Model-based and model-free mechanisms in methamphetamine use disorder.

People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.

Proof-of-concept trial of Goal Management Training+ to improve executive functions and treatment outcomes in methamphetamine use disorder.

BACKGROUND: Deficits in executive function are common in methamphetamine use disorder (MUD), likely contributing to difficulties in sustained treatment success. Cognitive remediation interventions are designed to treat such deficits but have not been adapted to the needs of people with MUD. This study presents a proof-of-concept trial to evaluate a new cognitive remediation program for MUD, Goal Management Training+ (GMT+). METHODS: This was a cluster-randomised crossover trial comparing GMT+ with a psychoeducation-based control (Brain Health Workshop; BHW). GMT+ is a therapist-administered group-based cognitive remediation for executive dysfunction comprising four 90-minute weekly sessions and daily journal activities. BHW is a lifestyle psychoeducation program matched to GMT+ for therapist involvement, format, and duration. Participants (n = 36; GMT n = 17; BHW n = 19) were recruited from therapeutic communities in Victoria, Australia. Primary outcomes included intervention acceptability, feasibility, and improvements in self-reported executive function. Secondary outcomes included cognitive tests of executive function, severity of methamphetamine dependence, craving, and quality of life. We performed mixed linear modelling and calculated Hedges' g effect sizes. RESULTS: GMT+ participant ratings and program retention indicated high acceptability. There was no difference between GMT+ and BHW on self-reported executive function (g = 0.06). Cognitive tasks suggested benefits of GMT+ on information gathering (g = 0.88) and delay-discounting (g = 0.80). Severity of methamphetamine dependence decreased more in GMT+ (g = 1.47). CONCLUSIONS: GMT+ was well-accepted but did not improve self-reported executive functioning. Secondary outcomes suggested GMT+ was beneficial for objective cognitive performance and severity of dependence.

Computational mechanisms underpinning greater exploratory behaviour in excess weight relative to healthy weight adolescents.

Obesity in adolescence is associated with cognitive changes that lead to difficulties in shifting unhealthy habits in favour of alternative healthy behaviours, similar to addictive behaviours. An outstanding question is whether this shift in goal-directed behaviour is driven by over-exploitation or over-exploration of rewarding outcomes. Here, we addressed this question by comparing explore/exploit behaviour on the Iowa Gambling Task in 43 adolescents with excess weight against 38 adolescents with healthy weight. We computationally modelled both exploitation behaviour (e.g., reinforcement sensitivity and inverse decay parameters), and explorative behaviour (e.g., maximum directed exploration value). We found that overall, adolescents with excess weight displayed more behavioural exploration than their healthy-weight counterparts - specifically, demonstrating greater overall switching behaviour. Computational models revealed that this behaviour was driven by a higher maximum directed exploration value in the excess-weight group (U = 520.00, p = .005, BF10 = 5.11). Importantly, however, we found substantial evidence that groups did not differ in reinforcement sensitivity (U = 867.00, p = .641, BF10 = 0.30). Overall, our study demonstrates a preference for exploratory behaviour in adolescents with excess weight, independent of sensitivity to reward. This pattern could potentially underpin an intrinsic desire to explore energy-dense unhealthy foods - an as-yet untapped mechanism that could be targeted in future treatments of obesity in adolescents.

Protocol for a cluster randomised crossover pilot trial of Goal Management Training+ (GMT+) for methamphetamine use disorder.

Background: Methamphetamine use disorder (MUD) is associated with executive dysfunctions, which are linked with poorer treatment outcomes. However, current treatments for MUD do not directly address cognition. We recently modified Goal Management Training (now Goal Management Training+; GMT+), a group-based intervention originally designed to improve executive functions after brain injury, to enhance suitability for MUD. Here, we describe the rationale and design of a trial which aims to determine the acceptability and feasibility of GMT+ during residential rehabilitation for MUD, and its impact on executive functions and clinical outcomes. Methods: We used a cluster randomised crossover design: participants are randomised at the cluster level to receive either GMT+ or psychoeducation-control (Brain Health Workshop; BHW). GMT+ is delivered in four 90-min weekly sessions and includes a between-session journal with 10-min daily activities. The program targets attention, impulse control, goal-setting, and decision-making. BHW is a health-oriented intervention that delivers information about the brain and promotes healthy exercise, diet, and sleep. It is matched to GMT+ on program format, length, and time with therapists. We will recruit forty-eight participants with MUD from residential treatment services. Our primary outcomes are acceptability, feasibility, and self-reported executive functioning. Secondary outcomes include craving, quality of life and cognitive performance. Outcome assessments are performed at baseline, post-interventions, 4-week follow-up, and 12-week follow-up. Conclusions: This study will provide GMT+ feasibility and acceptability data and will indicate initial efficacy on executive functions and clinical outcomes in residential treatment for MUD. Information from this pilot trial will inform a powered RCT.

Development of Goal Management Training+ for Methamphetamine Use Disorder Through Collaborative Design.

Background: Methamphetamine use disorder (MUD) is associated with executive dysfunctions, which are linked with poorer treatment outcomes including earlier drop out and relapse. However, current treatments for MUD do not address executive functions. Goal Management Training (GMT) is an evidence-based cognitive remediation program for executive dysfunction, although required modifications to enhance its relevance and application within addiction treatment settings. This study aimed to (1) tailor GMT to the key cognitive deficits and typical treatment duration of MUD; (2) explore consumers' (people with MUD) engagement with the revised program; (3) implement a prototype of the program with consumers; and (4) present the manualized standard administration to clinical service providers. Methods: We followed the Medical Research Council Complex Interventions Framework and employed an evidence- and person-based intervention development process. We used a four-phased approach and collaborated with neuropsychology experts, design researchers in healthcare, consumers with MUD, and clinical service providers. Each aim was addressed in a separate study phase; including content refinement and review with neuropsychology experts (phase 1), intervention design and collaboration with consumers (phase 2), prototype development and review with consumers (phase 3), and final program modifications and review with clinical stakeholders (phase 4). Results: Findings from phase 1 indicated support for targeting four cognitive processes (attention, impulse control, goal setting, and decision-making). Key feedback included the need to help habitualize cognitive strategies and to guide consumers in applying these strategies in emotionally salient situations. Findings from phases 2 and 3 indicated consumer support for the program strategies and materials but highlighted the need to further enhance the personal relevance of specific content and journal activities. Findings from phase 4 provided clinicians support for the revised program but indicated an opportunity to minimize unintended effects. We present the intervention materials for the final revised program, Goal Management Training+ (GMT+), in line with TIDieR guidelines. Conclusions: GMT+ targets key cognitive processes and is sensitive to the clinical needs of people with MUD. Our intervention development process was important for informing the active ingredients and materials for GMT+, and indicated initial consumer and provider acceptability prior to conducting a clinical trial.

Computational models of exploration and exploitation characterise onset and efficacy of treatment in methamphetamine use disorder.

People with Methamphetamine Use Disorder (PwMUD) spend substantial time and resources on substance use, which hinders their ability to explore alternate reinforcers. Gold-standard behavioural treatments attempt to remedy this by encouraging action towards non-drug reinforcers, but substance use often persists. We aimed to unravel the mechanistic drivers of this behaviour by applying a computational model of explore/exploit behaviour to decision-making data (Iowa Gambling Task) from 106 PwMUD and 48 controls. We then examined the longitudinal link between explore/exploit mechanisms and changes in methamphetamine use 6 weeks later. Exploitation parameters included reinforcement sensitivity and inverse decay (i.e., number of past outcomes used to guide choices). Exploration parameters included maximum directed exploration value (i.e., value of trying novel actions). The Timeline Follow Back measured changes in methamphetamine use. Compared to controls, PwMUD showed deficits in exploitative decision-making, characterised by reduced reinforcement sensitivity, U = 3065, p = 0.009, and less use of previous choice outcomes, U = 3062, p = 0.010. This was accompanied by a behavioural pattern of frequent shifting between choices, which appeared consistent with random exploration. Furthermore, PwMUD with greater reductions of methamphetamine use at 6 weeks had increased directed exploration (ß = 0.22, p = 0.045); greater use of past choice outcomes (ß = -0.39, p = 0.002) and greater choice consistency (ß = -0.39, p = 0.002). Therefore, limited computational exploitation and increased behavioural exploration characterise PwMUD's presentation to treatment, while increased directed exploration, use of past choice outcomes and choice consistency predict greater reductions of methamphetamine use.

Cognitive boosting interventions for impulsivity in addiction: a systematic review and meta-analysis of cognitive training, remediation and pharmacological enhancement.

AIMS: To evaluate and compare the effects of three cognitive boosting intervention approaches (computerised cognitive training, cognitive remediation and pharmacological cognitive enhancers) on measures of impulsive action and impulsive choice. DESIGN: Systematic review and meta-analysis of publications that reported original controlled trials of cognitive boosting interventions. SETTING: Studies conducted anywhere in the world. No language restrictions were applied. PARTICIPANTS: Treatment-seeking adults with substance use disorder or gambling disorder. MEASUREMENTS: Our primary outcome was a reduction in impulsive action or choice on a validated cognitive measure post-intervention. We assessed risk of bias using the Cochrane Collaboration tool and determined pooled estimates from published reports. We performed random-effects analyses for impulsive action and impulsive choice outcomes and planned moderator analyses. FINDINGS: Of 2204 unique studies identified, 60 were included in the full-text review. Twenty-three articles were considered eligible for inclusion in the qualitative synthesis and 16 articles were included in our meta-analysis. Articles eligible for pooled analyses included five working memory training (computerised cognitive training) studies with 236 participants, three goal management training (cognitive remediation) studies with 99 participants, four modafinil (cognitive enhancer) studies with 160 participants and four galantamine (cognitive enhancer) studies with 131 participants. Study duration ranged from 5 days to 13 weeks, with immediate follow-up assessments. There were no studies identified that specifically targeted gambling disorder. We only found evidence for a benefit on impulsive choice of goal management training, although only in two studies involving 66 participants (standardised mean difference (SMD) = 0.86; 95% CI = 0.49-1.23; P = 0.02; I2  = 0%, P = 0.95). CONCLUSION: Cognitive remediation, and specifically goal management training, may be an effective treatment for addressing impulsive choice in addiction. Preliminary evidence does not support the use of computerised cognitive training or pharmacological enhancers to boost impulse control in addiction.

Lack of longitudinal changes in cognition in individuals with methamphetamine use disorder during the first 6 weeks after commencing treatment.

Background: Methamphetamine use disorder (MUD) associates with cognitive impulsivity deficits. However, few studies have examined longitudinal changes in cognition, and it remains unclear if deficits resolve during early recovery.Objectives: To compare: (1) cognitive function of individuals with MUD at treatment onset and six-weeks later with controls tested over the same period; (2) cognitive changes in MUD-individuals who remained abstinent versus relapsed.Method: We recruited 108 participants meeting DSM-IV-TR criteria for methamphetamine dependence (81 males) and 50 demographically matched controls (38 males); 77 methamphetamine- dependent participants (59 males) and 48 controls (36 males) were retained at follow-up. We administered response inhibition, delay discounting and uncertainty-based decision-making tests at both endpoints. Relapse was defined as methamphetamine concentrations >0.4 ng/mg at follow-up in hair toxicology.Results: We found a significant time-by-group interaction on uncertainty-based decision-making (effect size: η2 = .05), although post-hoc tests to disentangle this interaction yielded inconclusive results (p-range = .14-.40; BF10-range = 0.43-1.67). There were no significant time-by-group interactions on response inhibition or delay discounting, with the former likely a null effect (η2-interaction = .003 and .02; BFincl = 0.23 and 0.71). There were no significant differences in cognitive recovery between individuals who maintained abstinence (n = 12) versus relapsed (n = 65) (η2-range = .003-.04), although evidence was inconclusive toward whether findings reflected true null effects (BFincl-range = 0.33-0.75).Conclusion: We did not find evidence that MUD-related cognitive impulsivity deficits improve beyond practice effects over 6 weeks. Findings do not support previous, albeit conflicting, evidence of early recovery of cognitive deficits in MUD.

Are methamphetamine users compulsive? Faulty reinforcement learning, not inflexibility, underlies decision making in people with methamphetamine use disorder.

Methamphetamine use disorder involves continued use of the drug despite negative consequences. Such 'compulsivity' can be measured by reversal learning tasks, which involve participants learning action-outcome task contingencies (acquisition-contingency) and then updating their behaviour when the contingencies change (reversal). Using these paradigms, animal models suggest that people with methamphetamine use disorder (PwMUD) may struggle to avoid repeating actions that were previously rewarded but are now punished (inflexibility). However, difficulties in learning task contingencies (reinforcement learning) may offer an alternative explanation, with meaningful treatment implications. We aimed to disentangle inflexibility and reinforcement learning deficits in 35 PwMUD and 32 controls with similar sociodemographic characteristics, using novel trial-by-trial analyses on a probabilistic reversal learning task. Inflexibility was defined as (a) weaker reversal phase performance, compared with the acquisition-contingency phases, and (b) persistence with the same choice despite repeated punishments. Conversely, reinforcement learning deficits were defined as (a) poor performance across both acquisition-contingency and reversal phases and (b) inconsistent postfeedback behaviour (i.e., switching after reward). Compared with controls, PwMUD exhibited weaker learning (odds ratio [OR] = 0.69, 95% confidence interval [CI] [0.63-0.77], p < .001), though no greater accuracy reduction during reversal. Furthermore, PwMUD were more likely to switch responses after one reward/punishment (OR = 0.83, 95% CI [0.77-0.89], p < .001; OR = 0.82, 95% CI [0.72-0.93], p = .002) but just as likely to switch after repeated punishments (OR = 1.03, 95% CI [0.73-1.45], p = .853). These results indicate that PwMUD's reversal learning deficits are driven by weaker reinforcement learning, not inflexibility.