Toward precision EEG: Assessing the reliability of individual-level ERPs across EEG Systems Article Swipe
Adi Korisky
,
Eshsed Rabinovitch
,
Paz Har-shai Yahav
,
Bruce D. McCandliss
,
Elana Zion Golumbic
,
Eshed Rabinovitch
,
Paz Har-shai Yahav
,
Bruce McCandliss
,
Elana Zion Golumbic
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.10.687573
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.10.687573
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.
Related Topics
Concepts
N100
Reliability (semiconductor)
Electroencephalography
Computer science
Metric (unit)
Perception
Consistency (knowledge bases)
Psychology
Speech recognition
Pattern recognition (psychology)
Similarity (geometry)
Artificial intelligence
Cluster analysis
Representation (politics)
Event-related potential
Cognitive psychology
Brain–computer interface
Machine learning
Mismatch negativity
Audiology
Canonical correlation
Endophenotype
Interpretability
Neurophysiology
P200
Metadata
- Type
- article
- Landing Page
- https://doi.org/10.1101/2025.11.10.687573
- https://www.biorxiv.org/content/biorxiv/early/2025/11/11/2025.11.10.687573.full.pdf
- OA Status
- green
- References
- 109
- OpenAlex ID
- https://openalex.org/W7105196278
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W7105196278Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2025.11.10.687573Digital Object Identifier
- Title
-
Toward precision EEG: Assessing the reliability of individual-level ERPs across EEG SystemsWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-11-11Full publication date if available
- Authors
-
Adi Korisky, Eshsed Rabinovitch, Paz Har-shai Yahav, Bruce D. McCandliss, Elana Zion Golumbic, Eshed Rabinovitch, Paz Har-shai Yahav, Bruce McCandliss, Elana Zion GolumbicList of authors in order
- Landing page
-
https://doi.org/10.1101/2025.11.10.687573Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2025/11/11/2025.11.10.687573.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2025/11/11/2025.11.10.687573.full.pdfDirect OA link when available
- Concepts
-
N100, Reliability (semiconductor), Electroencephalography, Computer science, Metric (unit), Perception, Consistency (knowledge bases), Psychology, Speech recognition, Pattern recognition (psychology), Similarity (geometry), Artificial intelligence, Cluster analysis, Representation (politics), Event-related potential, Cognitive psychology, Brain–computer interface, Machine learning, Mismatch negativity, Audiology, Canonical correlation, Endophenotype, Interpretability, Neurophysiology, P200Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
109Number of works referenced by this work
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