State-specific alterations in the neural computations underlying inhibitory control in women remitted from bulimia nervosa.

The neurocomputational processes underlying bulimia nervosa and its primary symptoms, out-of-control overeating and purging, are poorly understood. Research suggests that the brains of healthy individuals form a dynamic internal model to predict whether control is needed in each moment. This study tested the hypothesis that this computational process of inhibitory control is abnormally affected by metabolic state (being fasted or fed) in bulimia nervosa. A Bayesian ideal observer model was fit to behavioral data acquired from 22 women remitted from bulimia nervosa and 20 group-matched controls who completed a stop-signal task during two counterbalanced functional MRI sessions, one after a 16 h fast and one after a meal. This model estimates participants' trial-by-trial updating of the probability of a stop signal based on their experienced trial history. Neural analyses focused on control-related Bayesian prediction errors, which quantify the direction and degree of "surprise" an individual experiences on any given trial. Regardless of group, metabolic state did not affect behavioral performance on the task. However, metabolic state modulated group differences in neural activation. In the fed state, women remitted from bulimia nervosa had attenuated prediction-error-dependent activation in the left dorsal caudate. This fed-state activation was lower among women with more frequent past binge eating and self-induced vomiting. When they are in a fed state, individuals with bulimia nervosa may not effectively process unexpected information needed to engage inhibitory control. This may explain the difficulties these individuals have stopping eating after it begins.

Changes in guilt cognitions mediate the effect of trauma-informed guilt reduction therapy on PTSD and depression outcomes.

OBJECTIVE: Trauma-informed guilt reduction therapy (TrIGR), a six-session cognitive behavioral therapy targeting trauma-related guilt and distress, reduces guilt and symptoms of posttraumatic stress disorder (PTSD) and depression, yet little is known regarding how and why TrIGR may be effective. METHOD: This study examined treatment-related changes in avoidant coping and trauma-related guilt cognitions as possible mediators of treatment effects on PTSD and depression outcomes at 3- and 6-month follow-up. Data were from a randomized controlled trial for treatment of trauma-related guilt comparing TrIGR and supportive care therapy among 145 post-9/11 US veterans (Mage = 39.2 [8.1], 93.8% male). RESULTS: At pretreatment, most (86%) met PTSD criteria. Intent to treat analyses using parallel mediation models indicated changes in guilt cognitions, but not avoidant coping, mediated the effect of TrIGR on reducing PTSD severity at 3-month (a × b = -0.15, p < 0.01, 95% CI: [-0.24 to -0.06], p = 0.001) and 6-month (a × b = -0.17, 95% CI: [-0.26 to -0.07], p = 0.001) follow-up. Similarly, changes in guilt cognitions, but not avoidant coping, mediated the effect of TrIGR on reducing depression severity at 3-month (a × b = -0.10, 95% CI: [-0.18 to -0.02], p = 0.02) and 6-month (a × b = -0.11, 95% CI: [-0.20 to -0.03], p = 0.01) follow-up. CONCLUSIONS: Compared to guilt cognitions, changes in avoidant coping were less integral to downstream PTSD and depression symptom reduction. Guilt cognition change may be a salient active ingredient of PTSD and depression treatment for those with trauma-related guilt and a key therapy element to which providers should be attuned.

Resting-state connectivity subtype of comorbid PTSD and alcohol use disorder moderates improvement from integrated prolonged exposure therapy in Veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and are associated with significant functional impairment and inconsistent treatment outcomes. Data-driven subtyping of this clinically heterogeneous patient population and the associated underlying neural mechanisms are highly needed to identify who will benefit from psychotherapy. METHODS: In 53 comorbid PTSD/AUD patients, resting-state functional magnetic resonance imaging was collected prior to undergoing individual psychotherapy. We used a data-driven approach to subgroup patients based on directed connectivity profiles. Connectivity subgroups were compared on clinical measures of PTSD severity and heavy alcohol use collected at pre- and post-treatment. RESULTS: We identified a subgroup of patients associated with improvement in PTSD symptoms from integrated-prolonged exposure therapy. This subgroup was characterized by lower insula to inferior parietal cortex (IPC) connectivity, higher pregenual anterior cingulate cortex (pgACC) to posterior midcingulate cortex connectivity and a unique pgACC to IPC path. We did not observe any connectivity subgroup that uniquely benefited from integrated-coping skills or subgroups associated with change in alcohol consumption. CONCLUSIONS: Data-driven approaches to characterize PTSD/AUD subtypes have the potential to identify brain network profiles that are implicated in the benefit from psychological interventions - setting the stage for future research that targets these brain circuit communication patterns to boost treatment efficacy.

Comparison of Delivery of Care Before and During COVID-19 Within an Academic Outpatient Psychiatry Practice.

Introduction: The COVID-19 pandemic has challenged outpatient mental health clinics. This article compares care delivery and patient characteristics before and during the COVID-19 pandemic in outpatient mental health clinics within an academic health system. Methods: A retrospective cohort study was conducted in patients who received outpatient psychiatric services at two clinics (A and B). The investigators compared care delivery with patients with mental health conditions prepandemic (January 1-December 31, 2019) and midpandemic (January 1-December 31, 2020) periods. Care delivery was defined as the number and type of new and return visits (telehealth and face-to-face visits), patients with recorded measurement-based care (MBC) outcomes, and communication capability between patients and providers. Results: During the prepandemic period, 6,984 patients were seen in Clinics A and B, resulting in 57,629 visits. In the midpandemic period, 7,110 patients were served, resulting in 61,766 total visits. Medication management visits increased from 2019 to 2020; number of visits with documented outcome measures increased by 90% in Clinic A and 15% in Clinic B. The number of MyChart messages per patient increased more than twofold during the midpandemic period. The number of new visits with primary diagnosis of anxiety disorders increased in CY2020 and the number of visits with primary diagnosis of major depressive/mood disorders decreased in CY2020. Payor mix did not vary between the two periods although there was variability between payor mix at the two primary clinic locations. Discussion: The study suggests that there was no detrimental impact on access to care between the prepandemic and midpandemic periods within the health system. Mental health visits while pivoting to telehealth increased during the midpandemic period. Transition to telepsychiatry improved the ability to administer and document MBC.

The effect of obstructed action efficacy on reward-based decision-making in healthy adolescents: a novel functional MRI task to assay frustration.

Frustration is common in adolescence and often interferes with executive functioning, particularly reward-based decision-making, and yet very little is known about how incidental frustrating events (independent of task-based feedback) disrupt the neural circuitry of reward processing in this important age group. While undergoing functional magnetic resonance imaging (fMRI), 45 healthy adolescents played a card game in which they had to guess between two options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby increasing frustration potential. Neural deactivation of the precuneus, a Default Mode Network region, was observed during obstructed action blocks across stake conditions, but less so on high- relative to low-stake trials. Moreover, less deactivation in goal-directed reward processing regions (i.e., caudate), frontoparietal "task control" regions, and interoceptive processing regions (i.e., somatosensory cortex, thalamus) were observed on high-stake relative to low-stake trials. These findings are consistent with less disruption of goal-directed reward seeking during blocked action efficacy in high-stake conditions among healthy adolescents. These results provide a roadmap of neural systems critical to the processing of frustrating events during reward-based decision-making in youths and could help to characterize how frustration regulation is altered in a range of pediatric psychopathologies.

Symptoms of Posttraumatic Stress Disorder are Associated with Exaggerated Neural Response to Surprising Errors.

Posttraumatic stress disorder (PTSD) is characterized by exaggerated salience of previously innocuous cues and associated with hyperactivity of salience-related brain regions. Recently, computational models have been deployed to operationalize salience more precisely regarding surprise-driven learning, leading to findings that such learning is altered in anxiety-related disorders. In the present study, a sample of 20 combat veterans completed a probabilistic learning task during fMRI scanning. We applied a computational model to generate a trial-by-trial surprise signal (i.e., unsigned prediction error or difference between the expected probability of an outcome and the actual observed outcome), which allowed us to examine the neural response to surprising events. We did not observe an association between PTSD symptoms and behavioral indices of learning in the task. Surprising errors were associated with increased activity in the left precuneus/inferior parietal lobule and right inferior parietal lobule, two parietal regions that are linked to salience processing. Additionally, PTSD symptom severity was positively associated with precuneus/inferior parietal lobule activation to surprising errors, r = .63, p = .004. Taken together, this pattern of results suggests that PTSD symptoms are specifically associated with an exaggerated response to surprising errors in salience-related regions of the brain. This altered pattern of neural activity could represent a target for intervention to improve PTSD symptoms.

Proactive engagement of cognitive control modulates implicit approach-avoidance bias.

Implicit social-affective biases-reflected in a propensity to approach positive and avoid negative stimuli-have been documented in humans with paradigms, such as the Approach-Avoidance Task (AAT). However, the degree to which preemptively engaging cognitive control can help to down-regulate those behavioral tendencies remains poorly understood. While undergoing functional magnetic resonance imaging (fMRI), 24 healthy participants completed a cued version of the AAT, in which they responded to pictures of happy or angry faces by pulling a joystick toward themselves (approach) or pushing the joystick away (avoidance) based on the color of the stimulus frame. On some trials, they were cued to reverse the frame color/joystick action instructions. Before stimulus onset, a reverse cue was associated with deactivation of a visuo-spatial and motor planning network and subsequent slowing down in response to stimuli. During the stimulus phase, a reverse cue was associated with a) activation of cognitive control areas, including the right inferior frontal gyrus (IFG) and right inferior parietal lobule (IPL); and b) reduced right precentral gyrus activation when having to push (avoid) a happy face. Overall, these results suggest that proactively engaging cognitive control can help fine-tune behavioral and neural adjustment to emotionally incongruent behavioral conditions.

Neurocomputational Changes in Inhibitory Control Associated With Prolonged Exposure Therapy.

Posttraumatic stress disorder (PTSD) is associated with inhibitory control dysfunction that extends beyond difficulties inhibiting trauma-related intrusions. Inhibitory learning has been proposed as a potential mechanism of change underlying the effectiveness of extinction-based therapies such as prolonged exposure (PE), a first-line treatment for PTSD. To identify neurocognitive markers of change in inhibitory learning associated with PE, we applied a Bayesian learning model to the analysis of neuroimaging data collected during an inhibitory control task, both before and after PE treatment. Veterans (N = 20) with combat-related PTSD completed a stop-signal task (SST) while undergoing fMRI at time points immediately before and after PE treatment. Participants exhibited a small, significant improvement in performance on the SST, as demonstrated by longer reaction times and improved inhibition accuracy. Amplitude of neural activation associated with a signed prediction error (SPE; i.e., the discrepancy between actual outcome and model-based expectation of needing to stop) in the right caudate decreased from baseline to posttreatment assessment. Change in model-based activation was modulated by performance accuracy, with a decrease in positive SPE activation observed on successful trials, d = 0.79, and a reduction in negative SPE activation on error trials, d = 0.74. The decrease in SPE-related activation on successful stop trials was correlated with PTSD symptom reduction. These results are consistent with the notion that PE may help broadly strengthen inhibitory learning and the development of more accurate model-based predictions, which may thus facilitate change in cognitions in response to trauma-related cues and help reduce PTSD symptoms.

Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction.

Altered neural processing of the need to stop in young adults at risk for stimulant dependence.

Identification of neurocognitive predictors of substance dependence is an important step in developing approaches to prevent addiction. Given evidence of inhibitory control deficits in substance abusers (Monterosso et al., 2005; Fu et al., 2008; Lawrence et al., 2009; Tabibnia et al., 2011), we examined neural processing characteristics in human occasional stimulant users (OSU), a population at risk for dependence. A total of 158 nondependent OSU and 47 stimulant-naive control subjects (CS) were recruited and completed a stop signal task while undergoing functional magnetic resonance imaging (fMRI). A Bayesian ideal observer model was used to predict probabilistic expectations of inhibitory demand, P(stop), on a trial-to-trial basis, based on experienced trial history. Compared with CS, OSU showed attenuated neural activation related to P(stop) magnitude in several areas, including left prefrontal cortex and left caudate. OSU also showed reduced neural activation in the dorsal anterior cingulate cortex (dACC) and right insula in response to an unsigned Bayesian prediction error representing the discrepancy between stimulus outcome and the predicted probability of a stop trial. These results indicate that, despite minimal overt behavioral manifestations, OSU use fewer brain processing resources to predict and update the need for response inhibition, processes that are critical for adjusting and optimizing behavioral performance, which may provide a biomarker for the development of substance dependence.

Motivational context and neurocomputation of stop expectation moderate early attention responses supporting proactive inhibitory control.

Alterations in attention to cues signaling the need for inhibitory control play a significant role in a wide range of psychopathology. However, the degree to which motivational and attentional factors shape the neurocomputations of proactive inhibitory control remains poorly understood. The present study investigated how variation in monetary incentive valence and stake modulate the neurocomputational signatures of proactive inhibitory control. Adults (N = 46) completed a Stop-Signal Task (SST) with concurrent EEG recording under four conditions associated with stop performance feedback: low and high punishment (following unsuccessful stops) and low and high reward (following successful stops). A Bayesian learning model was used to infer individual's probabilistic expectations of the need to stop on each trial: P(stop). Linear mixed effects models were used to examine whether interactions between motivational valence, stake, and P(stop) parameters predicted P1 and N1 attention-related event-related potentials (ERPs) time-locked to the go-onset stimulus. We found that P1 amplitudes increased at higher levels of P(stop) in punished but not rewarded conditions, although P1 amplitude differences between punished and rewarded blocks were maximal on trials when the need to inhibit was least expected. N1 amplitudes were positively related to P(stop) in the high punishment condition (low N1 amplitude), but negatively related to P(stop) in the high reward condition (high N1 amplitude). Critically, high P(stop)-related N1 amplitude to the go-stimulus predicted behavioral stop success during the high reward block, providing evidence for the role of motivationally relevant context and inhibitory control expectations in modulating the proactive allocation of attentional resources that affect inhibitory control. These findings provide novel insights into the neurocomputational mechanisms underlying proactive inhibitory control under valence-dependent motivational contexts, setting the stage for developing motivation-based interventions that boost inhibitory control.

Sex moderates the effect of anhedonia on parietal alpha asymmetry.

Anhedonia, a transdiagnostic symptom present in many neuropsychiatric disorders, differs in males and females. Parietal EEG alpha asymmetry is associated with reduced arousal and low positive emotionality, and is, therefore, a promising neurophysiologic biomarker of anhedonia. To date, however, no prior studies have determined whether this measure captures sex differences in anhedonic expression. This preliminary study (N = 36) investigated whether anhedonia severity is associated with EEG resting-state parietal alpha asymmetry in adults and whether sex moderates this relationship. Results showed that there was a significant moderating effect of sex such that, only for females, higher levels of anhedonia were associated with increased parietal alpha asymmetry. These findings suggest that parietal alpha asymmetry is a promising biomarker of anhedonia severity in female adults and reinforces the need to account for sex differences in future research.

How Obstructed Action Efficacy Impacts Reward-Based Decision Making in Adolescent Depression: An fMRI Study.

OBJECTIVE: Disruption of reward seeking behavior by unforeseen obstacles can promote negative affect, including frustration and irritability, in adolescents. Repeated experiences of obstructed reward may in fact contribute to the development of depression in adolescents. However, the neurocognitive mechanisms whereby goal disruption impacts reward processing in adolescent depression have not yet been characterized. The present study addresses this gap by using neuroimaging and a novel paradigm to assess how incidental action obstruction impacts reward-based decision making. METHOD: We assessed 62 unmedicated adolescents with major depressive disorder (MDD; mean age = 15.6 years, SD = 1.4 years, 67% female participants) and 68 matched healthy control participants (mean age = 15.3 years, SD = 1.4 years, 50% female participants) using functional magnetic resonance imaging (fMRI) while they played a card game in which they had to guess between 2 options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby blocking action efficacy. RESULTS: Participants with MDD made fewer button press repetitions in response to action efficacy obstruction, which was more apparent in the low-stake condition (rate ratio =0.85, p = .034). During response repetition across stake conditions, MDDs exhibited higher activation in regions in the ventromedial prefrontal cortex, caudate, and putamen (F1,125 = 16.4-25.6, df=1,125; p values <.001; Hedges g = 0.85-0.98). CONCLUSION: Adolescents with depression tend to exhibit less flexible behavioral orientation in the face of blocked action efficacy, and abnormalities in neural systems critical to regulating negative affect during reward-based decision making. This research highlights possible mechanisms relevant to understanding and treating affective dysregulation in adolescent depression.

The neural mechanisms of affect infusion in social economic decision-making: a mediating role of the anterior insula.

Though emotions have been shown to have sometimes dramatic effects on decision-making, the neural mechanisms mediating these biases are relatively unexplored. Here, we investigated how incidental affect (i.e. emotional states unrelated to the decision at hand) may influence decisions, and how these biases are implemented in the brain. Nineteen adult participants made decisions which involved accepting or rejecting monetary offers from others in an Ultimatum Game while undergoing functional magnetic resonance imaging (fMRI). Prior to each set of decisions, participants watched a short video clip aimed at inducing either a sad or neutral emotional state. Results demonstrated that, as expected, sad participants rejected more unfair offers than those in the neutral condition. Neuroimaging analyses revealed that receiving unfair offers while in a sad mood elicited activity in brain areas related to aversive emotional states and somatosensory integration (anterior insula) and to cognitive conflict (anterior cingulate cortex). Sad participants also showed a diminished sensitivity in neural regions associated with reward processing (ventral striatum). Importantly, insular activation uniquely mediated the relationship between sadness and decision bias. This study is the first to reveal how subtle mood states can be integrated at the neural level to influence decision-making.

Inhibitory failures in cocaine use disorder: Not paying attention when there is a need to be cautious.

BACKGROUND: Stimulant use disorders, such as cocaine use disorder, are associated with significant impairment in inhibitory control, which has in turn been linked to difficulties maintaining abstinence following treatment. Here, we combine the Dynamic Belief Model (DBM) and a Hierarchical Drift Diffusion Model (HDDM) to examine whether individuals with cocaine use disorder have both strategic response updating and tactical speed accuracy trade-off problems during inhibitory control. METHODS: Twenty-seven individuals with cocaine use disorder and twenty-seven healthy control participants completed a Stop-Signal-Task (SST), in which one has to inhibit a motor response to a prepotent 2-alternative forced choice task on 25 % of the trials. RESULTS: Cocaine use disorder and control subjects did not differ on successful stopping behavior. In cocaine use disorder but not control subjects, higher likelihood of encountering a stop signal was associated with lower drift rate. Moreover, in cocaine use disorder subjects, a more negative relationship between likelihood of encountering a stop signal and drift rate was associated with lower accuracy on stop trials and slower stop reaction time. CONCLUSIONS: These results are consistent with a dysregulation between strategic and tactical processing during inhibitory control in cocaine use disorder. Specifically, these individuals are more likely to be less attentive to sensory evidence when the expectation of a stop signal is high.

Higher affective congruency in the approach-avoidance task is associated with insular deactivation to dynamic facial expressions.

Individuals exhibit a natural bias to approach positive social cues (e.g., smiling face) and to avoid negative ones, which may be altered in psychiatric conditions. Computerized approach/avoidance training to promote affectively congruent behavior has proven useful in modulating such biases. Here, we investigate how exposure to a higher rate of congruency impacts neural processing of social-affective cues. While undergoing functional magnetic resonance imaging (fMRI), twenty-four individuals completed two versions of the approach-avoidance task (AAT), in which they had to approach or avoid dynamic facial expressions of either happiness or disgust. In the high congruency condition, congruent responses (i.e. approaching happy faces, avoiding disgusted faces) were more frequent. The balanced condition had equal amounts of congruent and incongruent responses. Processing of congruent approach-avoidance actions towards social cues was associated with lower recruitment of the right anterior insula in the congruency-intensive relative to the balanced condition. Differential activation between the high congruency and balanced condition in the right hippocampus was negatively related to individuals' trait avoidance tendency. These findings are consistent with reduced affective neural processing of social cues when being exposed to congruent AAT contexts. These neural foci could be important targets when assessing the effectiveness of affective congruency training protocols.

Within-treatment clinical markers of dropout risk in integrated treatments for comorbid PTSD and alcohol use disorder.

BACKGROUND: Integrated interventions for comorbid posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are effective, but many patients prematurely drop out from treatment. Little is known about within-treatment risk factors for dropout, limiting the ability during therapy to identify patients at risk for attrition. METHODS: We examined measures assessing PTSD (PTSD Checklist for DSM-5; PCL-5), alcohol use (Substance Use Inventory; SUI), and patient satisfaction (Client Satisfaction Questionnaire; CSQ-8) as potential within-treatment markers of dropout risk, administered to 110 veterans in a randomized clinical trial of integrated exposure therapy versus integrated coping skills therapy for comorbid PTSD + AUD. Hierarchical Cox proportional hazard models with dropout status as the endpoint assessed effects of PCL-5, SUI, and CSQ-8 on dropout risk, and whether effects differed by treatment modality. RESULTS: A significant interaction between treatment and changes in alcohol use was observed (HR = 2.86, p = .007), where between-session alcohol use was positively associated with dropout hazard rate for those receiving integrated exposure therapy (HR = 2.34, p = .004), but not coping skills therapy (HR = 0.73, p = .19). Specifically, an increase of one drink consumed per day in the interval since last assessment (typically 2-3 weeks) was associated with a 5-fold increase in dropout hazard rate. CONCLUSIONS: The findings provide preliminary evidence of detectable within-treatment markers of dropout during integrated treatment for PTSD + AUD. Study of within-treatment indicators proximal to dropout may help identify at-risk patients and inform timely strategies to boost retention.

Neural affective mechanisms associated with treatment responsiveness in veterans with PTSD and comorbid alcohol use disorder.

Post-traumatic stress disorder (PTSD) is associated with neuro-physiological abnormalities reflecting increased anticipatory anxiety and reactivity to traumatic cues. It remains unclear whether neural mechanisms associated with PTSD treatment responsiveness, i.e. hyperactivation of the affective salience network in the brain, extend to a comorbid PTSD and substance use disorder population. Thirty-one Veterans with PTSD and co-occurring alcohol use disorder (AUD) were randomly assigned to either prolonged exposure or a non-exposure based treatment. They completed an affective anticipation task while undergoing fMRI, immediately prior and after completing treatment. After controlling for type and length of treatment, larger reduction of PTSD symptoms was associated with decreased anticipatory activation to negative trauma-related cues in the right pre-Supplementary Motor Area (pre-SMA), a region associated with emotion regulation. Smaller reduction in PTSD severity was associated with enhanced anticipatory activation to those cues within the right para-hippocampal region, an affective processing region. Our findings suggest that post-treatment reductions in anticipatory reactivity to trauma-related cues in the pre-SMA and para-hippocampal area are associated with larger PTSD symptom reduction in individuals with co-occurring PTSD and AUD. These results may offer neurofeedback training targets as an alternative to or enhancement of other PTSD treatment modalities in this population.

Bayesian computational markers of relapse in methamphetamine dependence.

Methamphetamine use disorder is associated with a high likelihood of relapse. Identifying robust predictors of relapse that have explanatory power is critical to develop secondary prevention based on a mechanistic understanding of relapse. Computational approaches have the potential to identify such predictive markers of psychiatric illness, with the advantage of providing a finer mechanistic explanation of the cognitive processes underlying psychiatric vulnerability. In this study, sixty-two recently sober methamphetamine-dependent individuals were recruited from a 28-day inpatient treatment program, and completed a Stop Signal Task (SST) while undergoing functional magnetic resonance imaging (fMRI). These individuals were prospectively followed for 1 year and assessed for relapse to methamphetamine use. Thirty-three percent of followed participants reported relapse. We found that neural activity associated with two types of Bayesian prediction error, i.e. the difference between actual and expected need to stop on a given trial, significantly differentiated those individuals who remained abstinent and those who relapsed. Specifically, relapsed individuals exhibited smaller neural activations to such Bayesian prediction errors relative to those individuals who remained abstinent in the left temporoparietal junction (Cohen's d = 0.91), the left inferior frontal gyrus (Cohen's d = 0.57), and left anterior insula (Cohen's d = 0.63). In contrast, abstinent and relapsed participants did not differ in neural activation to non-model based task contrasts or on various self-report clinical measures. In conclusion, Bayesian cognitive models may help identify predictive biomarkers of relapse, while providing a computational explanation of belief processing and updating deficits in individuals with methamphetamine use disorder.

Shared gray matter reductions across alcohol use disorder and posttraumatic stress disorder in the anterior cingulate cortex: A dual meta-analysis.

The considerable comorbidity of posttraumatic stress disorder (PTSD) and alcohol use disorders (AUD) poses a greater public health burden than either condition alone. Although there is a substantial body of evidence linking the direct neurotoxic effect of heavy drinking to gray matter (GM) deficits, as well as a growing body of literature supporting a strong association between PTSD and GM alterations, there is scant research interrogating the direct interaction of the two disorders. In order to generate data-driven, specific hypotheses regarding the overlapping neural substrates of PTSD and AUD, we conducted a meta-analysis of GM volumes in each disorder relative to healthy control subjects. We found shared GM deficits in the anterior cingulate cortex (ACC) across both disorders relative to healthy control participants. These findings suggest that reduced volumes of the ACC across PTSD and AUD may have implications for the development, expression, or treatment of symptoms linked to these frequently co-existing disorders. Recommendations are made for future work aimed at delineating the specific and shared effects of traumatic stress and alcoholism on neural integrity.