Distinct oscillatory signatures of emotional reactivity and cognitive reappraisal revealed through multiclass EEG decoding.

Cognitive reappraisal is a core emotion-regulation strategy; yet identifying interpretable neurophysiological markers that distinguish emotional reactivity from regulation remains challenging using traditional univariate electroencephalography (EEG) approaches. This proof-of-concept study tested whether band-limited oscillatory EEG features extracted from a standard reappraisal task can discriminate three affective/regulatory states at the single-trial level: neutral viewing, natural negative viewing, and cognitive reappraisal of negative stimuli. Electroencephalography was recorded in 53 adults during a cued emotion-regulation task using neutral and attachment-related negative pictures. For each trial, band-limited power was computed within a stimulus window across predefined scalp regions and frequency bands (theta, alpha, and beta). Multiclass decoding was implemented by using a linear support vector machine within an error-correcting output code framework with repeated within-subject cross-validation and permutation testing. The classifier successfully discriminated the three conditions above chance, indicating that distributed oscillatory EEG features contain reliable information distinguishing emotional reactivity from cognitive reappraisal at the single-trial level. Among the tested representations, alpha-band power aggregated across scalp regions provided the most consistent restricted feature set for decoding. These findings suggest that large-scale oscillatory dynamics, particularly in the alpha band, capture a stable component of neural processing associated with regulatory control during emotional picture viewing.