Neuroscience
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Patients with Bipolar Disorder type I (BD-I) exhibit maladaptive risky decision-making, which is related to impulsivity, suicide attempts, and aggressive behavior. Currently, there is a lack of effective predictive methods for early intervention in risky behaviors for patients with BD-I. This study aimed to predict risky behavior in patients with BD-I using resting-state functional magnetic resonance imaging (rs-fMRI). ⋯ The dEC-based linear regression-CPM model exhibited significant predictive ability for the adjusted pump scores in BD-I, while no significant predictive power was observed in HC. Furthermore, this model successfully predicted non-planning impulsiveness, motor impulsiveness, and BIS total score, but failed for attentional impulsiveness in BD-I. These findings provide a foundation for future work in predicting risky behaviors of psychiatric patients by using voxel-wise dEC underlying resting state.
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This study aimed to elucidate the spatial and temporal patterns of brain neural activity that are associated with cold and hot sensations. Participants (n = 20) sat in a controlled room with their eyes closed and received local thermal stimuli to the right fingers using a Peltier apparatus. The thermal stimuli were repeated 40 times using a paired-thermal stimulus paradigm, comprising a 15 s-reference stimulus (32 °C), followed by 10 s-conditioned stimuli (24 °C and 40 °C, cold and hot conditions, respectively), for which 15-channel electroencephalography (EEG) signals were continuously monitored. ⋯ The right precentral gyrus, precuneus, medial frontal gyrus, middle frontal gyrus, superior frontal gyrus, cuneus, cingulate gyrus, left precentral gyrus, middle occipital gyrus, and cingulate gyrus were activated in both cold and hot conditions. In most activated regions, EEG power temporal changes were observed across the frequency ranges and were different between the two conditions. These results may suggest that cold and hot sensations are processed through different temporal brain neural activity patterns in overlapping brain regions.
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Internet gaming disorder (IGD) is increasingly recognized as a public concern for its adverse impacts on cognition and mental health. In IGD, the transition from goal-directed actions to habitual and eventually compulsive behaviors is accompanied by altered neural response within the dorsal anterior cingulate cortex (dACC), a critical region involved in conscious actions. However, the neurochemical profile of the dACC in IGD and its relationship with behavioral awareness remain poorly understood. ⋯ In an independent cohort of 107 participants, the positive association between awareness and dACC glutamate concentration was replicated. These findings suggest that reduced dACC glutamate in IGD may underlie diminished awareness of maladaptive habitual behaviors. Enhancing dACC neural excitability through neuromodulation or mindfulness training could represent a potential intervention to restore behavioral awareness.
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Empathy is central to individual and societal well-being. Numerous studies have examined how trait of empathy affects prosocial behavior. However, little studies explored the psychological and neural mechanisms by which different dimensions of trait empathy influence prosocial behavior. ⋯ Further regression analysis results indicate that EC, rather than other dimensions of trait empathy, can positively predict LPP amplitude and negatively predict beta-band activity. These results indicated that participants with higher EC scores may experience heightened emotional arousal and the vicarious experience of others' emotions while processing donation information. Our work adds weight to understanding the relationship between trait empathy and prosocial behavior and provides electrophysiological evidence.
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The objective of this study is to examine the efficacy of magnetic resonance imaging (MRI) features and peripheral blood biomarkers in assessing cognitive function in patients with cerebral small vessel disease (CSVD). A total of 58 CSVD patients were recruited. Six features of white matter hyperintensities (WMHs) were derived from MRI scans. ⋯ An integrated model incorporating WMHs features, neurodegenerative biomarkers, and neuroinflammatory markers was developed, demonstrating high predictive accuracy for cognitive impairment with an area under the curve (AUC) of 0.95 (accuracy 0.88, sensitivity 0.87, specificity 0.89). Another integrated model that includes features of WMHs and inflammatory cytokines for predicting cerebral microbleeds (CMBs) achieved an AUC of 0.95 (accuracy 0.88, sensitivity 0.82, specificity 0.92). Our findings suggest that these markers have the potential to be used for the early detection of cognitive decline and CMBs in patients with CSVD.