Hemispheric segregation is evident in early perception, not just higher cognition.

INTRODUCTION

Functional hemispheric segregation, the organization of distinct cognitive functions into separate hemispheres, has so far been investigated mainly using behavioral measures or fMRI. Whether such segregation manifests at early perceptual stages, however, remains unknown. The present study is the first to test Gerrits' segregation bias model using EEG, examining lateralization of early ERP components (N1/N170) across language, face, and emotional face processing.

METHODS

The present study is based on an openly available EEG dataset obtained from OpenNeuro. We analyzed data from left-, mixed-, and right-handed participants to investigate the influence of handedness and sex on early functional hemispheric segregation. Hemispheric lateralization was assessed using early event-related potential components (N1/N170) across language, face, and emotional face processing tasks.

RESULTS

Consistent with predictions, typical lateralization patterns were most frequent, yet substantial individual variability was observed. Notably, "crowding" of multiple functions within one hemisphere - either left or right - was among the most common patterns, highlighting the probabilistic nature of hemispheric organization. These effects emerged at early perceptual stages, indicating that hemispheric segregation is not solely a consequence of later cognitive or decisional processes.

DISCUSSION: We suggest that differences in individual processing styles may partly explain variability in lateralization, particularly for simple recognition tasks. Our findings extend the segregation bias model by demonstrating that functional hemispheric segregation is already detectable during early perceptual processing and is modulated by both handedness and sex. This study underscores the importance of EEG for capturing the temporal dynamics of hemispheric organization and provides a novel perspective on the interplay between individual differences and early neural specialization.