Evidence map›Paper›PMID 39440187›Full record

ArticleFrontiers in neuroscience2024

Investigating the effect of template head models on Event-Related Potential source localization: a simulation and real-data study.

Emma Depuydt, Yana Criel, Miet De Letter, Pieter van Mierlo

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Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Physiologically Guided Modeling for EEG Multichannel Signals.Bioengineering (Basel, Switzerland) · 2026
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Emma DepuydtMedical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.
Yana CrielBrainComm Research Group, Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
Miet De LetterBrainComm Research Group, Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
Pieter van MierloMedical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Event-Related Potentials (ERPs) are valuable for studying brain activity with millisecond-level temporal resolution. While the temporal resolution of this technique is excellent, the spatial resolution is limited. Source localization aims to identify the brain regions generating the EEG data, thus increasing the spatial resolution, but its accuracy depends heavily on the head model used. This study compares the performance of subject-specific and template-based head models in both simulated and real-world ERP localization tasks. Methods: Simulated data mimicking realistic ERPs was created to evaluate the impact of head model choice systematically, after which subject-specific and template-based head models were used for the reconstruction of the data. The different modeling approaches were also applied to a face recognition dataset. Results: The results indicate that the template models capture the simulated activity less accurately, producing more spurious sources and identifying less true sources correctly. Furthermore, the results show that while creating more accurate and detailed head models is beneficial for the localization accuracy when using subject-specific head models, this is less the case for template head models. The main N170 source of the face recognition dataset was correctly localized to the fusiform gyrus, a known face processing area, using the subject-specific models. Apart from the fusiform gyrus, the template models also reconstructed several other sources, illustrating the localization inaccuracies. Discussion: While template models allow researchers to investigate the neural generators of ERP components when no subject-specific MRIs are available, it could lead to misinterpretations. Therefore, it is important to consider a priori knowledge and hypotheses when interpreting results obtained with template head models, acknowledging potential localization errors.

Indexed as

EEGEEG source localizationERPEvent-Related Potentialshead modelingsource estimation

Identifiers

PMID39440187
PMCPMC11493687

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.