Submission 202
Fixational Eye Movements and Microsaccade Statistics During Face Recognition
SymposiumTalk-03
Presented by: Keaton Dahl
Recently it was found that microsaccade statistics could be used to differentiate visual self-recognition from processing of other people’s faces (Schwetlick et al., 2025). In the current study we reevaluated this effect using several oculomotor statistics based on high-resolution (1000 Hz) binocular eye-tracking data. The study seeks to capture subtle temporal and spatial patterns that differentiate between viewing one’s own face from viewing the face of a stranger. We developed a multi-stage processing pipeline to detect and organize properties of microsaccades (rates, amplitudes, trajectories) and slow components of fixational eye movements (diffusion constants, Hurst exponent). Using stimulus-locked analyses, we show that this approach allows for the quantification of microsaccade parameters and their relationship to visual attention and face processing. As a potential application we suggest that involuntary, fine-grained oculomotor responses can serve as biometric signatures of self-identification.