Neural Correlates of Cue Reactivity and the Regulation of Craving in Substance Use Disorders
Abstract
Abstract.Theoretical background: Considerable progress has been made in illuminating the neural basis of the compulsive use patterns characterizing substance use disorders. It has been suggested to utilize these findings to alleviate the health burden associated with substance use. Objective: We address how neuroimaging research can provide these benefits. Methods: Based on neurobiological models of addiction, we highlight neuroimaging research elucidating neural predictors of relapse and how treatments modify these markers. Results: With the focus on cue reactivity, brain activity related to the motivational salience of drugs and automatized use behaviors can predict relapse. Cue reactivity changes with abstinence, and it remains to be determined whether such changes confer periods of critical relapse susceptibility. Conclusions: Several established and emerging interventions modulate brain activity associated with drug value. However, executive deficits in addiction may compromise interventions targeting control-related prefrontal brain areas. Lastly, it remains more difficult to change the brain responses mediating habitual behaviors.
Zusammenfassung. Theoretischer Hintergrund: Es wurden beträchtliche Fortschritte im Verständnis der neuronalen Grundlagen der für Substanzkonsumstörungen charakteristischen kompulsiven Konsummuster erzielt. Diese Erkenntnisse könnten genutzt werden, um die mit dem Substanzkonsum verbundene gesundheitliche Belastung zu mindern. Fragestellung: Wir untersuchen, wie neurobiologische Forschung zu diesem Ziel beitragen kann. Methoden: Basierend auf neurobiologischen Modellen der Sucht beleuchten wir Arbeiten, die neuronale Prädiktoren von Rückfallen identifizieren und zeigen, wie Interventionen diese Marker verändern. Ergebnisse: Es zeigt sich, dass Cue Reactivität im Zusammenhang mit der motivationalen Bedeutung von Drogen und automatisiertem Konsumverhalten Rückfalle vorhersagen kann. Cue Reactivität verändert sich mit Abstinenz, und es bleibt zu klären, ob solche Veränderungen die Rückfallanfälligkeit beeinflussen. Schlussfolgerungen: Mehrere etablierte und neuere Interventionen modulieren Gehirnaktivität, die mit dem Anreizwert von Drogen assoziiert ist. Exekutivdefizite könnten die Wirkung von Interventionen beeinträchtigen, welche die Nutzung kontrollrelevanter präfrontaler Hirnareale erfordern. Schließlich ist es nach wie vor schwieriger Gehirnaktivität zu verändern, die habituelle Verhaltensweisen mediiert.
Addiction imposes a considerable health burden (Degenhardt et al., 2018), emphasizing the need to understand its etiology, effective prevention, and treatment. Substance use disorders (SUDs) in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) and substance dependence in the International Statistical Classification of Diseases (ICD-11; World Health Organization, 2019) are characterized by impaired control over use, tolerance, and withdrawal. The DSM-5 further lists risky use and social impairments as criteria for SUDs; the ICD-11 specifies preoccupation with use as a criterion for substance dependence. Consistent with the dimensionality of SUDs, we use the terms “addiction” and “moderate-to-severe SUDs” synonymously.
Etiological models of addiction have to explain – and treatment approaches are challenged to modify – a compulsive pattern of persisting use despite negative consequences. However, addiction treatment does not yield fully satisfactory results (Brandon et al., 2007), implying the need and potential for improvement. Neurobiological research on drug use has elucidated the neural mechanisms of addiction (Berridge & Robinson, 2016; Everitt & Robbins, 2016; Volkow et al., 2016), and it has been suggested to apply these insights to advance our understanding of how and why treatments work (Morgenstern et al., 2013). Thus, the aims of this review are twofold: First, we relate the neurobiological mechanisms of addiction; second, we explore how neurobiological research may inform prognosis and explain how psychological interventions work.
The Neurobiology of Addiction
Volkow et al. (2016) conceptualize addiction as a three-stage, maladaptive cycle. The “binge / intoxication stage” is characterized by escalated use and widespread, substance-specific neuroadaptations, including synaptic function and structure in diverse transmitter systems and the macrolevel neuronal architecture (Volkow et al., 2019). It is now largely established that, while substances vary in their initial targets and transmitter cascades (Volkow et al., 2019), dopamine release in the ventral striatum (VS) is a correlate of drug reward (Nutt et al., 2015). Meta-analyses show downregulation of the dopamine reward system with protracted use of stimulants (Ashok et al., 2017), alcohol and opioids (Kamp et al., 2019), but not nicotine or cannabis (Kamp et al., 2019; Proebstl et al., 2019). This is associated with craving (Heinz et al., 2004, 2005), suggesting that drug use is maintained despite weakened neural reward effects. According to Volkow et al. (2016), the downregulation of reward systems generalizes, dampening the sensitivity to natural reinforcers. Of note, the dopamine system may recover through abstinence (e. g., Rominger et al., 2012), and the focus on dopamine for all drugs has been questioned (Nutt et al., 2015).
Protracted use yields further adaptations, i. e., overactive stress regulation (corticotropin-releasing factor), downregulation of dopamine function (dynorphin; Volkow et al., 2016), and, prominently documented for alcohol, alterations of (excitatory) glutamate and (inhibitory) GABA systems (Heinz et al., 2009). This shift is challenged by removing drugs from the system (detoxification), triggering the “withdrawal stage,” involving enhanced stress reactivity and dampened dopamine reward signals (Volkow et al., 2016). Alcohol cessation involves a hyperglutamatergic state – potentially combined with delayed recovery of GABA receptors (Garbusow et al., 2014) – yielding overexcitations that contribute to withdrawal symptoms (Heinz et al., 2009). Drug use may be continued to attain relief.
The “preoccupation / anticipation stage” is characterized by intense drug cravings that may trigger relapse (Volkow et al., 2016). Impairments facilitate this in the prefrontal cortex, which supports executive functions and is affected by dopaminergic and glutamatergic dysregulation. Similarly, the impaired response inhibition and salience attribution model assumes an imbalance between high-incentive salience ascribed to drug-predictive stimuli and disinhibition of ensuing drug-related impulses (Goldstein & Volkow, 2011). Other authors have emphasized the role of habits in pathological drug use, which are linked to the recruitment of the dorsal striatum (DS; caudate body and putamen; Everitt & Robbins, 2016). In sum, impaired executive functioning, craving, and inflexible drug habits drive drug intake despite intentions to remain abstinent.
Cue Reactivity
An important field of study examines associative learning between intoxication events and stimuli linked to these experiences (places, people, internal states). Pairing these neutral stimuli with unconditioned drug responses renders them conditioned stimuli eliciting conditioned responses, e. g., regarding motivation (craving) or arousal (skin conductance; see seminal meta-analyses by Carter & Tiffany, 1999). The withdrawal model (Siegel, 1975) claims that cues can elicit conditioned compensatory responses that counteract drug reactivity and evoke withdrawal-like states in the absence of drugs (distinct from withdrawal after discontinued use); the appetitive-motivational model (Stewart et al., 1984) posits that cues are incentive signals of future drug reward (reviewed in Heinz et al., 2009). A shift in dopaminergic firing away from drug administration and toward cue delivery (Volkow et al., 2006) has been described, suggesting decreased drug effects and increased neural activity evoked by drug-predictive stimuli. The importance of cues for pathological drug use has also been emphasized in models, e. g., focusing on incentive salience (Berridge & Robinson, 2016) or stimulus-response habits (Everitt & Robbins, 2016).
Cue reactivity (CR) describes a heightened psychological (e. g., craving, approach bias) and physiological (e. g., arousal, brain responses) sensitivity to drug-related stimuli. CR tasks confront drug users with drug-related stimuli, and dependent variables of interest (e. g., craving, brain activity) are compared to reactions to non-drug-related stimuli. Several meta-analyses have examined brain-based CR (briefly reviewed below).
The striatum, amygdala, anterior cingulate cortex (ACC), medial prefrontal cortex (PFC), posterior cingulate cortex (PCC), and insula were linked to smoking CR (Kühn & Gallinat, 2011; Lin et al., 2020). Craving was associated with activity in the insula, ACC, and PCC (Kühn & Gallinat, 2011). The VS, ACC, medial and lateral PFC showed alcohol CR (Kühn & Gallinat, 2011). Zeng et al. (2021) indicated alcohol CR in the PFC, insula, PCC, angular gyrus, superior parietal and occipital cortex, and cerebellum. Patients with alcohol use disorder (AUD) vs. healthy controls showed enhanced activity in the PCC, precuneus, and superior temporal gyrus (Schacht et al., 2013) and the medial PFC and ACC (Zeng et al., 2021). Further, whereas Kühn and Gallinat (2011) observed that VS activity correlated with craving, Zeng et al. (2021) failed to find brain activity associated with craving1. Meta-analyses of CR across substances found commonalities in the DS, PCC, medial frontal and temporal cortex (Noori et al., 2016) and in the ACC, VS, PCC, amygdala, occipital, parietal and precentral cortex (Hill-Bowen et al., 2021). Heterogeneity across substances notwithstanding, this work suggests CR in regions linked to reward (VS), salience processing (ACC / medial PFC, insula), habits (DS), self-referential processing (PCC), and control (lateral PFC).
Neurobiological Models of Change Through Treatment
A key contribution to improving addiction treatments may lie in determining mediators for treatment response by elucidating how treatments work, i. e., understanding the mechanisms of behavior change by studying the neural processes facilitating interventions (Morgenstern et al., 2013). Another goal is to examine for whom treatments work to better understand moderators (biomarkers) of treatment success (Garrison & Potenza, 2014). Knowledge of the relevant neurobiological processes (mediators) may help match individuals to appropriate interventions.
Neurobiological imbalance models, claiming that impaired prefrontal inhibition networks cannot counteract the pathologically high salience of drugs (Goldstein & Volkow, 2011), have been suggested as a promising starting point (Morgenstern et al., 2013) to explain treatment-related changes. Accordingly, benefits are expected from interventions enhancing control-related prefrontal networks, reducing drug and drug cue-induced activity, and strengthening connectivity between prefrontal and subcortical regions.
Moderators I
Predicting Clinical Outcomes From Cue Reactivity
Courtney et al. (2016) reviewed the association between neural CR and relapse for alcohol, tobacco, cocaine, and opioids. Several studies indicate the predictive utility of (mostly increased) CR for relapse. This entailed the dorsolateral and medial PFC, striatum, amygdala, insula, and PCC, with little regional consistency across or within substances. In a similar review, Moeller and Paulus (2018) emphasized the role of medial PFC and VS in predicting relapse and low treatment adherence. Recent individual studies ascribed the predictive utility of CR for relapse risk to the striatum, insula, medial and dorsolateral PFC, and ACC for nicotine (e. g., Allenby et al., 2020), alcohol (e. g., Bach et al., 2020), stimulants (e. g., Regier et al., 2021), and opioids (e. g., Li et al., 2015). Particularly, a link between striatal CR and relapse emerged as a recurring theme. However, the meta-analysis by Zeng et al. (2021) did not identify relapse-related alcohol CR. A cross-substance meta-analysis found that activity in the rostral-ventral ACC was predictive of better outcomes (Forster et al., 2018), but only when combining CR and substance-unrelated paradigms. Investigated separately, brain activity from (heterogeneous) substance-unrelated tasks (insula, claustrum, and DS) but not from (homogeneous) CR predicted relapse. Thus, the heterogeneous literature on CR-related neural predictors of relapse may benefit from considering interactions with markers from other domains (e. g., stress, cognition).
Moderators II
Changes in Cue Reactivity During Abstinence
Using CR to predict clinical outcomes assumes that the preabstinence interval is critical for the subsequent clinical trajectory. However, the lag between predictor and outcome grows with time and the preabstinence indicator may change. For instance, cue-induced craving can intensify after withdrawal, i. e., an “incubation of craving” (Bedi et al., 2011). In analogy, we review how cue reactivity evolves with abstinence.
Female tobacco users showed increased CR in ACC, PCC, caudate and frontal, temporal, and parietal cortices, and a decrease in the hippocampus, after an average of 8 days of abstinence compared to a prequit scan (Janes et al., 2009, but see Bradstreet et al., 2014). CR in AUD patients receiving psychosocial withdrawal treatment increased in the putamen, pallidum, and thalamus from 3 – 5 weeks after initiating abstinence (Bach et al., 2020). A group with additional anticraving medication did not show this effect. In contrast, CR in adolescent heavy drinkers compared to controls was increased in the ACC and cerebellum, but this difference disappeared after 1 month of abstinence (Brumback et al., 2015). In a cross-sectional sample of patients with cocaine use disorder (CUD), the cue-evoked centroparietal EEG response was highest in those abstinent for 1 and 6 months (vs. 2 days and 1 year), whereas craving decreased linearly (Parvaz et al., 2016). However, this pattern did not emerge in longitudinally assessed CUD patients (Parvaz et al., 2017). In the study by Moeller et al. (2018), CR did not differ between currently using and abstinent (median 1 year) CUD patients. In contrast, He et al. (2018) observed higher CR in the DS, thalamus, and lateral PFC in currently-using compared to abstinent (1 – 30 years) patients with CUD. Short-term (1 – 2 months) but not long-term (20 months) abstainers with methamphetamine use disorder showed higher CR than controls in the ventromedial PFC (Chen et al., 2020).
Short-term (1 month) vs. long-term (1 year) abstainers with heroin use disorder showed higher CR in the hippocampus, insula, thalamus, DS, PCC, cerebellum, and the temporal, parietal, and occipital cortices (Lou et al., 2012). Similarly, Li et al. (2013) observed higher CR in the ACC, medial PFC, caudate, occipital cortex, inferior parietal lobule, and precuneus in short-term (1 month) versus long-term (6 months) heroin abstainers. In the study by Wang et al. (2014), patients with opioid use disorder undergoing methadone maintenance treatment for less than 1 year (8 months) vs. more than 2 years (30 months) showed higher CR in the caudate.
Mediators
Psychological Interventions Modulating Cue Reactivity
Major tools of cognitive-behavioral therapy are relapse prevention, i. e., handling situations with high relapse risk, and coping skills, e. g., regulating cue-induced urges (Dutra et al., 2008). Emulating the latter, neuroimaging studies of the regulation of craving (ROC) train participants to apply psychological strategies during cue presentation (imagining the long-term risks of drug use; Kober et al., 2010). Downregulation of craving was accompanied by attenuation of the VS, insula, ACC, PCC, and ventromedial PFC, and increased recruitment of prefrontal areas in smokers, alcohol patients, and cocaine abusers (Kober et al., 2010; Suzuki et al., 2020; Tabibnia et al., 2014; Volkow et al., 2010). A link between higher PFC activity and lower craving was mediated by reduced VS activity (Kober, Mende-Siedlecki et al., 2010). Interestingly, real-time neurofeedback, using readouts from cue-related brain regions, can support ROC (reviewed in Martz et al., 2020).
Interestingly, a pattern of results similar to the ROC was observed when alcohol cues were accompanied by MI-derived statements derived from motivational interviewing favoring (drugs causing family issues) vs. opposing (drugs not a personal problem) change (Ewing et al., 2011), suggesting potentially common mechanisms across intervention types.
Cue-exposure therapy (CET) involves repeated confrontation with drug cues to foster the extinction of associations with drug reward. CET yielded reduced alcohol CR in the VS, DS, ACC, PCC, insula, and other regions (Kiefer et al., 2015; Vollstädt-Klein et al., 2011), and reduced amygdala CR in smokers (McClernon et al., 2007). Relatedly, within-session CR habituation may be of clinical relevance, as cocaine users with lower habituation showed poorer clinical outcomes (Regier et al., 2021).
Cognitive bias modification alters automatic drug tendencies. For instance, the retraining approach bias incrementally augmented alcohol treatment (Eberl et al., 2013). Medial PFC activity related to the alcohol approach could be reduced by training (Wiers, Ludwig et al., 2015). This training yielded reduced amygdala activity measured in a CR task with different cues than those used for training, and this change ran parallel to craving reductions (Wiers, Stelzel et al., 2015). However, recent work in adolescents failed to show a change in cannabis CR (Karoly et al., 2019), such that translating the promising results for alcohol to other substances still poses a challenge for future research.
Mindfulness involves nonjudgmental attention to thoughts and feelings and could serve as a coping skill for craving or relapse prevention when facing lapse-related guilt (Witkiewitz et al., 2014). Those who reduced CR in the PCC pre- to postmindfulness training also smoked less (no main effect of training on PCC; Janes et al., 2019). Training mindfulness also yielded reduced CR in the VS and ACC (Froeliger et al., 2017). Mindfully attending to smoking cues vs. uninstructed viewing reduced CR in the ACC and attenuated its connectivity with the insula and VS (Westbrook et al., 2013).
Conclusions
Moderators
A unified biomarker of cue processing to reliably enhance prognosis is still lacking. However, the wealth of individual results on the predictive utility of CR indicates that CR readouts could inform prognostic assessments for specific substances, in certain subgroups or even individuals when this becomes affordable. For instance, cue-evoked activity associated with anticipated drug reward (VS) or habit formation (DS) could reflect potential biomarkers identifying those with increased need for relapse prevention. Thus, treatments modifying how patients handle drug cues could be strengthened by specifically targeting the reward incentives and automatic tendencies associated with cues. Indeed, these neurobiological insights suggest that the degree to which striatal CR is affected could serve as a benchmark for evaluating cue-oriented interventions.
A challenge for the field going forward lies in considering a host of potential influences on CR (Jasinska et al., 2014). For instance, haptic cues (drug paraphernalia) rather than frequently employed visual cues may more robustly activate the DS and thus responses linked to drug behaviors (Yalachkov et al., 2013). Further, multisensory cue delivery more closely emulates drug-use realities and can enhance associations between CR and clinical variables such as craving (Yalachkov et al., 2012). CR and addiction severity may be linked (Chase et al., 2011), and CR is less readily observed in treatment-seeking individuals, such that the expectancy of drug availability is important (Jasinska et al., 2014). Interestingly, stimuli signaling the beginning (availability) rather than the end (nonavailability) of smoking rituals elicit craving, VS, and ACC responses (Mucha et al., 2008; Stippekohl et al., 2010), even though the end of the ritual is temporally more closely linked to the drug effect. Finally, the poor retest reliability of neural CR (Bach et al., 2021) needs to be addressed to successfully implement it in prospective research.
Conclusions regarding an “incubation of CR” can only be drawn tentatively, and within-subjects studies with at least three assessments (pre, short-term, long-term abstinence) are lacking. While testing during the withdrawal interval may be challenging, such endeavors could aid prognosis and interventions by identifying especially critical periods in need of particular monitoring and prevention efforts based on objective measures that could augment self-reported craving.
Mediators
The above-mentioned interventions attenuate regions mediating salience (VS, ACC / mPFC, amygdala, insula), indicating that reducing the motivational value of drug cues may facilitate successful treatment. Indeed, ROC recruits prefrontal brain regions to exert top-down control on circuits linked to cue value, yielding lower cravings. While flexibly employable in challenging situations, its reliance on prefrontal recruitment may be disadvantageous. First, addiction is linked to impairments in prefrontally mediated executive functions (Volkow et al., 2016); and second, stress, a well-established relapse risk (Sinha, 2007), may further compromise prefrontal functioning (Shields et al., 2016). To compensate for these challenges, coping skills may require rigorous training. Additionally, coping skills do not seem to affect the DS, suggesting they may be less suited to target habitual responding. As such, an advantage of CET may lie in its effect on the DS (in addition to the VS and other CR-related regions; Vollstädt-Klein et al., 2011) and a potential role in reducing highly automatized drug rituals triggered in drug environments. Approach avoidance training did not rely on executive influences, which is consistent with the finding that executive control did not affect training results (Eberl et al., 2013). Bias modification may therefore represent a prerequisite-free (in terms of executive control) addition to addiction treatment.
Lastly, coping skills, CET, and mindfulness affect cue-evoked PCC activity, which has been linked to being absorbed in one’s experience, e. g., craving (Brewer et al., 2013). As such, modifying such preoccupations is an important contributor to resisting cues. Regulation of craving may achieve this by generating structured thoughts and momentarily preventing the motivational pull of cues. The latter is likely also true for CET. Mindfulness should foster detecting mental absorption and subsequent disengagement by re-focusing on the present moment.
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1Note that Zeng et al. (2021) used seed-based d mapping, which accounts for increases and decreases simultaneously in one map, unlike the frequently employed activation likelihood estimation method, which does this separately, potentially identifying regions as increased and decreased.
