Empathic Traits Modulate Oscillatory Dynamics Revealed by Time-Frequency Analysis During Body Language Reading

Empathy has been linked to enhanced processing of social information, yet the neurophysiological correlates of such individual differences remain underexplored. Objectives: The aim of this study was to investigate how individual differences in trait empathy are reflected in oscillatory brain activity during the perception of non-verbal social cues. Methods: In this EEG study involving 30 participants, we examined spectral and time-frequency dynamics associated with trait empathy during a visual task requiring the interpretation of others' body gestures. Results: FFT Power spectral analyses (applied to alpha/mu, beta, high beta, and gamma bands) revealed that individuals with high empathy quotients (High-EQ) exhibited a tendency for increased beta-band activity over frontal regions and markedly decreased alpha-band activity over occipito-parietal areas compared to their low-empathy counterparts (Low-EQ), suggesting heightened attentional engagement and reduced cortical inhibition during social information processing. Similarly, time-frequency analysis using Morlet wavelets showed higher alpha power in Low-EQ than High-EQ people over occipital sites, with no group differences in mu suppression or desynchronization (ERD) over central sites, challenging prior claims linking mu ERD to mirror neuron activity in empathic processing. These findings align with recent literature associating frontal beta oscillations with top-down attentional control and emotional regulation, and posterior alpha with vigilance and sensory disengagement. Conclusions: Our results indicate that empathic traits are differentially reflected in anterior and posterior oscillatory dynamics, supporting the notion that individuals high in empathy deploy greater cognitive and attentional resources when decoding non-verbal social cues. These neural patterns may underlie their superior ability to interpret body language and mental states from visual input.