Joint Analysis of Eye Blinks and Brain Activity to Investigate Attentional Demand during a Visual Search Task

Sciaraffa, Nicolina; Borghini, Gianluca; Di Flumeri, Gianluca; Cincotti, Febo; Babiloni, Fabio; Aricò, Pietro · 2021 · Crossref

DOI: 10.3390/brainsci11050562

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Summary

This study investigates the neurophysiological correlates of attentional demand by jointly analyzing eye blink activity and high-density electroencephalography (EEG) data during a visual search task. The research addresses the need for continuous, non-invasive monitoring of attention levels, which is critical for situational awareness and decision-making in operational contexts. While previous studies often relied on time-locked analyses or invasive techniques like fMRI, this work aims to characterize the association between endogenous neural mechanisms and eye blinks without imposing strict timing constraints, thereby offering a more naturalistic assessment of cognitive load. The experimental design involved twelve healthy participants performing a Conjunction Search Task (CST) with two conditions: a "Low" demand condition requiring the identification of a target based on a single feature (color), and a "High" demand condition requiring the conjunction of two features (color and orientation). High-density EEG signals were recorded using 61 electrodes, and eye blinks were monitored via electrooculography. Data processing included artifact removal, source localization using standardized low-resolution brain electromagnetic tomography (sLORETA) to estimate activity in ten regions of interest (ROIs) within the dorsal and ventral attention networks, and connectivity analysis using Partial Directed Coherence (PDC). Behavioral performance was assessed using the Inverse Efficiency Score. The results demonstrated that higher attentional demand significantly reduced the number of eye blinks. Neurophysiologically, the High condition elicited statistically significant spatial and spectral modulations in brain activity. Specifically, there was an increase in theta and beta band activity over frontal and central areas, alongside a decrease in alpha band activity in frontal, central, and parietal regions. Source localization confirmed increased activation in the Dorsal Attention Network (Frontal Eye Fields and Intraparietal Sulcus) and decreased activation in the Ventral Attention Network (Temporoparietal Junction) during high-demand trials. Crucially, the joint analysis revealed a strong correlation between eye blink rate and neural activity: blink rate showed a high positive correlation ($R > 0.7$) with anterofrontal activity at 8 Hz and centroparietal activity at 12 Hz, and a moderate negative correlation ($R = -0.62$) with the participation of the right Intraparietal Sulcus in the alpha band. These findings suggest that eye blink rate serves as a robust, unobtrusive proxy for underlying neural mechanisms governing attentional investment. By establishing a significant link between simple ocular measures and complex brain network dynamics, the study supports the development of real-time monitoring systems for cognitive workload. This approach allows for the assessment of attentional states without the need for cumbersome high-density EEG setups, facilitating applications in clinical diagnostics, human-computer interaction, and operational safety monitoring.

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• gaze based attention detection