Anxiety-related illnesses are highly prevalent in human society. Being able to identify neurobiological markers signaling high trait anxiety could aid the assessment of individuals with high risk for mental illness. Here, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity (rsFC) data to predict the degree of trait anxiety in 76 healthy participants. Using a computational “lesion” approach in CPM, we then examined the weights of the identified main brain areas as well as their connectivity. Results showed that the CPM successfully predicted individual anxiety based on whole-brain rsFC, especially the rsFC between limbic areas and prefrontal cortex. The prediction power of the model significantly decreased from simulated lesions of limbic areas, lesions of the connectivity within limbic areas, and lesions of the connectivity between limbic areas and prefrontal cortex. Importantly, this neural model generalized to an independent large sample (n = 501). These findings highlight important roles of the limbic system and prefrontal cortex in anxiety prediction. Our work provides evidence for the usefulness of connectome-based modeling in predicting individual personality differences and indicates its potential for identifying personality factors at risk for psychopathology.
Alexithymia has been characterized as an impaired ability of emotion processing and regulation. The definition of alexithymia does not include a social component. However, there is some evidence that social cognition may be compromised in individuals with alexithymia. Hence, emotional impairments associated with alexithymia may extend to socially relevant information. Here, we recorded electrophysiological responses of individuals meeting the clinically relevant cut-off for alexithymia (ALEX; n=24) and individuals without alexithymia (NonALEX; n=23) while they viewed affective scenes that varied on the dimensions of sociality and emotional valence during a rapid serial visual presentation task. We found that ALEX exhibited lower accuracy and larger N2 than NonALEX in the perception of social negative scenes. Source reconstruction revealed that the group difference in N2 was localized at the dorsal anterior cingulate cortex. Irrespective of emotional valence, ALEX showed stronger alpha power than NonALEX in social but not nonsocial conditions. Our findings support the hypothesis of social processing being selectively affected by alexithymia, especially for stimuli with negative valence. Electrophysiological evidence suggests altered deployment of attentional resources in the perception of social-specific emotional information in alexithymia. This work sheds light on the neuropsychopathology of alexithymia and alexithymia-related disorders.
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