literature will be needed for the selection of a task with the appropriate cognitive demands.

5.1.1 Selection of Tasks to Model the Effects of Cognitive Training

Given that there is some evidence that domain-specific cognitive training has limited efficacy for enhancing global cognition (Bosia et al., 2017), it was important to select a task that would have both attentional and cognitive control demands. One option considered was the

Attentional Set Shifting Task (ASST) (Birrell & Brown, 2000), a rodent digging task previously used in the lab to reveal deficits in cognitive flexibility in EKYN animals (Pershing et al., 2015).

Compared to a simple Visual Discrimination/Reversal Learning Task, the ASST challenges animals with reversals (relevant stimulus modality is the same, but the previously incorrect exemplar becomes the correct exemplar), and with extradimensional (ED) shifts (previously irrelevant stimulus modality becomes relevant stimulus modality). ED shift deficits have been shown in schizophrenic patients in the CANTAB ID/ED task (Turner et al., 2004). One problem with ASST that prevented its selection was that it requires animals to be food deprived.

Considering animals undergoing the rTDT are water deprived, this would introduce an additional unwanted confound to the experiment. Therefore the Plus Maze Set Shifting task, which has also been shown to be sensitive to manipulations that challenge cognitive flexibility (Stefani et al.,

2003; Stefani & Moghaddam, 2005) was adapted for use with water deprivation.

5.1.2 Rationale

Aim 2 examined the consequences of gestational exposure to kynurenine on the emergence of cognitive deficits in adulthood. EKYN animals presented with impairments in attentional processes in the rTDT and deficits in cognitive control in the Maze Set Shifting task. This provides a unique opportunity to evaluate the efficacy of cognitive training, via prior experience in a cognitively demanding task, to eliminate these deficits. A fully crossed design counterbalancing task order was essential to show whether the effect training is generalized to multiple tasks or if the effect is domain-specific.

Hypothesis: If cognitive training is an effective therapeutic option then either training in the

Maze Set Shifting task will be protective in EKYN animals subsequently tested in the rTDT, or training in the rTDT will be protective in EKYN animals subsequently tested in the Maze Set

Shifting task.

5.2 Methods

5.2.1 Cognitive Training Full Cross Experimental Design

A subset of EKYN animals underwent cognitive training. A fully crossed design was used in which animals were either trained in the Maze Set Shifting task and tested in the rTDT or trained in the rTDT and then tested in the Maze Set Shifting task. For each of two trained groups

(EKYN rTDT Trained N=8, EKYN Maze trained N=8), there were counterpart groups exposed to the experimental apparatus and stimulus reward pairing but was not trained in the task (EKYN rTDT exposed N=8, EKYN maze exposed N=8). The rTDT trained group underwent acquisition of stage 1-4 and all of the probe tests described in section 4.3.1. The rTDT non-trained group underwent only stage 1 (simple stimulus reward pairing) for 18 days. The EKYN Maze trained group completed Set 1-3 as described in section 2.9 but on day 7 underwent a 4th Set. Set 4 consisted of a second ‘extradimensional’ shift to the only stimulus that had not been correct during Set 1-3. The EKYN maze exposed group underwent 4 days of access to the maze in the open plus maze formation with water repeatedly added to all reward receptacles.

5.2.2 Statistical Analyses

All comparisons are between EKYN, ECON, EKYN trained (rTDT trained or maze trained), and EKYN exposed (rTDT exposed or maze exposed) not-trained groups, unless otherwise noted. In the rTDT the d’ sensitivity parameter was used to compare the general acquisition performance in a two-way RM ANOVA with Tukey multiple comparison for d’ for Stage 3 and stage 4 acquisition. For the parametric challenge, changes in d’ from baseline for the SD2 probe test were analyzed by one-way ANOVA with Sidak multiple comparisons, with individual unpaired t-tests between all EKYN groups. For the Maze Set Shifting task, trials to criterion for

Set 1, 2 and 3 were compared by two-way ANOVA with Sidak multiple comparisons tests. Set 2 performance was additionally analyzed with one-way ANOVA and Sidak multiple comparison tests to examine total number of errors, perseverative errors, and non-reinforced errors.

Perseverative errors were also analyzed with an unpaired t-test. All statistical analysis was completed with GraphPad Prism (Version 6.07). 47

5.3 Results

The major findings of chapter 5 are summarized in Table 6, which revealed that prior cognitive training but not exposure in the rTDT was protective against deficits in cognitive flexibility found in the Maze Set Shifting task in EKYN animals; in comparison, both training and exposure in the Maze Set Shifting task was protective against deficits found in attentional processing in the rTDT in EKYN animals. To study the effects of cognitive training, task order was counterbalanced generating two sets of EKYN animals: EKYN Maze trained and EKYN maze exposed (tested in the rTDT) and EKYN rTDT trained and EKYN rTDT exposed (tested in the Maze Set Shifting Task). First the effects of cognitive training in the Maze Set Shifting task on performance in the rTDT was evaluated. The following four groups were compared:

ECON/EKYN (no prior training), EKYN maze trained (trained in Set 1-4), and EKYN maze exposed (exposure to maze and water rewards only). Second the effects of cognitive training in the rTDT on performance in the Maze Set Shifting task was evaluated. The following four groups were compared: ECON/EKYN (no prior training), EKYN rTDT trained (trained in Stage

1-4 and stimulus duration and contrast probe test), and EKYN rTDT exposed (exposed to simple stimulus water reward pairing only). Although only the EKYN maze trained group showed improvements in acquisition performance compared to EKYN animals, both the maze training and maze exposure was protective of the attentional deficits present in the EKYN animals in the rTDT. Maze training but not maze exposure was protective of the deficits in Set 2

(extradimensional shift) and Set 3 (reversal) performance in EKYN animals.

,5.3.1 Effects of Prior Cognitive Training in the Maze Set Shifting Task on the - Acquisition of the rTDT Task in ECON and EKYN Animals

Our results show that cognitive training in Maze Set Shifting task in EKYN animals improved performance in stage 3, which in turn, resulted in a transient improvement in stage 4 of acquisition. Task acquisition can be represented by increases in d’ (sensitivity) over multiple sessions. Figures 18 and 19 show that d’ increased over days for all groups during Stage 3 (F7, 196

= 70.15, P = 0.0001) and Stage 4 (F9, 252 = 19.2, P= 0.0001). Note that the same animals are represented in each stage (n= 8 per group).

Stage 3 is the first and simplest stage where animals are required to discriminate target from non-target; therefore, rapid acquisition with large increases in d’ were expected. Figure 18 shows that performance improved from Day 1 to Day 8 in all groups: ECON (Day 1: 0.46 ± .09

Day 8: 1.51 ± .15), EKYN (Day 1: 0.34 ± .18 Day 8: 1.84 ± .2), EKYN maze trained (Day 1:

0.57 ± .07 Day 8: 2.51 ± 0.2) and EKYN maze exposed animals (Day 1: 0.28 ± .07 Day 8: 1.96 ±

0.17). Importantly, there were overall differences between groups (F3, 28 = 7.562, P = 0.0007) and a trend toward differences between groups as a function of day (P = 0.054). The EKYN maze trained group showed significantly higher d’ than the EKYN group (P = 0.02) or the EKYN maze exposed group (P = 0.03) across days. Additionally, the EKYN maze trained group was significantly higher d’ than the EKYN group on Day 2 (1.31 ± 0.16 vs 0.72 ± 0.17; P = 0.036) and day 8 (2.51 ± 0.2 vs 1.84 ± .2; P = 0.011), p-values corrected for multiple comparisons. The

EKYN maze trained group was also significantly higher than the EKYN maze exposed group on

Day 2 (1.31 ± 0.16 vs 0.71 ± 0.16; P = 0.031), Day 3 (1.82 ± 0.17 vs 1.2 ± 0.12; P = 0.022) and

Day 5 (2.12 ± 0.16 vs 1.44 ± 0.15; P = 0.011).

Stage 4 is the final and most complex version of the task, therefore slower acquisition approaching a performance ceiling was expected. Figure 19 shows that performance improved from Day 1 to Day 10 in all groups: ECON (Day 1: 0.82 ± .12 Day 10: 1.54 ± .13), EKYN (Day

1: 0.67 ± .06 Day 10: 1.46 ± .15) EKYN maze trained (Day 1: 1.19 ± .12 Day 10: 1.8 ± 0.17) and

EKYN maze exposed animals (Day 1: 1.1 ± .14 Day 10: 1.71 ± 0.19). There was an overall difference between groups (F3, 28 = 3.554, P = 0.027). Overall the EKYN maze trained animals

(Day 1: 1.19 ± .12 Day 10: 1.8 ± 0.17) trended (P=0.062) towards better performance than the

EKYN animals (Day 1: 0.67 ± .06 Day 10: 1.46 ± .15). The EKYN maze trained groups had better performance than the EKYN group on Day 1 (1.19 ± .12 vs 0.67 ± .06; P = 0.039) and Day

3 (1.6 ± 0.17 vs 1.09 ± 0.13; P = 0.038), p-values corrected for multiple comparisons. This improvement in performance did not persist to later days of acquisition. Following this assessment of baseline performance of the rTDT, the next step was to test whether the groups differed under increasing cognitive load.

5.3.2 Effects of Prior Cognitive Training in the Maze Set Shifting Task on Performance in the rTDT under Conditions of Enhanced Cognitive Load in ECON and EKYN Animals

Our results show that exposure to a novel environment with a reward stimulus pairing may be protective when EKYN animals are challenged with increasing cognitive load.

Reductions of stimulus duration (SD) and stimulus contrast (SC) were used to decrease stimulus detectability and to increase the cognitive load of the rTDT. Animals (n=8 per group) underwent a series of challenge sessions (SD1, SD2, SC1, SC2, SD3, SD4) as described in Table 4. Data represented the difference in performance between the challenge session and the baseline of the

50 previous day. Importantly baseline performance was not significantly different for any of the performance measures. Figure 20 shows the statistically significant effects of varying SD on measures of performance. Figure 20 shows an overall effect of group (F3, 28 = 5.77, P = 0.003), and more specifically shows that reduction of stimulus duration results in larger decreases in performance in the EKYN animals (-0.71 ± 0.07) compared to the ECON animals (-0.26 ± 0.07) during the SD2 session (P = 0.004). Additionally, EKYN animals showed larger decreases in performance (-0.71 ± 0.07) than the EKYN maze trained (-0.32 ± 0.09; P = 0.015) and the

EKYN maze exposed (-0.3 ± 0.11; P = 0.01) groups. There were no significant differences in the magnitude of decreased d’ in any of the groups during SD1, SC1, SC2, SD3 or SD4. Also measured but not reported because there were no significant differences between groups: c

(response bias), HR, FAR, correct choice latency, incorrect choice latency, and retrieval latency.

Animals that first underwent the rTDT (chapter 4 experiments) were then tested in the Plus Maze

Set Shifting task.

5.3.3 Effects of Prior Cognitive Training in the rTDT on Performance in the Plus Maze Set Shifting Task in ECON and EKYN Animals

Our results demonstrate that cognitive training in the rTDT can reverse the cognitive flexibility deficits found in the Maze Set shifting task that was present in EKYN animals. An extradimensional and reversal set shift were used to challenge animal’s cognitive flexibility.

Figure 21 shows the number of trials animals (n=8 per group) took to reach criterion (8 consecutive correct choices twice) when completing an initial discrimination (Set 1), an extradimensional set shift (Set 2), and a reversal set shift (Set 3). There was an overall difference in the EKYN, ECON, EKYN rTDT trained and EKYN rTDT exposed groups (F3, 28 = 13.44, P = 51

0.0001) and group as a function of Set (F6, 56 = 3.31, P = 0.0074). Set 1: There were no significant differences between groups in learning the first discrimination. Set 2: EKYN animals took significantly more trials (70 ± 7) to reach criterion when performing an extradimensional set shift than EKYN rTDT trained (37 ± 3; P = .0001) or ECON animals (40 ± 3; P = .0001).

Importantly the EKYN rTDT exposed group also took significantly more trials (64 ± 5) to reach criterion than the EKYN rTDT trained (37 ± 3; P = 0.0004) or the ECON group (40 ± 3; P =

0.0027) and was indistinguishable from the EKYN group (70 ± 7; P = 0.34). The EKYN rTDT trained group was not significantly different from the ECON group indicating a full recovery of the deficit. Set 3: EKYN animals took significantly more trials (66 ± 6) to reach criterion when performing a reversal set shift than EKYN rTDT trained (47 ± 3; P = 0.021) or ECON animals

(49 ± 3; P = 0.049). The EKYN rTDT exposed group also took significantly more trials (64 ± 5) than the EKYN rTDT trained (47 ± 3; P = 0.0244) and was indistinguishable from the EKYN group (66 ± 6; P = 0.99). The EKYN rTDT trained group was not significantly different from the

ECON group again indicating a full recovery of the deficit. Both ECON (P = 0.007) and EKYN rTDT trained animals (P = 0.044) required fewer trials to reach criterion when performing the extra-dimensional set shift (Set 2: 40 ± 3 and 37 ± 3), compared to the initial discrimination (Set

1: 62 ± 3 and 54 ± 3).

Further analysis was conducted to determine the distribution of errors made in Set 2.

Figure 22 shows total errors and the breakdown of two possible types of error; perseverative errors and non-reinforced errors. There was an overall difference in the EKYN, ECON, EKYN rTDT trained and EKYN rTDT exposed groups in total errors (F3, 28 = 3.607, P=0.0007), perseverative errors (F3, 28 = 5.026, P=0.007) and non-reinforced errors (F3, 28 = 2.348, P=0.01).

Figure 22 shows that cognitive training in the rTDT in EKYN animals resulted in fewer overall errors mainly as a result of fewer perseverative and non-reinforced errors. Panel A: EYN animals made significantly more total errors (24 ± 3) than ECON (12 ± 1; P = 0.016) animals. EKYN rTDT trained animals made significantly fewer total errors (9 ± 1) than EKYN animals (24 ± 3;

P = 0.0024) or EKYN rTDT exposed (22 ± 3; P = 0.011) animals. Panel B: EKYN animals trended towards making more perseverative Errors (18 ± 3) than ECON animals (11 ± 1; P =

0.086). EKYN rTDT trained animals made significantly fewer perseverative Errors (8 ± 1) than

EKYN animals (18 ± 3; P = 0.11) or EKYN rTDT exposed animals (17 ± 3; P = 0.028). Panel C:

EKYN animals made more non-reinforced errors (6 ± 2) than ECON animals (2 ± 0.5; P =

0.036). EKYN rTDT trained animals made significantly fewer non-reinforced errors (2 ± 0.3) than EKYN animals (6 ± 2; P = 0.029).

5.4 Discussion

Collectively these data show that cognitive training but not exposure in the rTDT was protective of the deficits in cognitive flexibility in the Maze Set Shifting task that were present in

EKYN animals. Interestingly this reversal effect was specific to training rather than exposure in the rTDT compared to the reversal of the attentional processing deficits in the rTDT, which was rescued by either training or exposure in the Maze Set Shifting task. This discussion section will focus on dissecting a possible explanation for this discrepancy and exploring how our results compare to the use of cognitive training in patients with schizophrenia.

In Figures 18 and 19 ECON, EKYN, EKYN maze trained and EKYN maze exposed animals showed improvements in acquisition performance in the rTDT that is consistent with animals learning the task. EKYN maze trained animals had significantly better performance than 53

EKYN Animals on stage 3 and trended toward better performance on stage 4. The fact that the

EKYN Maze trained group’s improvement in acquisition did not persist into the later days of stage 4 may be due to the temporal proximity of the maze training. It suggests that maze training had effect early on but as rTDT acquisition continued the effect of within-task training superseded benefits from the Maze.

Figure 20 shows that both Maze Training and Maze Exposure was protective of the deficit in d’ during the reduced stimulus challenge (SD2) in the EKYN animals. The fact that this recovery was not specific to cognitive training but occurred in the maze exposed group was unexpected, especially considering that there were no improvements in d’ during the acquisition of the rTDT in the maze exposed group. Further analysis of stage 4 acquisition data revealed overall significant effect of group across day in HR (F3, 28 = 10.84, P = 0.0001). Specifically, both the EKYN maze trained animals (P = 0.001) and EKYN maze exposed animals (P = 0.019) showed increased HR across days compared to the EKYN animals during stage 4 acquisition.

Since the deficit in d’ during SD2 was primarily driven by a decrease in HR, it’s possible that both the EKYN maze trained and exposed groups had reached a baseline HR that resulted in these animals being more resilient to challenge.

Figure 21 shows that ECON, EKYN, EKYN rTDT trained, and EKYN rTDT exposed showed similar ability to learn an initial discrimination (Set 1) but EKYN animals and EKYN rTDT exposed animals required more trials to reach criterion compared to ECON animals and

EKYN rTDT trained animals. The clear difference between EKYN rTDT trained vs EKYN rTDT exposed reveals that cognitive training specifically was required to reverse the deficits in cognitive flexibility present in the EKYN animals. Figure 22 shows that rTDT training but not

54 exposure reduces the total number of errors made during the extradimensional shift in EKYN animals. This overall reduction in errors was a result of the combined changed in perseverative and non-reinforced errors.

Chapter 6: General Discussion

6.1 Discussion

Collectively this dissertation has shown (1) that the rTDT has a stable and reproducible acquisition, is sensitive to increases in cognitive load via parametric challenge, and responds predictably to pharmacological challenges that are known to disrupt the neurochemical systems needed for attentional processing, (2) that EKYN animals, when compared to ECON animals, show normal task acquisition but present with deficits in attentional processing and cognitive flexibility when challenged with task parameters that enhance cognitive load in both the rTDT and the Maze Set Shifting task, and (3) that cognitive training in, but not exposure to, the rTDT was protective of the deficits in cognitive flexibility present in EKYN animals and that either cognitive training or exposure in the Maze Set Shifting Task was protective of deficits in attentional processing in the rTDT. This dissertation is the first to show rTDT deficits in a developmental model that uses naturalistic manipulations via endogenous molecules. The current work further validates the rTDT and the EKYN model and has utilized past cognitive experience as a proof-of-concept model showing the efficacy of cognitive training in adult animals. This discussion section will further address the translational validity of the rTDT attentional deficits, found in the EKYN animals, will speculate on what constitutes the essential components to effective cognitive training, and will outline possible future directions.

6.2 Translational Relevance of EKYN model and the rTDT

As described in section 3.1.1, attention is a complex cognitive construct that can be disrupted in a multitude of ways. To get a better understanding of how well EKYN animal performance in the rTDT models the attentional deficits present in schizophrenia, a broader understanding of the attentional deficits in schizophrenia is needed.

Human Continuous Performance Tasks (CPTs) represent a group of sustained attention tasks which collectively are the gold standard for evaluating deficits in attentional processing in schizophrenia. The major rodent attentional tasks (5CSRTT, 5C-CPT, DSAT) were inspired by human CPTs. CPTs typically focus on the discrimination of target and non-target stimuli under conditions that would induce a vigilance decrement. This vigilance decrement is dependent upon the type of discrimination and the event rate (See et al., 1995). Specifically, the type of discrimination refers to either successive stimulus presentations, in which individuals must maintain the target in working memory to compare it to subsequent stimulus presentations, or simultaneous stimulus presentations in which all information required to make a discrimination is present simultaneously. Event rate relates to two factors: the rate of stimuli presentation and the proportion of non-target to target stimuli; it is representative of the signal to noise ratio of the task. High event rates occur when there is a rapid rate of stimuli presentation with a bias towards non-target stimuli presentations. Vigilance decrements only occur under conditions of successive stimulus presentations with a high event rate (See et al., 1995). Typically, this involves a higher percentage of non-target presentations to target presentations. By comparison the rTDT has an equal probability of target and non-target presentation during normal trials. This difference is required to maintain the animal’s motivation to complete the task. The rTDT

57 attempts to compensate for this difference with the fact that every time a non-target is touched

(False Alarm) a correction trial is initiated which results in a 100% chance that the next stimuli is a non-target. Despite the inclusion of correction trials, the rTDT task parameters used in this dissertation were not optimal for detecting vigilance decrement. Therefore, it is not surprising that an initial analysis found no significant differences in vigilance decrement between the

EKYN and ECON animals.

This raises the question of whether the rTDT can fully capture the attentional deficits of schizophrenia. In fact, a review of 41 studies of sustained attention ability in patients with schizophrenia revealed that studies that used overall assessments of sustained attention (such as sensitivity, d’) yielded deficits, while studies that examined changes in sensitivity over time

(vigilance) did not find deficits (Hoonakker 2017). The fact the EKYN animals showed a larger decrease in overall d’ is, therefore, consistent with the deficit present in patients with schizophrenia. That being said, deficits in sustained attention over time have been found under specific conditions of degraded stimuli (Mass et al., 2000); although it has been suggested that the deficit in this particular study was the result of impaired perceptual processing rather than an attentional deficit. EKYN animals in the rTDT, compared to ECON animals, presented with an overall deficit in d’ only under conditions of reduced stimulus duration. The perceptual demands of reducing stimulus duration likely contribute to the deficits seen in EKYN animals, but the fact that EKYN animals do not show significant deficits with reductions in stimulus contrast, may suggest that the EKYN deficit is not simply a perceptual issue such as those that were found in the degraded stimuli study.

Another interpretation is that the EKYN attentional deficit in the rTDT is a deficit in attentional effort. Attentional effort is a construct that relates to the motivated activation of attentional systems especially in conditions that challenge attentional systems (Sarter et al.,

2006). Examples of challenges that would require increased attentional effort include: changes in stimulus presentation parameters (e.g. reductions in stimulus duration and stimulus contrast), the inclusion of distractors, prolonged task time, and/or changes in the overall state of the animal

(e.g. circadian disruption, stress, and sickness). The fact that both changes in stimulus duration and the state of the animal could be interacting to cause rTDT deficit is of interest. We have already provided some evidence that ECON and EKYN animals did not show differences in anxiety, but the fact that the rTDT attentional deficits in the EKYNs animals were reversed in both the EKYN Maze Trained and EKYN Maze Exposed groups raised the question of whether a reduction in anxiety could be contributing to the rescue of these deficits. Although additional experiments would be needed to confirm this hypothesis, we did find that there was an anxiolytic effect of training determined using the elevated plus maze. We found that EKYN and ECON animals who had been trained in both behavioral tests (rTDT followed by Maze Set Shifting task) showed increased time in the open arms and increased entries into the open arms compared to behaviorally naive EKYN and ECON animals tested in adulthood (~PD56). There were no significant differences between EKYN and ECON groups and no significant difference between

EKYN trained and ECON trained groups. It would be interesting to determine whether animals merely exposed but not trained in these tasks would also have reduced anxiety compared to behaviorally naïve animals.

An additional piece of evidence that mechanistically links the EKYN attentional deficits to deficits in attentional effort is the fact that cholinergic input to the prefrontal cortex is key in initiating the top-down cognitive control that is used to optimize the processing of stimuli under conditions of increased attentional effort {reviewed in (Sarter et al., 2006)}. As was covered in section 1.2, the development of cholinergic systems in EKYN animals is disrupted because early elevations of kynurenic acid in the EKYN results in the negative allosteric modulation of the alpha-7 nicotinic acetylcholine receptor (α7nAChR), which is key in the development of early cholinergic circuitry (Broide & Leslie, 1999). The link between early disruptions of the development of cholinergic circuitry and the attentional deficits seen in EKYN animals is further supported by the fact that animals with lesions of the basal forebrain cholinergic system have been shown to be sensitive to reductions in stimulus duration (Muir et al., 1994; Robbins et al.,

1989). The link between disruptions of cholinergic systems and the development of cognitive impairments in schizophrenia has been well established {reviewed in (Friedman, 2004)}. Of particular note is the fact that the number of α7nACh receptors have been shown to be reduced in patients with schizophrenia (Freedman et al.,1995) and the locus of the α7nACh receptor gene

(CHRNA7) has been genetically linked to the sensory processing deficits in schizophrenia (R.

Freedman et al., 1997). In summary, EKYN animal attentional deficits in the rTDT provide additional evidence for the construct validity of the EKYN model.

6.3 Mechanism of Cognitive Training

In comparison to pharmaceuticals, that often have a variety of off-target side effects, non- pharmacological psychotherapeutic treatment strategies have few risks and are, therefore, being suggested as a first line of treatment (Lambert et al., 2016). Although Cognitive Remediation 60

Therapy (CRT) has shown efficacy in patients with schizophrenia, little is understood about what the components of a successful training regimen are. It has been identified that the proportion of cognitive domains that can be returned to ‘normal’ performance may be a key factor in quality of life improvements. This suggests that training in domain-specific tasks may not be as effective as tasks that require a multitude of domains (Bosia et al., 2017). It has also been found that cognitive training targeted towards attention, memory, and language resulted in unique improvements in working memory compared to a computer-skills training control condition

(Kurtz et al., 2007b). Also, it has been shown that training focused on executive functions is most associated with improvements in daily function (Penadés et al., 2010). Considering these studies, it makes sense that training in the rTDT showed improvements exclusive to the EKYN rTDT trained group compared to EKYN exposed group. More specifically, it is likely the rTDT is well-suited for cognitive training because it puts large demands on many domains, including attention, cognitive control and perception. The current work supports that prior experience in these cognitive domains is sufficient to induce improvements in cognitive flexibility in the Maze

Set Shifting task. Many questions regarding the key components of cognitive training remain and additional studies will need to be done to determine whether a certain of length of training or a certain level of cognitive load is a necessary perquisite for efficacy. It would be interesting to determine the efficacy of a shorter version of the rTDT (with animals trained up to stage 3) in reversing the cognitive flexibility deficits in the Maze Set Shifting task present in the EKYNs.

Additionally, it would be of interest to explore whether training in the rTDT is effective in reversing deficits in other tasks or animal models.

6.4 Future Directions

In the immediate future, the next most important experiment would be to investigate a biomarker that is sensitive to the effects of cognitive training. Ideally, this would be a biomarker shown to be disrupted in EKYN animals compared to ECONs. One possibility is the expression of parvalbumin positive GABAergic interneurons. A lack of excitatory input onto GABAergic parvalbumin (PV) positive interneurons has been implicated in schizophrenia (Belforte et al.,

2010; D. A. Lewis et al., 2006; Lisman et al., 2008; Thomases et al., 2013). Also, a reduction in the expression of PV interneurons is one of the most consistently reproducible findings in postmortem studies of patients with schizophrenia {reviewed in (Gonzalez-Burgos et al., 2010)}.

Preliminary evidence has shown that EKYN animals compared to ECON animals show a lack of

GABAergic tone following adolescence (Unpublished Data; Tseng et al. 2014). Therefore, it would be expected that EKYN animals would present with reductions in PV expression.

Importantly, there already is some preliminary evidence that PV network plasticity may be affected by cognitive training (Donato, 2013).

In the far future, the current work could be expanded to examine methods to enhance the efficacy of cognitive training. Two routes that have emerged in the literature are (A) pharmacologically-augmented cognitive therapies (PACTs) and (B) prophylactic treatment in clinically high risk (CHR) individuals.

Combining pharmacological compounds with symptom-specific training has been well established in treatment strategies for recovery from brain injury or stroke {reviewed in

(Michalopoulou et al., 2013)}. In regards to treatment of psychiatric conditions, some proof of concept examples have emerged including the successful combination of fluoxetine or d-

62 cycloserine with exposure therapy for the treatment of acrophobia (Karpova et al., 2011; Ressler et al., 2004). Although it makes intuitive sense that cognitive enhancing agents may be more effective in patients that are cognitively engaged, finding an effective combination therapy for schizophrenia has proved challenging. For example, d-cycloserine combined with a CRT protocol, emphasizing auditory discrimination, resulted in better performance on the discrimination task, but did not generalize to a MATRICS cognitive battery (Cain et al., 2014).

Another study combining d-serine and CRT did not show any significant effect on global cognitive index (D’Souza et al., 2013). Modafinil combined with CRT also failed to produce a synergistic effect on cognitive or functional measures (Michalopoulou et al., 2015). These mixed results illustrate the need for further research to identify optimal combinations of drug, dose, and training regimen.

Prophylactic therapy or treatment during the prodromal period, requires selection criteria with accurate predictive value for conversion to psychosis. Unfortunately, even the well- established criteria such as the early initial prodromal state (EIPS) and cognitive disturbances

(COGDIS) have yielded relatively low conversion rates of 10% within 6 months and 40% within

3 years (Fusar-Poli, 2012; Schmidt et al., 2015; Schultze-Lutter et al., 2015). Given the relatively high rate of false-positives (CHR individuals that don’t develop schizophrenia), the lack of efficacy of non-antipsychotic agents, and evidence of elevated risk for adverse side effects of neuroleptics used during adolescence (Agius et al., 2012; Correll, 2008), psychotherapeutic interventions are preferred to pharmacological therapies as first line treatment strategies

(Lambert et al., 2016). Studies directly comparing the magnitude of cognitive training effects found larger effect size in younger patients compared to older patients (McGurk et al., 2008;

Wykes et al., 2009). CRT studies in CHR individuals have had mixed results showing either improvements or no significant difference from video game control subjects (Hooker et al.,

2014; Piskulic et al., 2015). CRT studies, conducted specifically during adolescence, similarly show neutral to positive results for cognitive enhancement and functional outcomes (Barlati et al., 2015; Holzer et al., 2014). While the use of CRT in CHR individuals is promising, the key components of successful training protocols needs to be elucidated.

6.5 Conclusions

The experiments in this dissertation demonstrate the validity of the rTDT for measuring deficits in attention and cognitive control. This work also further validates the EKYN model as a naturalistic developmental model of schizophrenia that produces translationally relevant deficits in attentional processes and cognitive flexibility. Finally, this work shows that the EKYN model can be used as a platform for modeling the efficacy of cognitive training; revealing that prior experience in a cognitively demanding task can be protective of translationally relevant deficits in another cognitively demanding task.

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APPENDIX A: TABLES AND FIGURES

Cognitive Domain (CNTRICS/MATRICS Human Task Domains) (CANTAB)s Rodent Tasks (NEWMEDS) 5 Choice Serial Reaction Time Continuous Task(5CSRTT), rodent Target Attention /Vigilance Performance task Detection Task (rTDT) Speed of Processing 5 Choice Reaction Time 5CSRTT, rTDT Contrast-contrast effect Perceptional Processing task rTDT Problem solving/reasoning Executive Control/ Intra/Extradimensional Visual Reversal Learning, Cognitive Flexibility Shift task, 5CSRTT, rTDT Continuous Trial-Unique Non- Spatial Working Matching to Location Task, Self- Working Memory Memory (SWM) Ordered Working Memory Task Paired Associates Visual Learning Learning Paired Associates Learning Verbal Recognition/Recall Verbal Learning Memory none Emotion Recognition Social Cognition Test none

Table 1. Summary of Tasks Associated with Cognitive Domains identified by CNTRICS and MATRICS The mission of NEWMEDs (Novel Methods leading to New Medications in Depression and Schizophrenia) initiative was to develop a clinical touchscreen battery analogous to the CANTAB (Cambridge Neuropsychological Test and Automated Battery) used in humans. The rodent Target Detection Task (rTDT) was selected by NEWMEDS as a task most analogous to human Continuous Performance tasks. The rTDT is a novel touchscreen task of sustained attention that requires animals to discriminate target from non-target stimuli that are presented successively one after another. Performance in the rTDT was identified as being sensitive to multiple cognitive domains including: Attention and Vigilance, Speed of Processing, and Executive Control. These cognitive domains were identified as being relevant to the cognitive deficits present in schizophrenia by the MATRICS (Measurement And Treatment Research to Improve Cognition In Schizophrenia) and CNTRICS (Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia) initiatives. Not listed in this table but utilized in this dissertation is the Maze Set Shifting task which is most analogous to the ID/ED task. The Maze Set Shifting task requires animals to discriminate between sets of sensory stimuli. Performance in the Maze Set Shifting task is most sensitive to cognitive flexibility.

Number of Animals Selected Experiment 1 pup/ litter used in behavior (A, B, C) + All animals who underwent rTDT Training KYNA Biochemistry followed by the maze set shift task (A) 1-2 pups/litter (A) rTDT trained -> Maze Set Shifting task 1 pup/litter (A, B) Maze Set Shifting task trained -> rTDT Maze Set Shifting task exposed not trained -> 1 pup/litter (A, B) rTDT rTDT exposed not trained -> Maze Set 1-2 pups/litter (C) Shifting task Cohorts Dams A 4 EKYN 4 ECON B 4 EKYN C 4 EKYN 4 ECON

Table 2. Distribution of Offspring of ECON and EKYN DAMs to Experimental Aims Starting on embryonic day 15, and continuing till birth, pregnant dams were fed wet mash dosed with 100mg/kg per day of kynurenine (Embryonic Kynurenine; EKYN) or unadulterated mash (Embryonic Control; ECON). Pups from EKYN and ECON litters were allowed to grow to adulthood and were then assigned to several experiments including: the rodent Target Detection Test (rTDT), the Maze Set Shifting task, and the assay of kynurenic acid (KYNA; metabolite of kynurenine) levels. Pup distribution was done to optimize even litter contributions and maximize the use of generated animals.

Table 3. Summary of Chapter 3 (Aim 1) Results: Validation of the rTDT Summary of Intact animal performance during acquisition, under baseline conditions, as well as following parametric and pharmacological challenges designed to enhance cognitive load in the rTDT. Acquisition was reported as d’ across days during stage 3 and stage 4 of the rTDT. Parametric challenge consisted of reductions of stimulus duration (Stimulus Duration 1: SD1= 0.5 – 1.0 s and Stimulus Duration 2: SD2 = 0.25 – 0.75 s) and stimulus contrast (Stimulus Contrast 1: SC1= 50% contrast and Stimulus Contrast 2: SC2 = 25% contrast). Pharmacological challenge consisted of acute injections of MK801 (0, 0.05, and 0.1 mg/kg), Mecamylamine (0, 1, and 5 mg/kg), and scopolamine (0, 0.1, and 0.2 mg/kg). Green font highlights a change in a performance measure that is indicative of an improvement in performance. Red font highlights a change in a performance measure that is indicative of a deficit in performance. For each section of the table if a performance measure is not reported it is because there were no significant interactions among any of the conditions. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001***, and P < 0.0001****.

Figure 5 and 6 Intact Cohort 1 Compared Intact Acquisition to Intact Cohort 2 d' Stage 3 Acquisition No Difference d' Stage 4 Acquisition No Difference Figure 7 Reduction of Stimulus Duration SD1 Compared to Baseline 1 SD2 Compared to Baseline 2 SD1 Compared to SD2 d' No Difference Decrease**** Decrease** HR No Difference Decrease*** No Difference FAR No Difference Increase* No Difference ISI Touches No Difference Increase** Increase*** Figure 8 Reduction of Stimulus Contrast SC1 Compared to Baseline 3 SC2 Compared to Baseline 4 SC1 Compared to SC2 d' No Difference Decrease**** Decrease**** HR No Difference Decrease* No Difference FAR No Difference Increase*** Increase** ISI Touches Increase** Increase** No Difference Figure 9 0.05 mg/kg Compared to 0.1 mg/kg Compared to 0.05 mg/kg Compared MK801 Vehicle Vehicle to 0.1 mg/kg c Decrease** Decrease** No Difference HR Increase* Increase* No Difference FAR Increase** Increase*** No Difference ISI Touches No Difference Increase** No Difference Retrieval Latency Decrease** Decrease** No Difference Figure 10 1 mg/kg Compared to 5 mg/kg Compared to 1 mg/kg Compared to Mecamylamine Vehicle Vehicle 5 mg/kg d' No Difference Decrease** Decrease* c No Difference Increase*** Increase*** HR No Difference Decrease**** Decrease*** FAR No Difference Decrease* Decrease** Correct Latency No Difference Increase*** Increase** Retrieval Latency No Difference Increase** Increase** Figure 11 0.1 mg/kg Compared to 0.2 mg/kg Compared to 0.1 mg/kg Compared Scopolamine Vehicle Vehicle to 0.2 mg/kg d' No Difference Decrease** No Difference c No Difference Increase** Increase** HR No Difference Decrease*** Decrease** FAR No Difference No Difference Decrease*

Stimulus Parameters Baseline Conditions Stimulus Duration (SD) SD = 0.5 – 1.5s Stimulus Contrast (SC) SC = 100%

Probe Test (Duration) Change Stimulus Duration Stimulus Duration 1 Probe SD1 = 0.5 – 1.0 s Stimulus Duration 2 Probe SD2 = 0.25 – 0.75 s Stimulus Duration 3 Probe SD3 = 0.1 – 0.3 s Stimulus Duration 4 Probe SD4 = 0.03, 0.06, 0.50 s

Probe Test (Contrast) Change Stimulus Contrast Stimulus Contrast 1 Probe SC1 = 50% Contrast Stimulus Contrast 2 Probe SC2 = 25% Contrast

Table 4. Summary of Parametric Challenge Parameters Baseline represents the standard stimulus condition during the final version of the task (stage 4). Baseline stimulus duration occurred over a range of values with an average stimulus length of one second. Baseline contrast represents the maximum discrimination between white and black, as the contrast is reduced the stimulus becomes greyer and it is harder to differentiate white from black. During reduced stimulus duration challenge sessions reductions of stimulus duration occurred over a range of values randomized across trials with the following average stimulus lengths: SD1 0.75 s, SD2 0.5 s and SD3 0.2 s. Challenge session SD4 was limited to the three listed values randomized across trial. During reduced stimulus contrast challenge sessions the stimulus for all trials is 50% grey (SC1) and 75% grey (SC2).

Figure 12 and Figure 13 rTDT Acquisition EKYN Compared to ECON d’ Stage 3 Acquisition No Difference d’ Stage 4 Acquisition No Difference Figure 14 rTDT Reduction of Stimulus EKYN Compared to ECON Duration SD2 Difference in d’ from Baseline Larger Magnitude Decrease*** SD2 Difference in HR from Baseline Larger Magnitude Decrease*** SD3 Difference in d’ from Baseline Larger Magnitude Decrease*** Figure 15 Set Shifting Trials to Criterion EKYN Compared to ECON Set 1 No Difference Set 2 Extradimensional Shift Increase*** Set 3 Reversal Trend Towards Increase P = 0.055 Figure 16 Set Shifting Errors Set 2 EKYN Compared to ECON Total Errors Increase* Perseverative Errors Increase* Non-Reinforced Errors Trend Towards Increase P = 0.0501

Table 5. Summary of Chapter 4 (Aim 2) Behavior Results: Effects of elevating Kynurenine during Gestation Summary of outcomes of rTDT, and Maze Set Shifting task in EKYN and ECON animals. Performance during acquisition, under baseline conditions, as well as following parametric challenges designed to enhance cognitive load in the rTDT. Acquisition was reported as d’ across days during stage 3 and stage 4 of the rTDT. Parametric challenge consisted of a series of reductions of stimulus duration and stimulus contrast (SD1, SD2, SC1, SC2, SD3, and SD4) described in Table 4. Performance in the Maze Set Shifting task was reported as trials to criterion to complete Set 1, Set 2 (extradimensional shift) and Set 3 (reversal) and errors during Set 2. Red font highlights a change in a performance measure that is indicative of a deficit in performance. For each section of the table if a performance measure is not reported it is because there were no significant interactions between groups. Significance denoted as P < 0.05* and P < 0.001***.

Figure 18 and 19 EKYN Maze Trained EKYN Compared to EKYN Maze Trained EKYN Maze Exposed rTDT Acquisition Compared to EKYN ECON Compared to EKYN Compared to EKYN Maze Exposed d' Stage 3 Acquisition No Difference Increase* No Difference No Difference Trend Towards Increase P = d' Stage 4 Acquisition No Difference No Difference No Difference 0.062 Figure 20 EKYN Maze Trained rTDT Reduction of EKYN Compared to EKYN Maze Trained EKYN Maze Exposed Compared to EKYN Stimulus Duration ECON Compared to EKYN Compared to EKYN Maze Exposed SD2 Difference in d' Larger Magnitude Smaller Magnitude Decrease* Smaller Magnitude Decrease* No Difference from Baseline Decrease** SD2 Difference in HR No Difference No Difference No Difference No Difference from Baseline SD3 Difference in d' No Difference No Difference No Difference No Difference from Baseline Figure 21 EKYN rTDT Trained Set Shifting Trials To EKYN Compared to EKYN rTDT Trained EKYN rTDT Exposed Compared to EKYN Criterion ECON Compared to EKYN Compared to EKYN rTDT Exposed Set 1 No Difference No Differences No Differences No Differences Set 2 Extradimensional Increase*** Decrease**** No Differences Decrease* Shift Set 3 Reversal Increase* Decrease* No Differences Decrease* Figure 22 EKYN rTDT Trained Set Shifting Errors Set EKYN Compared to EKYN rTDT Trained EKYN rTDT Exposed Compared to EKYN 2 ECON Compared to EKYN Compared to EKYN rTDT Exposed Total Errors Increase* Decrease** No Difference Decrease* Trend Towards Increase P = Preservative Errors Decrease* No Difference Decrease* 0.086 Non-Reinforced Errors Increase* Decrease* No Difference No Difference

Table 6. Summary of Chapter 5 (Aim 3) Behavior Results: Effects of Cognitive Training Summary of outcomes in the rTDT (comparisons between ECON, EKYN, EKYN maze trained, and EKYN Maze exposed animals) and Maze Set Shifting task (comparisons between ECON, EKYN, EKYN rTDT trained and EKYN rTDT exposed animals). Performance during acquisition, under baseline conditions, as well as following parametric challenges designed to enhance cognitive load in the rTDT. Acquisition was reported as d’ across days during stage 3 and stage 4 of the rTDT. Parametric challenge consisted of a series of reductions of stimulus duration and stimulus contrast (SD1, SD2, SC1, SC2, SD3, and SD4) described in Table 4. Performance in the Maze Set Shifting task was reported as Trials to Criterion to complete Set 1, Set 2 (extradimensional shift) and Set 3 (reversal) and errors during Set 2. Green font highlights a change in a performance measure that is indicative of an improvement in performance. Red font highlights a change in a performance measure that is indicative of a deficit in performance. For each section of the table if a performance measure is not reported it is because there were no significant interactions among groups. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001***, and P < 0.0001****.

Schizophrenia:

Figure 1. Schematic of Disruptions of the Kynurenine Pathway (KP) of Tryptophan Degradation in Patients with Schizophrenia

Kynurenine (KYN) which is derived from tryptophan is the bio-precursor to Kynurenic Acid (KYNA) which is produced exclusively in astrocytes. Big arrows indicate the changes in the Kynurenine Pathway (KP) that occur in patients with schizophrenia. In Schizophrenia increases in kynurenine coupled with decreased expression of Kynurenine 3-Monooxygenase shifts the KP pathway towards the overproduction KYNA acid, in astrocytes. KYNA once produced automatically is released acting as a negative allosteric modulator of the Alpha-7 Nicotinic Receptor and at higher concentration an antagonist of the glycine b-site of the NMDA receptor.

Figure 2. Summary of Experimental Design Aim 1 is a validation of the Rodent Target Detection task (rTDT) in intact animals. Aim 2 compares Embryonic Kynurenine (EKYN) and Embryonic Control (ECON) animals in the rTDT and the Maze Set Shifting Task. Aim 3 examines the effects of cognitive training via prior task experience. EKYN animals tested in Aim 2 continue become the EKYN trained animals in Aim 3. The experiment in Aim 3 uses a fully crossed design with task order counterbalanced. Not listed in this summary is the assay of kynurenic acid levels which occurs in (1) behavior naïve sentinel littermates to the EKYN and ECON animals used in Aim 2 (brains collected ~PD 56) (2) EKYN ECON animals who completed rTDT training followed by Maze Set Shifting testing (brains collected after completion of behavior; PD136-143). A description of the protocols for each tasks are covered in the chapter 2 (methods).

Figure 3. Schematic of Stage 4 of Rodent Target Detect Task (rTDT) and Signal Detection Theory Measures Represented is a schematic of the final stage of the (rTDT). In the rTDT normal trials start with the presentation of either the target stimulus (50% chance) or one of four possible non-targets (50% chance). During baseline task conditions stimulus presentation occurs for a randomized range of durations (between 0.5-1.5 s). Animals have the duration of the Limited Hold (LH) period to respond. Responding inside the stimulus box outside of the LH during the inter- stimulus interval (ISI; no stimulus is present) is counted as an ISI touch. There are four categories of stimulus response that animals can make. Touching the target is a hit (only response that gives water reward), failure to touch the target is a miss, withholding response to non-targets is a correct rejection, and touching non-targets is a false alarm (only response that triggers correction trials). During correction trials there is a 100% chance of a non-target presentation. Hits and misses are used to calculate the Hit Rate (HR). False alarms and correct rejections are used to calculate the False alarm rate (FAR). Both HR and FAR are used to calculate signal detection theory measures including; d’ a parametric measurement of sensitivity, or an animals ability to discriminate targets from non-targets (higher d’ = better performance), and c a parametric measurement of the response bias, or the likelihood that animals will respond or not respond to both the target and non-targets (increases in c = bias against responding, decreases in c = bias towards responding). Sessions last 45 minutes in which animals perform anywhere from 250 to 350 trials. Measures not listed include: correct latency which is the amount of time from stimulus presentation to a correct response, incorrect latency is the amount of time from stimulus presentation to an incorrect response, retrieval latency is the amount of time from a correct response to the retrieving the water reward. Animals are water deprived (22hr/day) prior to each rTDT session.

Figure 4. Schematic of Maze Set Shifting Task Depicted is a description of the Maze Set Shifting task protocol. Animals learned a series of discriminations or sets associated with two stimulus modalities, brightness (light vs dark) and texture (rough vs smooth). During the testing one of the four arms is blocked this turn the maze into a T-maze configuration as pictured at the top. Animals start in the middle arm of the ‘T’ and then proceed to make a 90 degree turn to either the left or right arm. If the animals travels to the end of the correct arm they are rewarded with water. Animals are water deprived prior to each Maze Set Shifting task session. Sets were completed every other day. To reach criterion animals had to make 8 consecutive correct choices in a row on two occasions (either separate or consecutive). The text describes a representative order of correct arms for each set. Which arms that were correct for each set was fully counterbalanced across animals. The image shows green checkmarks for correct choices for each set and red x’s for each incorrect choice for each set. Perseverative errors occur when the animal makes an error during Set 2 going into an arm that was previously rewarded in Set 1. Non-reinforced errors occur when the animal makes an error during Set 2 going into an arm that was previously not rewarded during Set 1. For each trial the start arm is randomized and the maze is rotated to prevent the animal form using position cues to determine the correct answer. In between trials animals are placed in a holding cage (not pictured) for approximately 15 seconds.

Figure 5. Acquisition of Stage 3 of the rTDT in Intact Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. There is an increase in d’ over days but there is no overall difference between intact cohorts nor any interaction as a function of day (n= 17 animals or rats/cohort)

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Figure 6. Acquisition of Stage 4 of the rTDT in Intact Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. There is an increase in d’ over days but there is no overall difference between intact cohorts nor an interaction as a function of day (n= 17 per cohort, same animals as Figure 5)

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Figure 7. Effects of Reduced Stimulus Duration on the Performance of Intact Animals in the rTDT Shown are data (mean ± SEM) from two challenge days Stimulus Duration 1 (SD1= 0.5 - 1.0 s) and Stimulus Duration 2 (SD2 = 0.25 - 0.75 s) and the baseline sessions of the previous day (baseline 1, baseline 2). Different measures of performance are indicated in each panel. Baseline 1 and 2 are not statistically different for any measure. Panel A: d’ was significantly reduced during SD2 compared to baseline 2 and was also reduced compared to SD1. Panel B: HR was significantly reduced during SD2 compared to baseline 2 but was not different from SD1. Panel C: FAR was significantly increased following SD2 as compared to baseline 2 but was not different from SD1. Panel D: ISI touches were significantly increased during SD2 when compared to baseline 2 and were also higher compared to SD1. Also measured but not depicted: c, correct choice latency, incorrect choice latency, and retrieval latency because there were no significant differences between baseline and challenge sessions. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001***, and P < 0.0001****.

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Figure 8. Effects of Reduced Stimulus Contrast on the Performance of Intact Animals in the rTDT Shown are data (mean ± SEM) from two challenge days Stimulus Contrast 1 (SC1= 50% contrast) and Stimulus Contrast 2 (SC2 = 25% contrast) and the baseline sessions of the previous day (baseline 3, baseline 4). Different measures of performance are indicated in each panel. Baseline 3 and 4 are not statistically different for any measure. Panel A: d’ was significantly reduced during SC2 compared to baseline 4 and was also reduced compared to SC1. Panel B: HR was significantly reduced during SC2 compared to baseline 4 but was not different from SC1. Panel C: FAR was significantly increased during SC2 compared to baseline 4 and was also higher compared to SC1. Panel D: ISI touches were significantly increased during SC1 compared to baseline 3, but were not different compared to SC2. ISI touches were also significantly increased during SC2 when compared to baseline 4. Also measured but not depicted: c, correct choice latency, incorrect choice latency, and retrieval latency because there were no significant differences between baseline and challenge sessions. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001***, and P < 0.0001****.

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Figure 9. Effects of acute MK801 on the Performance of Intact Animals in the rTDT Shown are data (mean ± SEM) from the vehicle (saline), lower (0.05mg/kg) and higher dose (0.1mg/kg) injections of MK801 (n= 17, Animals from cohort 1). Different measures of performance are indicated in each panel. Panel A: C was significantly reduced with the lower or higher dose of MK801 compared to vehicle. Panel B: HR was significantly increased with the lower or higher dose of MK801 compared to vehicle. Panel C: FAR was significantly increased with lower or higher dose of MK801 compared to vehicle. Panel D: ISI touches were significantly increased with higher dose of MK801 when compared to vehicle. Panel E: Retrieval latency was significantly lower with the lower or higher dose of MK801 compared to vehicle. Also measured but not depicted: d’, correct choice latency, and incorrect choice latency, because there were no significant differences between vehicle and either the lower or higher dose of MK801. Significance denoted as P < 0.05*, P < 0.01** and P < 0.001***.

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Figure 10. Effects of acute Mecamylamine on the Performance of Intact Animals in the rTDT

Shown are data (mean ± SEM) from the vehicle (saline), lower (1 mg/kg), and a higher dose (5 mg/kg) injections of mecamylamine (n= 17, Animals from cohort 1). Different measures of performance are indicated in each panel. Panel A: d’ was significantly reduced with the higher dose of mecamylamine compared to vehicle or the lower dose of mecamylamine. Panel B: c was significantly increased with the higher dose of mecamylamine compared to either vehicle or the lower dose of mecamylamine. Panel C: Hit Rate was significantly decreased with the higher dose of mecamylamine compared to either vehicle or the lower dose of mecamylamine. Panel D: FAR was significantly decreased with higher dose of mecamylamine compared to either vehicle or the lower dose of mecamylamine. Panel E: Correct choice latency was significantly higher with higher dose of mecamylamine compared to either the vehicle or the lower dose of mecamylamine. Panel F: Retrieval latency was significantly higher with the higher dose of mecamylamine compared to either the vehicle or the lower dose of mecamylamine. Also measured but not depicted: ISI touches and incorrect choice latency because there were no significant differences between vehicle and either the lower or higher dose of mecamylamine. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001*** and P < 0.0001****.

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Figure 11. Effects of acute Scopolamine on the Performance of Intact Animals in the rTDT Shown are data (mean ± SEM) from the vehicle (saline), lower (0.1 mg/kg) and higher dose (0.2 mg/kg) injections of scopolamine (n= 9, Animals from cohort 2). Different measures of performance are indicated in each panel. Panel A: d’ was significantly reduced with the higher dose of scopolamine compared to vehicle. Panel B: c was significantly increased with higher dose of scopolamine compared to either vehicle or the lower dose of scopolamine. Panel C: HR was significantly decreased with higher dose of scopolamine compared to either vehicle or the lower dose of scopolamine. Panel D: FAR was significantly decreased in the higher dose of scopolamine compared to the lower dose of scopolamine but not compared to vehicle. Also measured but not depicted: ISI touches, correct choice latency, incorrect choice latency, and retrieval latency because there were no significant differences between vehicle and either the lower or higher dose of scopolamine. Significance denoted as P < 0.05*, P < 0.01** and P < 0.001***.

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Figure 12. Acquisition of Stage 3 of the rTDT in EKYN and ECON Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. There is an increase in d’ over days but there is no overall difference between groups nor any interaction as a function of day (n= 8 per group).

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Figure 13. Acquisition of Stage 4 of the rTDT in ECON and EKYN Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. There is an increase in d’ over days but there is no overall difference between groups nor any interaction as a function of day (n= 8 per group; Same animals as Figure 12).

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Figure 14. Effects of Reduced Stimulus Duration on Performance of ECON and EKYN animals in the rTDT Data represent (mean ± SEM) the difference in performance (mean ± SEM) during the Stimulus Duration 2 (SD2 = 0.25 - 0.75 s) and Stimulus Duration 3 (SD3= 0.1 - 0.3 s) challenge sessions and the baseline session of the previous day (n= 8 per group). Different measures of performance are indicated in each panel. Panel A: d’ during SD2 was significantly reduced in the EKYNs compared to the ECONs. Panel B: HR during SD2 was significantly reduced in the EKYNs compared to the ECONs. Panel C: d’ during SD3 was significantly reduced in the EKYNs compared to the ECONs. Also measured but not depicted: c (responsivity), FAR, ISI touches, correct choice latency, incorrect choice latency, and retrieval latency because there were no significant differences between groups. Also, not depicted, there were no significant differences between groups during SD1 and SD4. Significance denoted as P < 0.05*, and P < 0.001***.

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Figure 15. Effects of Set Shifts on Performance of ECON and EKYN animals in the Plus Maze Set Shifting Task Data represent the number of trials (mean ± SEM) to pass the criterion, 8 correct choices in a row twice, in ECON and EKYN animals (n= 8 per group). Animals underwent 3 days of testing in which they learned 3 sets for choosing the reward arm. Set 1 consisted of a discrimination between textures (rough and smooth) or brightness (light or dark). Set 2 required the animals to perform an extradimensional (ED) set shift in which the previously irrelevant modality (from Set 1) became relevant. Set 3 required animals to perform a reversal (REV) in which the previously incorrect arm of the same modality (from Set 2) became the correct arm. Set 1: There was no significant differences between groups. Set 2: EKYN animals required significantly more trials to reach criterion compared to ECON animals. Set 3: There was a trend towards EKYN animals requiring more trials to reach criterion compared to ECON animals, but this effect did not reach statistical significance. Significance denoted as P < 0.001***.

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Figure 16. Extradimensional Set Shifts Errors of ECON and EKYN animals in the Plus Maze Set Shifting Task Data represent the number errors (mean ± SEM) made prior to reaching the criterion of 8 correct choices in a row twice in ECON and EKYN animals (n= 8 per group). Perseverative Errors occur when the animal makes an incorrect choice that follows the rule of Set 1. Non-reinforced errors occur when animals make an incorrect choice and enters the arm that was not rewarded in the previous set. Panel A: EKYN animals made significantly more total errors than ECON animals. Panel B: EKYN animals made significantly more perseverative errors than ECON animals. Panel C: EKYN animals trended towards making more non-reinforced errors than ECON animals, but this effect did not reach statistical significance. Significance denoted as P < 0.05*.

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Figure 17 Brain KYNA Acid Levels in ECON and EKYN animals Data represent the levels (mean ± SEM) of KYNA in homogenates from the prelimbic and infralimbic regions of the prefrontal cortex (ECON n= 9; EKYN n= 8; ECON Trained n= 8; EKYN Trained n= 8). The ECON and EKYN group samples were collected in adulthood (postnatal day 56-80) from sentinel animals from the same litters that contributed to each behavioral task. ECON trained and EKYN trained group samples were collected following behavior (postnatal day 136-143) in the animals who completed training in the rTDT followed by testing in the Maze Set Shifting task. EKYN Trained animals trended toward lower KYNA levels compared to ECON Trained animals but this effect did not reach statistical significance. There were no significant differences between ECON and EKYN sentinel animals or compared to either trained group.

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Figure 18. Effects of Cognitive Training on the Acquisition of Stage 3 of the rTDT in ECON and EKYN Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. All groups show an increase in d’ over days (n= 8 per group). Overall the EKYN maze trained group shows a higher d’ than the EKYN, or the EKYN maze exposed group. Additionally, there were group differences as a function of day. On days 2 and 8 the EKYN maze trained group had better performance compared to the EKYN group. On days 2, 3 and 5 the EKYN maze trained group had better performance compared to the EKYN maze exposed group.

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Figure 19. Effects of Cognitive Training on the Acquisition of Stage 4 of the rTDT in ECON and EKYN Animals Data represent d’ (sensitivity; mean ± SEM) over days as an expression of task acquisition. All groups show an increase in d’ over days (n= 8 per group). Overall there was a trend towards increased performance of the EKYN trained group compared to the EKYN group but this effect did not reach statistical significance. Although there were no significant differences between groups overall, there were group differences as a function of day. On days 1 and 3 the EKYN maze trained group had better performance compared to the EKYN group. Significance denoted as P < 0.05*.

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Figure 20. Effects of Cognitive Training on the Performance of ECON and EKYN Animals in the rTDT During Reduced Stimulus Duration Data represent the difference in d’ (sensitivity; mean ± SEM) during the Stimulus Duration 2 (SD2 = .25-.75 s) challenge session and the baseline session of the previous day. The decrease in d’ was significantly higher in the EKYNs compared to the ECONs (n= 8 per group). Both the EKYN maze trained and Maze exposed groups showed a smaller decrease in d’ than the EKYN group. Also measured but not depicted: c (responsivity), HR, FAR, ISI touches, correct choice latency, incorrect choice latency, retrieval latency because there were no significant differences between groups. Significance denoted as P < 0.05* and P < 0.01**.

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Figure 21. Effects of Cognitive Training on Performance of ECON and EKYN Animals in the Plus Maze Set Shifting Task

Data represent the number of trials (mean ± SEM) required to pass the criterion of 8 correct choices in a row twice in ECON and EKYN animals (n= 8 per group). Animals underwent 3 days of testing in which they learned 3 sets for choosing the reward arm. Set 1 consisted of a discrimination between textures (rough and smooth) or brightness (light or dark). Set 2 required the animals to perform an extradimensional (ED) set shift in which the previously irrelevant modality (from Set 1) became relevant. Set 3 required animals to perform a reversal (REV) in which the previously incorrect arm of the same modality (from Set 2) became the correct arm. Set 1: There were no significant differences between groups in acquiring Set 1. Set 2: EKYN animals required significantly more trials to reach criterion compared to ECON animals. EKYN rTDT trained groups took significantly fewer trials to reach criterion and were indistinguishable from the ECON group. Importantly the EKYN rTDT exposed group was not significantly different from the EKYN group and took significantly more trials to reach criterion than the EKYN rTDT trained or ECON groups. Set 3: EKYN animals required significantly more trials to reach criterion compared to ECON animals. EKYN rTDT trained groups took significantly fewer trials to reach criterion and were indistinguishable from the ECON group. Importantly the EKYN rTDT exposed group was not significantly different from the EKYN group and took significantly more trials to reach criterion than the EKYN rTDT trained group. Significance denoted as P < 0.05*, P < 0.01**, P < 0.001***, and P < 0.0001****.

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Figure 22. Effects of Cognitive Training on Extradimensional Set Shift Errors in ECON and EKYN Animals in the Plus Maze Set Shifting Task Data represent the number of errors (mean ± SEM) made prior to reaching the criterion of 8 correct choices in a row twice in ECON and EKYN animals (n= 8 per group). Perseverative Errors occur when the animal makes an incorrect choice that follows the rule of Set 1. Non- reinforced Errors occur when the animal makes an incorrect choice and enters the arm that was not rewarded in the previous set. Panel A: EKYN animals made significantly more total errors than ECON animals. The EKYN rTDT trained group made significantly fewer total errors than the EKYN group or the EKYN rTDT exposed group. Panel B: EKYN rTDT trained animals made significantly fewer perseverative errors than the EKYN group or the EKYN rTDT exposed group. Panel C: EKYN animals made significantly more non-reinforced errors than ECON animals. The EKYN rTDT trained group made significantly fewer non-reinforced errors than the EKYN group. Significance denoted as P < 0.05* and P < 0.01**.

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B. C.

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