Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation

阳性分类优势:基于脑振荡追踪时间进程

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Abstract

The present study aimed to explore the modulation of frequency bands (alpha, beta, theta) underlying the positive facial expressions classification advantage within different post-stimulus time intervals (100-200 ms, 200-300 ms, 300-400 ms). For this purpose, we recorded electroencephalogram (EEG) activity during an emotion discrimination task for happy, sad and neutral faces. The correlation between the non-phase-locked power of frequency bands and reaction times (RTs) was assessed. The results revealed that beta played a major role in positive classification advantage (PCA) within the 100-200 and 300-400 ms intervals, whereas theta was important within the 200-300 ms interval. We propose that the beta band modulated the neutral and emotional face classification process, and that the theta band modulated for happy and sad face classification.

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