Neural Substrates of Cue Reactivity: Association with Treatment Outcomes and Relapse
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bs_bs_banner INVITED REVIEW doi:10.1111/adb.12314 Neural substrates of cue reactivity: association with treatment outcomes and relapse Kelly E. Courtney1, Joseph P. Schacht2, Kent Hutchison3, Daniel J. O. Roche1 & Lara A. Ray1,4 Department of Psychology, University of California, Los Angeles, CA, USA1, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA2, Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA3 and Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA4 ABSTRACT Given the strong evidence for neurological alterations at the basis of drug dependence, functional magnetic resonance imaging (fMRI) represents an important tool in the clinical neuroscience of addiction. fMRI cue-reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. Thus, this review summarizes the research that has applied fMRI cue-reactivity paradigms to the study of adult substance use disorder treatment responses. Studies utilizing fMRI cue-reactivity paradigms for the prediction of relapse and as a means to investigate psychosocial and pharmacological treatment effects on cue-elicited brain activa- tion are presented within four primary categories of substances: alcohol, nicotine, cocaine and opioids. Lastly, sugges- tions for how to leverage fMRI technology to advance addiction science and treatment development are provided. Keywords Addiction, cue reactivity, fMRI, medication development, substance use disorder, treatment. Correspondence to: Lara A. Ray, Department of Psychology, University of California, 1285 Franz Hall, Box 951563, Los Angeles, CA 90095-1563, USA. E-mail: [email protected] INTRODUCTION and, after repeated drug use, the development of incen- tive salience to stimuli associated with these substances The clinical neuroscience of substance use disorders (Berridge & Robinson 1998; Berridge & Kringelbach (SUDs) is predicated on knowledge gained from animal 2008). Chronic drug use is known to alter various neuro- models of addiction, which suggest that dysfunction of transmitter systems and synaptic structure within these the brain systems underling motivated, goal-directed networks, leading to impairments in motivational drive behavior, as well as networks responsible for the inhibi- and sensitized conditioned responses to drug-related cues tory control of such behaviors, is a fundamental compo- (Kalivas & Volkow 2005), including cue-induced craving nent of the neurological alterations subserving the for the substance (Wise 1988; Berridge & Robinson development of SUDs (Kalivas & Volkow 2005). These 1998; Kauer & Malenka 2007). Furthermore, dysfunc- models suggest that motivated, goal-directed behavior is tion of higher cortical areas responsible for the regulation represented in the brain by an interconnected network of motivational drives, including the lateral orbitofrontal of areas, such as the ventral tegmental area (VTA), ven- cortex (OFC), inferior frontal gyrus (IFG), dorsolateral tral striatum (VS), ventromedial prefrontal cortex prefrontal cortex (dlPFC) and dorsal anterior cingulate (vmPFC), amygdala, lateral hypothalamus and hippo- cortex (ACC) (Bechara 2005; Koob & Volkow 2010), campus, that rely primarily on dopamine, GABA, opioid may aid in the progression to compulsive substance use and glutamate signaling (Kalivas & Volkow 2005; Nestler in later stages of addiction potentially by synergizing defi- 2005; Kauer & Malenka 2007). This network is thought ciencies in the function of the reward/motivation system to be responsible for the acute rewarding effects of drugs (Lubman, Yücel & Pantelis 2004; Kalivas 2009). of abuse (Berridge & Kringelbach 2008; Le Merrer et al. Given the strong evidence for neurological alterations 2009), the goal-directed behavior and exertion of effort at the basis of drug dependence (e.g., Goldstein & Volkow in attaining these drugs (Salamone & Correa 2012) 2011; Parvaz et al. 2011; Volkow et al. 2012), functional © 2015 Society for the Study of Addiction Addiction Biology 2 Kelly E. Courtney et al. magnetic resonance imaging (fMRI) represents an impor- (Drummond et al. 2000; Perkins 2009). Thus, fMRI-based tant tool in translating these preclinical insights to brain cue-reactivity paradigms are well positioned to advance function in humans affected by addictive disorders. While our understanding of the involvement of neurobiological there has been a focus on developing fMRI-based bio- pathways subserving the reward/motivation system in markers for psychiatric disorders in general (Fu & addiction and offer a translational platform by which inter- Costafreda 2013), the field of addictions has yet to identify ventions and behavioral predictions can be tested. reliable biomarkers, fMRI based or otherwise. Importantly, This review focuses on research that has applied fMRI diagnostic and prognostic biomarkers are only as useful as cue-reactivity paradigms to the study of adult SUD treat- their ability to add value to existing clinical and behav- ment responses. Based on the conceptual framework that ioral systems. With that in mind, one promising notion has evolved over the last two decades, pharmacological is that understanding addiction neurobiology at the level and psychosocial treatments are hypothesized to influ- of individual brain function will allow the development ence brain activation within the reward/motivation and of more efficacious psychosocial and pharmacological inhibitory networks (via bottom–up and/or top–down interventions. In particular, it has been argued that neu- control over these regions), which, in turn, is thought ropsychological and pharmacological therapies for addic- to predict treatment success and relapse propensity. As tion must target affected brain circuits, particularly the such, research utilizing fMRI cue-reactivity paradigms reward/motivation network (Konova, Moeller & Goldstein for the prediction of relapse is reviewed, and psychosocial 2013). Thus, fMRI represents a promising avenue to not and pharmacological treatment effects on cue-elicited only enable identification of these dysfunctional neurolog- brain activation are presented within four primary ical mechanisms underlying addiction but also to poten- categories of substances: alcohol, nicotine, cocaine and tially serve as an objective and quantifiable measure for opioids. Lastly, future directions for how to leverage fMRI evaluating changes associated with treatment beyond technology to advance addiction science and treatment what can be gathered from self-report or behavior alone development are proposed. (Menossi et al. 2013). Cue reactivity is one of the longest-studied phenotypes in substance use research, and several recent meta- PREDICTION OF RELAPSE FROM analyses (Chase et al. 2011; Engelmann et al.2012; CUE-ELICITED ACTIVATION Schacht, Anton & Myrick 2013a) and reviews (Yalachkov, Kaiser & Naumer 2012; Jasinska et al. 2014) summarize To date, 11 studies have examined prospective associa- the neuroimaging literature on this phenotype, including tions between brain activation and relapse among indi- a variety of individual difference variables that affect it. viduals dependent on alcohol, nicotine and cocaine; Because addiction neurobiology, and cue reactivity in par- nine of which employed drug-cue reactivity paradigms ticular, has a strong learning and memory component (see Table 1). However, several issues cloud interpreta- (Robinson & Berridge 1993; Kalivas & Volkow 2005), the tion of these findings and hinder efforts to synthesize this presentation of drug cues appears to reliably produce acti- literature. First, quantifications of relapse have varied vation of neural circuits involved in learning and memory, widely across studies. In general, breath tests for exhaled as well as brain regions associated with the aforementioned carbon monoxide and urine drug screens conducted reward/motivation network, such as the VS, amygdala, with varying frequency have been used to define nico- PFC, cingulate, precuneus and the insula (Camara et al. tine and cocaine relapse, while alcohol relapse is fre- 2009; Engelmann et al. 2012; Schacht et al.2013a).In quently captured only by patient self-report; however, a theory, greater cue-induced craving in the laboratory recent study in non-treatment-seeking alcohol drinkers should predict greater risk for relapse when similar cues suggests self-report data are highly consistent with bio- are faced in the natural environment, and in turn, a markers of alcohol intake (Simons et al. 2015). Second, therapy’s ability to blunt cue-induced craving in the labo- most studies have implicitly endorsed an abstinence- ratory should be a proxy marker of that treatment’sreal based treatment model, defining relapse as any subse- world efficacy (Marlatt 1990; Drummond 2000; Monti, quent substance use; re-initiation of heavy use has not Rohsenow & Hutchison 2000). These ideas are consistent been well studied. Third, many studies have compared with the notion of craving as a translational phenotype in baseline neuroimaging data between dichotomized addiction, which is exemplified by the recent addition of groups of patients who either relapsed to any use or craving as a symptom in the fifth edition of the Diagnostic remained abstinent;