Exploring the role of electrode density in capturing spatiotemporal dynamics of resting-state networks with EEG

Abstract This study investigates the role of electrode density in capturing resting-state brain activity, an area of significant clinical relevance, where electroencephalography (EEG) is favored for its cost-efficiency. We analyze how different electrode configurations affect the precision of cortical current density estimation in EEG recordings. Using exact Low-Resolution Electromagnetic Tomography (eLORETA), we estimated the cortical current density in regions of interest linked to Resting State Networks (RSN). Point process analysis was employed to identify regions of high activity over time, revealing dynamic brain salient activity patterns, or brain maps. We evaluated the impact of electrode density by comparing 64-channel and 20-channel configurations and found that both configurations yielded similar and consistent brain maps. To confirm the robustness of our approach, we assessed the Berger effect in eyes-closed (EC) versus eyes-open (EO) conditions, observing that the functional differences between EC and EO states remained stable regardless of electrode density, aligning with previous research. Conversely, randomization of data or the use of non-homogeneous electrode configurations disrupted the resulting patterns, highlighting the physiological relevance of our methodology. Overall, our results demonstrate that this approach reliably captures the spatiotemporal dynamics of brain activity, even with fewer electrodes, and holds promise for broader clinical applications.