Positive and negative affect in adolescent self-evaluation: Psychometric information in single trials used to generate dimension-specific ERPs and neural source models

We examined brain mechanisms of self-evaluation in a sample of adolescents using dense array EEG (dEEG), neural source analysis, and a novel psychometric weighting method. Each trial of the self-evaluation task was weighted according to its correlation with negative affect and positive affect, such that unique ERP averages were constructed for each mood dimension. Results support the hypothesis that the emotional influence on self-appraisal is dimension specific. Negative affect was associated with more robust ERP responses 300ms into the decision-making epoch. Affect-weighted source analyses further differentiated dorsal-posterior and ventral-anterior features of brain activity. The integration of psychometric weights and dEEG neural source analysis may provide new clues to the neural mechanisms of affective influence on self-evaluative cognition.