Impaired Bayesian learning for cognitive control in cocaine 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.

People with a tobacco use disorder exhibit misaligned Bayesian belief updating by falsely attributing non-drug cues as worse predictors of positive outcomes compared to drug cues

Adaptive behaviours depend on dynamically updating internal representations of the world based on the ever-changing environmental contingencies. People with a substance use disorder (pSUD) show maladaptive behaviours with high persistence in drug-taking, despite severe negative consequences. We recently proposed a salience misattribution model for addiction (SMMA; Kalhan et al., 2021), arguing that pSUD have aberrations in their updating processes where drug cues are misattributed as strong predictors of positive outcomes, but weaker predictors of negative outcomes. We also argued that conversely, non-drug cues are misattributed as weak predictors of positive outcomes, but stronger predictors of negative outcomes. We tested these hypotheses using a multi-cue reversal learning task, with reversals in whether drug or non-drug cues are relevant in predicting the outcome (monetary win or loss). We show that people with a tobacco use disorder (pTUD), do form misaligned internal representations. We found that pTUD updated less towards learning the drug cue's relevance in predicting a loss. Further, when neither drug nor non-drug cue predicted a win, pTUD updated more towards the drug cue being relevant predictors of that win. Our Bayesian belief updating model revealed that pTUD had a low estimated likelihood of non-drug cues being predictors of wins, compared to drug cues, which drove the misaligned updating. Overall, several hypotheses of the SMMA were supported, but not all. Our results implicate that strengthening the non-drug cue association with positive outcomes may help restore the misaligned internal representation in pTUD, and offers a quantifiable, computational account of these updating processes.

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.

Computational models of behavioral addictions: State of the art and future directions

Non-pharmacological behavioral addictions, such as pathological gambling, videogaming, social networking, or internet use, are becoming major public health concerns. It is not yet clear how behavioral addictions could share many major neurobiological and behavioral characteristics with substance use disorders, despite the absence of direct pharmacological influences. A deeper understanding of the neurocognitive mechanisms of addictive behavior is needed, and computational modeling could be one promising approach to explain intricately entwined cognitive and neural dynamics. This review describes computational models of addiction based on reinforcement learning algorithms, Bayesian inference, and biophysical neural simulations. We discuss whether computational frameworks originally conceived to explain maladaptive behavior in substance use disorders can be effectively extended to non-substance-related behavioral addictions. Moreover, we introduce recent studies on behavioral addictions that exemplify the possibility of such extension and propose future directions.

Prefrontal Cortex Activation and Stopping Performance Underlie the Beneficial Effects of Atomoxetine on Response Inhibition in Healthy Volunteers and Those With Cocaine Use Disorder

BACKGROUND

Impaired response inhibition in individuals with cocaine use disorder (CUD) is hypothesized to depend on deficient noradrenergic signaling in corticostriatal networks. Remediation of noradrenergic neurotransmission with selective norepinephrine reuptake inhibitors such as atomoxetine may therefore have clinical utility to improve response inhibitory control in CUD.

METHODS

We carried out a randomized, double-blind, placebo-controlled, crossover study with 26 participants with CUD and 28 control volunteers investigating the neural substrates of stop-signal inhibitory control. The effects of a single dose of atomoxetine (40 mg) were compared with placebo on stop-signal reaction time performance and functional network connectivity using dynamic causal modeling.

RESULTS

We found that atomoxetine speeded Go response times in both control participants and those with CUD. Improvements in stopping efficiency on atomoxetine were conditional on baseline (placebo) stopping performance and were directly associated with increased inferior frontal gyrus activation. Further, stopping performance, task-based brain activation, and effective connectivity were similar in the 2 groups. Dynamic causal modeling of effective connectivity of multiple prefrontal and basal ganglia regions replicated and extended previous models of network function underlying inhibitory control to CUD and control volunteers and showed subtle effects of atomoxetine on prefrontal-basal ganglia interactions.

CONCLUSIONS

These findings demonstrate that atomoxetine improves response inhibition in a baseline-dependent manner in control participants and in those with CUD. Our results emphasize inferior frontal cortex function as a future treatment target owing to its key role in improving response inhibition in CUD.

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.

Altered functional network activities for behavioral adjustments and Bayesian learning in young men with Internet gaming disorder

BACKGROUND AND AIMS

Deficits in cognitive control represent a core feature of addiction. Internet Gaming Disorder (IGD) offers an ideal model to study the mechanisms underlying cognitive control deficits in addiction, eliminating the confounding effects of substance use. Studies have reported behavioral and neural deficits in reactive control in IGD, but it remains unclear whether individuals with IGD are compromised in proactive control or behavioral adjustment by learning from the changing contexts.

METHODS

Here, fMRI data of 21 male young adults with IGD and 21 matched healthy controls (HC) were collected during a stop-signal task. We employed group independent component analysis to investigate group differences in temporally coherent, large-scale functional network activities during post-error slowing, the typical type of behavioral adjustments. We also employed a Bayesian belief model to quantify the trial-by-trial learning of the likelihood of stop signal - P(Stop) - a broader process underlying behavioral adjustment, and identified the alterations in functional network responses to P(Stop).

RESULTS

The results showed diminished engagement of the fronto-parietal network during post-error slowing, and weaker activity in the ventral attention and anterior default mode network in response to P(Stop) in IGD relative to HC.

DISCUSSION AND CONCLUSIONS

These results add to the literatures by suggesting deficits in updating and anticipating conflicts as well as in behavioral adjustment according to contextual information in individuals with IGD.

Age-Related Structural and Functional Changes of the Hippocampus and the Relationship with Inhibitory Control

Aging is associated with structural and functional changes in the hippocampus, and hippocampal dysfunction represents a risk marker of Alzheimer’s disease. Previously, we demonstrated age-related changes in reactive and proactive control in the stop signal task, each quantified by the stop signal reaction time (SSRT) and sequential effect computed as the correlation between the estimated stop signal probability and go trial reaction time. Age was positively correlated with the SSRT, but not with the sequential effect. Here, we explored hippocampal gray matter volume (GMV) and activation to response inhibition and to p(Stop) in healthy adults 18 to 72 years of age. The results showed age-related reduction of right anterior hippocampal activation during stop success vs. go trials, and the hippocampal activities correlated negatively with the SSRT. In contrast, the right posterior hippocampus showed higher age-related responses to p(Stop), but the activities did not correlate with the sequential effect. Further, we observed diminished GMVs of the anterior and posterior hippocampus. However, the GMVs were not related to behavioral performance or regional activities. Together, these findings suggest that hippocampal GMVs and regional activities represent distinct neural markers of cognitive aging, and distinguish the roles of the anterior and posterior hippocampus in age-related changes in cognitive control.

Meta-analysis of aberrant post-error slowing in substance use disorder: implications for behavioral adaptation and self-control

Individual with substance use disorders have well-recognized impairments in cognitive control, including in behavioral adaptation after mistakes. One way in which this impairment manifests is via diminished post-error slowing, the increase in reaction time following a task-related error that is posited to reflect cautionary or corrective behavior. Yet, in the substance use disorder literature, findings with regard to post-error slowing have been inconsistent, and thus could benefit from quantitative integration. Here, we conducted a meta-analysis of case-control studies examining post-error slowing in addiction. Twelve studies with 15 unique comparisons were identified, comprising 567 substance users and 384 healthy controls across three broad types of inhibitory control paradigms (go-no/go, conflict resolution, and stop signal tasks, respectively). Results of the random-effects meta-analysis revealed a moderate group difference across all studies (Cohen's d = 0.31), such that the individuals with substance use disorder had diminished post-error slowing compared with controls. Despite this omnibus effect, there was also large variability in the magnitude of the effects, explained in part by differences between studies in task complexity. These findings suggest that post-error slowing may serve as a promising and easy-to-implement measure of cognitive control impairment in substance use disorder, with potential links to aberrant brain function in cognitive control areas such as the anterior cingulate cortex.

Thalamic Cortical Error-Related Responses in Adult Social Drinkers: Sex Differences and Problem Alcohol Use

BACKGROUND

Error-related brain activities are altered in individuals with substance use disorders. Here we examined error-related activities in relation to problem drinking in nondependent alcohol drinkers. In particular, we investigated sex differences and whether altered error responses are related to post-error behavioral control.

METHODS

A sample of 145 nondependent drinkers (77 women) performed the stop-signal task during functional magnetic resonance imaging. Imaging data were processed and modeled using statistical parametric mapping. Independent sample t test and linear regression were employed to examine sex differences in error response and relationship between error response and problem drinking.

RESULTS

Compared with men, women showed greater error-related (stop error > go success) activations in the bilateral thalamus, right middle/superior temporal cortex, and bilateral dorsal anterior cingulate cortex. In whole-brain linear regression of error responses against the Alcohol Use Disorders Identification Test score, a wide swath of cortical and subcortical regions, including the thalamus, showed decreased activation in association with problem drinking in women but not in men. However, men and women were not different in the extent of post-error slowing and decreased thalamic error response in association with problem drinking was not related to the extent of post-error slowing in women.

CONCLUSIONS

The results suggest sex differences in error-related activations with heavier drinking associated with reduced error activations in women but not in men. These differences in cerebral activations may reflect higher physiological arousal in response to errors and greater vulnerability of saliency-related arousal response to problem drinking in female as compared with male social drinkers.

Dynamic network dysfunction in cocaine dependence: Graph theoretical metrics and stop signal reaction time

Graphic theoretical metrics have become increasingly popular in characterizing functional connectivity of neural networks and how network connectivity is compromised in neuropsychiatric illnesses. Here, we add to this literature by describing dynamic network connectivities of 78 cocaine dependent (CD) and 85 non-drug using healthy control (HC) participants who underwent fMRI during performance of a stop signal task (SST). Compared to HC, CD showed prolonged stop signal reaction time (SSRT), consistent with deficits in response inhibition. In graph theoretical analysis of dynamic functional connectivity, we examined temporal flexibility and spatiotemporal diversity of 14 networks covering the whole brain. Temporal flexibility quantifies how frequently a brain region interacts with regions of other communities across time, with high temporal flexibility indicating that a region interacts predominantly with regions outside its own community. Spatiotemporal diversity quantifies how uniformly a brain region interacts with regions in other communities over time, with high spatiotemporal diversity indicating that the interactions are more evenly distributed across communities. Compared to HC, CD exhibited decreased temporal flexibility and increased spatiotemporal diversity in the great majority of neural networks. The graph metric measures of the default mode network negatively correlated with SSRT in CD but not HC. The findings are consistent with diminished temporal flexibility and a compensatory increase in spatiotemporal diversity, in association with impairment of a critical executive function, in cocaine addiction. More broadly, the findings suggest that graph theoretical metrics provide new insights for connectivity analyses to elucidate network dysfunction that may elude conventional measures.

•

Cocaine addiction (CA) is associated with prolonged stop signal reaction time (SSRT).

•

CA is associated with decreased temporal flexibility (TF) of neural networks.

•

CA is associated with increased spatial temporal diversity (STD) of neural networks.

•

The TF and STD of default mode network correlated negatively with SSRT in CA.

•

Dynamic connectivity captures network dysfunction in link with inhibition deficits in CA.

Emotional Regulation in Young Adults with Internet Gaming Disorder

People diagnosed with Internet gaming disorder (IGD) have been frequently reported to experience depression, anxiety, and hostility. Emotional regulation contributes to these mood symptoms. This study evaluated emotional regulation in subjects with IGD and examined relationships between emotional regulation, depression, anxiety, and hostility in young adults with IGD. We recruited 87 people with IGD and a control group of 87 people without a history of IGD. All participants underwent a diagnostic interview based on the IGD criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and they completed a questionnaire on emotional regulation, depression, anxiety, and hostility. We found that subjects with IGD were less likely to practice cognitive reappraisal and were more likely to suppress their emotions. Linear regression revealed the higher cognitive reappraisal and lower expressive suppression associated with depression, anxiety, and hostility among subjects with IGD. The emotional regulation strategies that characterize those with IGD could be contributing factors to the depression and hostility tendencies of these people. When treating patients with IGD, in addition to providing appropriate interventions to relieve depression and hostility, practitioners should effectively assess emotional regulation strategies and provide emotional regulation therapy to prevent a vicious cycle of negative emotions.

Distinct neural processes support post-success and post-error slowing in the stop signal task

Executive control requires behavioral adaptation to environmental contingencies. In the stop signal task (SST), participants exhibit slower go trial reaction time (RT) following a stop trial, whether or not they successfully interrupt the motor response. In previous fMRI studies, we demonstrated activation of the right-hemispheric ventrolateral prefrontal cortex, in the area of inferior frontal gyrus, pars opercularis (IFGpo) and anterior insula (AI), during post-error slowing (PES). However, in similar analyses we were not able to identify regional activities during post-success slowing (PSS). Here, we revisited this issue in a larger sample of participants (n=100) each performing the SST for 40 min during fMRI. We replicated IFGpo/AI activation to PES (p≤0.05, FWE corrected). Further, PSS engages decreased activation in a number of cortical regions including the left inferior frontal cortex (IFC; p≤0.05, FWE corrected). We employed Granger causality mapping to identify areas that provide inputs each to the right IFGpo/AI and left IFC, and computed single-trial amplitude (STA) of stop trials of these input regions as well as the STA of post-stop trials of the right IFGpo/AI and left IFC. The STAs of the right inferior precentral sulcus and supplementary motor area (SMA) and right IFGpo/AI were positively correlated and the STAs of the left SMA and left IFC were positively correlated (slope>0, p's≤0.01, one-sample t test), linking regional responses during stop success and error trials to those during PSS and PES. These findings suggest distinct neural mechanisms to support PSS and PES.

Proactive Control: Neural Oscillatory Correlates of Conflict Anticipation and Response Slowing

Proactive control allows us to anticipate environmental changes and adjust behavioral strategy. In the laboratory, investigators have used a number of different behavioral paradigms, including the stop-signal task (SST), to examine the neural processes of proactive control. Previous functional MRI studies of the SST have demonstrated regional responses to conflict anticipation-the likelihood of a stop signal or P(stop) as estimated by a Bayesian model-and reaction time (RT) slowing and how these responses are interrelated. Here, in an electrophysiological study, we investigated the time-frequency domain substrates of proactive control. The results showed that conflict anticipation as indexed by P(stop) was positively correlated with the power in low-theta band (3-5 Hz) in the fixation (trial onset)-locked interval, and go-RT was negatively correlated with the power in delta-theta band (2-8 Hz) in the go-locked interval. Stimulus prediction error was positively correlated with the power in the low-beta band (12-22 Hz) in the stop-locked interval. Further, the power of the P(stop) and go-RT clusters was negatively correlated, providing a mechanism relating conflict anticipation to RT slowing in the SST. Source reconstruction with beamformer localized these time-frequency activities close to brain regions as revealed by functional MRI in earlier work. These are the novel results to show oscillatory electrophysiological substrates in support of trial-by-trial behavioral adjustment for proactive control.

Novelty Seeking, Harm Avoidance, and Cerebral Responses to Conflict Anticipation: An Exploratory Study

Proactive control allows us to maneuver a changing environment and individuals are distinct in how they anticipate and approach such changes. Here, we examined how individual differences in personality traits influence cerebral responses to conflict anticipation, a critical process of proactive control. We explored this issue in an fMRI study of the stop signal task, in which the probability of stop signal – p(Stop) – was computed trial by trial with a Bayesian model. Higher p(Stop) is associated with prolonged go trial reaction time, indicating conflict anticipation and proactive control of motor response. Regional brain activations to conflict anticipation were correlated to novelty seeking (NS), harm avoidance (HA), reward dependence, as assessed by the Tridimensional Personality Questionnaire, with age and gender as covariates, in a whole-brain linear regression. Results showed that increased anticipation of the stop signal is associated with activations in the bilateral inferior parietal lobules (IPL), right lateral orbitofrontal cortex (lOFC), middle frontal gyrus (MFG), anterior pre-supplementary motor area (pre-SMA), and bilateral thalamus, with men showing greater activation in the IPL than women. NS correlated negatively to activity in the anterior pre-SMA, right IPL, and MFG/lOFC, and HA correlated negatively to activity in the thalamus during conflict anticipation. In addition, the negative association between NS and MFG/lOFC activity was significant in men but not in women. Thus, NS and HA traits are associated with reduced mobilization of cognitive control circuits when enhanced behavioral control is necessary. The findings from this exploratory study characterize the influence of NS and HA on proactive control and provide preliminary evidence for gender differences in these associations.

Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis

Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions in cocaine dependence. To address this issue, we used multivariate pattern analysis (MVPA) to examine how functional connectivity of the thalamus distinguishes 100 cocaine-dependent participants (CD) from 100 demographically matched healthy control individuals (HC). We characterized six task-related networks with independent component analysis of fMRI data of a stop signal task and employed MVPA to distinguish CD from HC on the basis of voxel-wise thalamic connectivity to the six independent components. In an unbiased model of distinct training and testing data, the analysis correctly classified 72% of subjects with leave-one-out cross-validation (p < 0.001), superior to comparison brain regions with similar voxel counts (p < 0.004, two-sample t test). Thalamic voxels that form the basis of classification aggregate in distinct subclusters, suggesting that connectivities of thalamic subnuclei distinguish CD from HC. Further, linear regressions provided suggestive evidence for a correlation of the thalamic connectivities with clinical variables and performance measures on the stop signal task. Together, these findings support thalamic circuit dysfunction in cognitive control as an important neural marker of cocaine dependence.

A dual but asymmetric role of the dorsal anterior cingulate cortex in response inhibition and switching from a non-salient to salient action

Response inhibition and salience detection are among the most studied psychological constructs of cognitive control. Despite a growing body of work, how inhibition and salience processing interact and engage regional brain activations remains unclear. Here, we examined this issue in a stop signal task (SST), where a prepotent response needs to be inhibited to allow an alternative, less dominant response. Sixteen adult individuals performed two versions of the SST each with 25% (SST25) and 75% (SST75) of stop trials. We posited that greater regional activations to the infrequent trial type in each condition (i.e., to stop as compared to go trials in SST25 and to go as compared to stop trials in SST75) support salience detection. Further, successful inhibition in stop trials requires attention to the stop signal to trigger motor inhibition, and the stop signal reaction time (SSRT) has been used to index the efficiency of motor response inhibition. Therefore, greater regional activations to stop as compared to go success trials in association with the stop signal reaction time (SSRT) serve to expedite response inhibition. In support of an interactive role, the dorsal anterior cingulate cortex (dACC) increases activation to salience detection in both SST25 and SST75, but only mediates response inhibition in SST75. Thus, infrequency response in the dACC supports motor inhibition only when stopping has become a routine. In contrast, although the evidence is less robust, the pre-supplementary motor area (pre-SMA) increases activity to the infrequent stimulus and supports inhibition in both SST25 and SST75. These findings clarify a unique role of the dACC and add to the literature that distinguishes dACC and pre-SMA functions in cognitive control.

Power spectrum scale invariance as a neural marker of cocaine misuse and altered cognitive control

BACKGROUND

Magnetic resonance imaging (MRI) has highlighted the effects of chronic cocaine exposure on cerebral structures and functions, and implicated the prefrontal cortices in deficits of cognitive control. Recent investigations suggest power spectrum scale invariance (PSSI) of cerebral blood oxygenation level dependent (BOLD) signals as a neural marker of cerebral activity. We examined here how PSSI is altered in association with cocaine misuse and impaired cognitive control.

METHODS

Eighty-eight healthy (HC) and seventy-five age and gender matched cocaine dependent (CD) adults participated in functional MRI of a stop signal task (SST). BOLD images were preprocessed using standard procedures in SPM, including detrending, band-pass filtering (0.01-0.25 Hz), and correction for head motions. Voxel-wise PSSI measures were estimated by a linear fit of the power spectrum with a log-log scale. In group analyses, we examined differences in PSSI between HC and CD, and its association with clinical and behavioral variables using a multiple regression. A critical component of cognitive control is post-signal behavioral adjustment, which is compromised in cocaine dependence. Therefore, we examined the PSSI changes in association with post-signal slowing (PSS) in the SST.

RESULTS

Compared to HC, CD showed decreased PSS and PSSI in multiple frontoparietal regions. PSSI was positively correlated with PSS in HC in multiple regions, including the left inferior frontal gyrus (IFG) and right supramarginal gyrus (SMG), which showed reduced PSSI in CD.

CONCLUSIONS

These findings suggest disrupted connectivity dynamics in the fronto-parietal areas in association with post-signal behavioral adjustment in cocaine addicts. These new findings support PSSI as a neural marker of impaired cognitive control in cocaine addiction.

The effects of methylphenidate on cerebral responses to conflict anticipation and unsigned prediction error in a stop-signal task

To adapt flexibly to a rapidly changing environment, humans must anticipate conflict and respond to surprising, unexpected events. To this end, the brain estimates upcoming conflict on the basis of prior experience and computes unsigned prediction error (UPE). Although much work implicates catecholamines in cognitive control, little is known about how pharmacological manipulation of catecholamines affects the neural processes underlying conflict anticipation and UPE computation. We addressed this issue by imaging 24 healthy young adults who received a 45 mg oral dose of methylphenidate (MPH) and 62 matched controls who did not receive MPH prior to performing the stop-signal task. We used a Bayesian Dynamic Belief Model to make trial-by-trial estimates of conflict and UPE during task performance. Replicating previous research, the control group showed anticipation-related activation in the presupplementary motor area and deactivation in the ventromedial prefrontal cortex and parahippocampal gyrus, as well as UPE-related activations in the dorsal anterior cingulate, insula, and inferior parietal lobule. In group comparison, MPH increased anticipation activity in the bilateral caudate head and decreased UPE activity in each of the aforementioned regions. These findings highlight distinct effects of catecholamines on the neural mechanisms underlying conflict anticipation and UPE, signals critical to learning and adaptive behavior.