Evidence map›Paper›PMID 42331932›Full record

ArticleScientific reports2026

Forward model of rat electroencephalogram: influence of inhomogeneous and anisotropic skull.

David Kuratko, Vlastimil Koudelka, Cestmir Vejmola, Filip Dusek, Frantisek Kucera, Daniel K Wójcik, Tomas Palenicek, Jaroslav Lacik

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

David KuratkoFaculty of Electrical Engineering and Communication, Brno University of Technology, Brno, 61600, Czech Republic. xkurat01@vut.cz.
Vlastimil KoudelkaNational Institute of Mental Health, Klecany, 250 67, Czech Republic.
Cestmir VejmolaNational Institute of Mental Health, Klecany, 250 67, Czech Republic.
Filip DusekFaculty of Electrical Engineering and Communication, Brno University of Technology, Brno, 61600, Czech Republic.
Frantisek KuceraFaculty of Chemistry, Brno University of Technology, Brno, 61200, Czech Republic.
Daniel K WójcikNencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093, Warsaw, Poland.
Tomas PalenicekNational Institute of Mental Health, Klecany, 250 67, Czech Republic.
Jaroslav LacikFaculty of Electrical Engineering and Communication, Brno University of Technology, Brno, 61600, Czech Republic. lacik@vut.cz.

Funding

Grantová Agentura České Republiky 23-07578K
6 · The paper itself

Abstract

The forward modeling of electroencephalogram (EEG) plays a crucial role in solving source localization and, consequently, in the detection of EEG connectivity networks in the rat brain. We investigated the impact of skull tissue properties-inhomogeneities, anisotropy, and thickness-on measured skull potentials. Five cuboid head phantoms with identical geometry, differing in skull material parameters, and a realistic head phantom with varying skull anisotropy ratios were tested. Simulations were verified by four electromagnetic solvers and an EEG measurement on a physical phantom. The cuboid phantom with sutures yields similar electric potentials as the isotropic one, but noticeable differences appear at electrodes near sutures, particularly in real brain sensing of somatosensory, motor, and visual cortices, as well as the retrosplenial dysgranular cortex, for a dipole located close to the surface. Skull thickness reduces potentials at the top electrodes but increases them at side electrodes, in real brain sensing somatosensory, auditory, association, and entorhinal cortices. Skull anisotropy alters electric potentials with differences up to 60% for dipoles near electrodes at the limiting anisotropy ratio of 10:1, and its effect decreases with increasing distance. Varying anisotropy ratios (10:1 to 1.3:1) show that nearby dipoles are the most affected, while the impact is reduced for lower, more realistic ratios (1.3:1 to 1.8:1) and for more distant sources. This trend was consistently observed in realistic head phantoms as well. Tangential dipoles are most strongly affected in the vicinity of the electrodes and gradually become radial at more distant positions near the inner skull surface.

Indexed as

BrainElectroencephalographyModels, NeurologicalSkullAnimalsAnisotropyPhantoms, ImagingRats

Identifiers

PMID42331932
PMCPMC13575132

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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.