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Toward precision EEG: Assessing the reliability of individual-level ERPs across EEG Systems

Korisky, A.; Rabinovitch, E.; Har-shai Yahav, P.; McCandliss, B.; Zion Golumbic, E.

2025-11-11 neuroscience
10.1101/2025.11.10.687573 bioRxiv
Show abstract

Event-related potentials (ERPs) are among the most established tools for studying the neural mechanisms of perception and cognition. Advancing toward precision EEG, however, places new demands for a better understanding of how reliable neural markers are at the individual subject level. We conducted two complementary experiments to examine the reliability of N100 and P300 components in an auditory oddball paradigm with three sounds (Standard, Target, and Novel). In Experiment 1, we evaluated the consistency at both the group level and the individual level across four EEG systems: one research-grade wired system (BioSemi) and three mobile devices--Smarting, DSI-24, and EPOC X. At the group level, all systems demonstrated the canonical N100 and P300 components; however, the EPOC X system showed a significantly reduced signal-to-noise ratio compared to the others. At the individual level, temporal and spatial clustering analyses showed that N100 and P300 components were detectable in most individuals (70-85%), with additional significant responses appearing outside this range. We further calculated the similarity of individual responses across participants ("typicality index"), which revealed highly consistent responses to Standard and Novel sounds, alongside divergent patterns of responses to Targets. In Experiment 2, we assessed the within-participant reliability of N100 and P300 using a test-retest design. Results indicated high within-participant consistency of response patterns for all three stimuli, demonstrating that individual ERPs remain reliably stable over time, even when they deviate from canonical group-level patterns. The current study contributes to the ongoing discussion regarding the utility and reliability of ERP-based metrics for precision imaging and highlights important methodological considerations for their practical implementation.

Published in Frontiers in Human Neuroscience (predicted rank #13) · training set

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