Association of Neural Responses to Drug Cues With Subsequent Relapse to Stimulant Use

Abstract

Importance Although chronic relapse is a characteristic of addiction to stimulants, conventional measures (eg, clinical, demographic, and self-report) do not robustly identify which individuals are most vulnerable to relapse. Objectives To test whether drug cues are associated with increased mesolimbic neural activity in patients undergoing treatment for stimulant use disorder and whether this activity is associated with risk for subsequent relapse. Design, Setting, and Participants This prospective cohort study of 76 participants included a control group for baseline group comparisons. Veteran patients (n = 36) with stimulant use disorders were recruited from a 28-day residential treatment program at the Veterans Affairs Palo Alto Health Care System. Healthy controls (n = 40) were recruited from the surrounding community. Baseline data were collected between September 21, 2015, and January 26, 2018, from patients and healthy controls using functional magnetic resonance imaging during a performance of a reward cue task. Patients’ stimulant use was subsequently assessed after treatment discharge (at approximately 1, 3, and 6 months) to assess relapse outcomes. Main Outcomes and Measures Primary measures included neural responses to drug and food cues in estimated mesolimbic volumes of interest, including the medial prefrontal cortex, nucleus accumbens (NAcc), and ventral tegmental area. The primary outcome variable was relapse (defined as any stimulant use), assessed both dichotomously (3 months after discharge) and continuously (days to relapse). Brain activity measures were contrasted between groups to validate neural measures of drug cue reactivity, which were then used to estimate relapse outcomes of patients. Results Relative to controls (n = 40; 16 women and 24 men; mean [SD] age, 32.0 [11.6] years), patients (n = 36; 2 women and 34 men; mean [SD] age, 43.4 [13.3] years) showed increased mesolimbic activity in response to drug cues (medial prefrontal cortex, t 74 = 2.90, P = .005, Cohen d = 0.66; NAcc, t 74 = 2.39, P = .02, Cohen d = 0.54; and ventral tegmental area, t 74 = 4.04, P < .001, Cohen d = 0.92). In patients, increased drug cue response in the NAcc (but not other volumes of interest) was associated with time to relapse months later (Cox proportional hazards regression hazard ratio, 2.30; 95% CI, 1.40-3.79). After controlling for age, NAcc response to drug cues classified relapsers (12 patients; 1 woman and 11 men; mean [SD] age, 49.3 [14.1] years) and abstainers (21 patients; 1 woman and 20 men; mean [SD] age, 39.3 [12.3] years) at 3 months with 75.8% classification accuracy. Model com...

The Paraventricular Thalamus is a Critical Mediator of Top-down Control of Cue-motivated Behavior in Rats

“…While both strategies may be adaptive under the right conditions, an extreme bias for the selective use of a single strategy may contribute to an increased risk for specific pathologies. Indeed, several psychiatric disorders have been associated with excessive attribution of motivational significance to environmental cues, including substance use disorder [9][10][11][12] , eating disorders 13,14 , gambling disorder 15 , post-traumatic stress disorder (PTSD) 16 , and bipolar disorder 17,18 . On the other side of the spectrum, a deficit in the attribution of incentive value to reward-cues has been associated with avolition (i.e.…”

Brain-outcome associations for risk taking depend on the measures used to capture individual differences

“…Against this backdrop, biological substrates like brain function are receiving ever more attention as potential markers of individual differences in risk taking and related constructs (Braams et al, 2015;Qu et al, 2015;Büchel et al, 2017;Blankenstein et al, 2018;Casey et al, 2018;MacNiven et al, 2018;Krönke et al, 2020). Indeed, much research has been devoted to the neural basis of risk taking (Mohr et al, 2010;Wu et al, 2012;Bartra et al, 2013), leading to the identification of three brain regions as core elements of a neural risk matrix, differentially promoting (nucleus accumbens in ventral striatum), inhibiting (anterior insular cortex), and controlling (anterior cingulate cortex) risky choice (Knutson and Huettel, 2015).…”

“…Thirdly, regional activation differences do not necessarily reflect useful or reliable predictors for the outcomes of interest (Poldrack et al, 2018), thus we evaluate the explanatory / predictive power of neural indices for risk-related outcomes. For example, activation differences in the NAcc, an anatomically and functionally central structure in the (non)human reward circuit and integral part of the risk matrix (Haber and Knutson, 2010;Knutson and Huettel, 2015;Samanez-Larkin and Knutson, 2015), have been shown to be predictive of clinically relevant outcomes (Büchel et al, 2017;MacNiven et al, 2018). What is currently unclear, however, is the extent to which different risk-taking measures compare with regards to their potential for brain-outcome associations.…”

“…Concretely, this means negative brain-outcome associations for anterior insula and ACC, considering their respective roles in inhibiting and monitoring/controlling risky choice. For the NAcc, the existing evidence base for brain-outcome associations is mixed with regards to directionality (Büchel et al, 2017;MacNiven et al, 2018), and there is a lack of studies which have examined brain-outcome associations for different operationalizations of risk taking. As a consequence, the directionality of brain-outcome associations for NAcc, especially for neural indicators from different risk-taking measures and for nonclinical risk-related outcomes, remains to be determined.…”

Addiction science and the perception of freewill

“…Subcortical structures implicated in incentive signaling in rat work are reliably activated by drug, food, and sex cues (Noori, Cosa Linan, & Spanagel, 2016). Moreover, activity in the nucleus accumbens in response to cocaine cues predicts relapse among individuals in treatment for cocaine substance use disorder (MacNiven et al, 2018).…”