Face Selective Neural Activity: Comparison Between Fixed and Free Viewing

Abstract

<jats:title>Abstract</jats:title><jats:p>Event Related Potentials (ERPs) are widely used to study category-selective EEG responses to visual stimuli, such as the face-selective N170 component. Typically, this is done by flashing stimuli abruptly at the point of static gaze fixation. While allowing for good experimental control, these paradigms ignore the dynamic role of eye-movements in natural vision. Fixation-related potentials (FRPs) obtained using simultaneous EEG and eye-tracking, overcome this limitation. Various studies have used FRPs to study processes such as lexical processing, target detection and attention allocation. The goal of this study was to compare face-sensitive activity evoked by stimulus abrupt appearance with that evoked by self-controlled gaze fixations on a stimulus. Twelve participants were studied in three experimental conditions: Free-viewing (FRPs), Cued-viewing (FRPs) and Control (ERPs). We used a multiple regression approach to disentangle overlapping activity components. Our results show that the N170 face effect (face vs. non-face) is evident for the first fixation on a stimulus, whether it follows a self-generated saccade or stimulus appearance at fixation point. Furthermore, the N170 exhibits category-specific adaptation in free viewing. The N170 face effect had similar topography across viewing conditions, but there were major differences within each stimulus category. We ascribe these differences to an overlap of the fixation-related Lambda response and the N170. We tested the plausibility of this account using dipole simulations. This study establishes the use of the N170 face effect as a signature of face detection in free-viewing experiments while highlighting the importance of accounting for eye-movement related effects.</jats:p>

Wild lab: A naturalistic free viewing experiment reveals previously unknown EEG signatures of face processing

“…This depletion might override the negative effect of the source usually associated with the N170, which in turn will lead to a generally more positive activation. This amplitude reduction is in line with previous studies (Auerbach-Asch et al, 2019; Buonocore et al, 2020). Notably, the fERP in our study is changing earlier than previously reported (Schweinberger & Neumann, 2016).…”

“…As the combination of these two aspects is what we encounter in our everyday life, it is necessary to combine them to obtain the full picture of naturalistic face perception. Not only are we able to confirm results classically reported in passive perception experiments (Rossion & Jacques, 2008), but we also replicate the findings of one of the first studies combining free viewing and face perception (Auerbach-Asch et al, 2019) comparing fERPs recorded during task-driven free viewing to ERPs in a passive stimulation task using cutout faces. Yet, we could demonstrate that naturalistic face processing will lead to earlier effects, including time points classically defined as the P100, and extend beyond parieto-occipital electrodes, throughout the whole scalp.…”

“…The main goal of this study is the validation and extension of classic experimental results under more naturalistic experimental conditions. While previous studies used naturalistic setups, they either employed everyday stimulus material, but lacked eye movements (Cauchoix et al, 2014; Johnston et al, 2015) or they allowed for eye movements but used artificial stimulus material (Auerbach-Asch et al, 2019; Soto et al, 2018). These studies advanced face perception research, but lacked the crucial combination of embodiment and natural stimulus material.…”

“…These studies advanced face perception research, but lacked the crucial combination of embodiment and natural stimulus material. Previous literature showed that the neural correlates of perception differ between passive and active perception (Auerbach-Asch et al, 2019; Ehinger et al, 2014; Gramann et al, 2010; Kaunitz et al, 2014) and that naturalistic stimuli will lead to different activation from artificial ones (Hasson et al, 2004; Johnston et al, 2015). As the combination of these two aspects is what we encounter in our everyday life, it is necessary to combine them to obtain the full picture of naturalistic face perception.…”

“…Continuous data were visually inspected and artifactual sections were manually marked (muscle artifacts) and noisy channels removed (mean: 25.8, range: [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Next, we used an independent component analysis (ICA, amica12, [56]) to remove components with eye-muscle artifacts [57].…”