Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes.

Details

Serval ID
serval:BIB_32123E63B345
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes.
Journal
Scientific data
Author(s)
Pascucci D., Tourbier S., Rué-Queralt J., Carboni M., Hagmann P., Plomp G.
ISSN
2052-4463 (Electronic)
ISSN-L
2052-4463
Publication state
Published
Issued date
19/01/2022
Peer-reviewed
Oui
Volume
9
Number
1
Pages
9
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Abstract
We describe the multimodal neuroimaging dataset VEPCON (OpenNeuro Dataset ds003505). It includes raw data and derivatives of high-density EEG, structural MRI, diffusion weighted images (DWI) and single-trial behavior (accuracy, reaction time). Visual evoked potentials (VEPs) were recorded while participants (n = 20) discriminated briefly presented faces from scrambled faces, or coherently moving stimuli from incoherent ones. EEG and MRI were recorded separately from the same participants. The dataset contains raw EEG and behavioral data, pre-processed EEG of single trials in each condition, structural MRIs, individual brain parcellations at 5 spatial resolutions (83 to 1015 regions), and the corresponding structural connectomes computed from fiber count, fiber density, average fractional anisotropy and mean diffusivity maps. For source imaging, VEPCON provides EEG inverse solutions based on individual anatomy, with Python and Matlab scripts to derive activity time-series in each brain region, for each parcellation level. The BIDS-compatible dataset can contribute to multimodal methods development, studying structure-function relations, and to unimodal optimization of source imaging and graph analyses, among many other possibilities.
Pubmed
Web of science
Open Access
Yes
Funding(s)
Swiss National Science Foundation / Programmes / CRSII5_170873
Create date
31/01/2022 16:14
Last modification date
05/02/2022 7:33
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