High-definition transcranial direct current stimulation over the right dorsolateral prefrontal cortex reduces risk-taking

Sex-based differences in fairness norm compliance and neural circuitry

Human behavior often aligns with fairness norms, either voluntarily or under external pressure, like sanctions. Prior research has identified distinct neural activation patterns associated with voluntary and sanction-based compliance or non-compliance with fairness norms. However, an investigation gap exists into potential neural connectivity patterns and sex-based differences. To address this, we conducted a study using a monetary allocation game and functional magnetic resonance imaging to examine how neural activity and connectivity differ between sexes across three norm compliance conditions: voluntary, sanction-based, and voluntary post-sanctions. Fifty-five adults (27 females) participated, revealing that punishment influenced decisions, leading to strategic calculations and reduced generosity in voluntary compliance post-sanctions. Moreover, there were sex-based differences in neural activation and connectivity across the different compliance conditions. Specifically, the connectivity between the right dorsolateral prefrontal cortex and right dorsal anterior insular appeared to mediate intuitive preferences, with variations across norm compliance conditions and sexes. These findings imply potential sex-based differences in intuitive motivation for diverse norm compliance conditions. Our insights contribute to a better understanding of the neural pathways involved in fairness norm compliance and clarify sex-based differences, offering implications for future investigations into psychiatric and neurological disorders characterized by atypical socialization and mentalizing.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background

Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD).

Aims

This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM).

Methods

One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8-month follow-up of abstinence. CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ (HCQfollow-up-HCQbaseline). Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.

Results

CPM could predict craving changes induced by long-term abstinence, as shown by a significant correlation between predicted and actual HCQfollow-up (r=0.417, p<0.001) and changes in HCQ (negative: r=0.334, p=0.002；positive: r=0.233, p=0.038). Identified craving-related prediction networks included the somato-motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal-parietal network (FPN)-SMN, FPN-DMN and FPN-SALN and increased connectivity of subcortical network (SCN)-DMN, SCN-SALN and SCN-SMN were positively correlated with craving levels.

Conclusions

These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.