(Micro)saccade-related potentials during face recognition: A study combining EEG, eye-tracking, and deconvolution modeling

扫视 眼球运动 刺激(心理学) 心理学 固定(群体遗传学) 眼动 脑电图 凝视 面部表情 认知心理学 Microsaccade 负效应 沟通 神经科学 囊状掩蔽 计算机视觉 计算机科学 医学 人口 环境卫生 精神分析
作者
Lisa Spiering,Olaf Dimigen
出处
期刊:Attention, perception & psychophysics [Springer Science+Business Media]
被引量:1
标识
DOI:10.3758/s13414-024-02846-1
摘要

Abstract Under natural viewing conditions, complex stimuli such as human faces are typically looked at several times in succession, implying that their recognition may unfold across multiple eye fixations. Although electrophysiological (EEG) experiments on face recognition typically prohibit eye movements, participants still execute frequent (micro)saccades on the face, each of which generates its own visuocortical response. This finding raises the question of whether the fixation-related potentials (FRPs) evoked by these tiny gaze shifts also contain psychologically valuable information about face processing. Here, we investigated this question by corecording EEG and eye movements in an experiment with emotional faces (happy, angry, neutral). Deconvolution modeling was used to separate the stimulus ERPs to face onset from the FRPs generated by subsequent microsaccades-induced refixations on the face. As expected, stimulus ERPs exhibited typical emotion effects, with a larger early posterior negativity (EPN) for happy/angry compared with neutral faces. Eye tracking confirmed that participants made small saccades in 98% of the trials, which were often aimed at the left eye of the stimulus face. However, while each saccade produced a strong response over visual areas, this response was unaffected by the face’s emotional expression, both for the first and for subsequent (micro)saccades. This finding suggests that the face’s affective content is rapidly evaluated after stimulus onset, leading to only a short-lived sensory enhancement by arousing stimuli that does not repeat itself during immediate refixations. Methodologically, our work demonstrates how eye tracking and deconvolution modeling can be used to extract several brain responses from each EEG trial, providing insights into neural processing at different latencies after stimulus onset.
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