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

David Pascucci,Joan Rué-Queralt,Patric Hagmann,Margherita Carboni,Gijs Plomp,Sebastien Tourbier

doi:10.1038/s41597-021-01116-1

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.

Highlights

Background & SummaryVisual evoked potentials (VEPs) have a long record of shedding light on the spatial and temporal dynamics of large-scale neural processing in the brain[1,2]
The VEP provides a millisecond by millisecond recording of whole-brain activity dynamics, and has a rich distribution of temporal frequencies that provides further insight into the functionality of brain processes[13,14]
From VEPs recorded across the scalp, the underlying distributed patterns of brain activity can be estimated using an inverse solution based on anatomical constraints[15,16,17,18]

Summary

Introduction

Background & SummaryVisual evoked potentials (VEPs) have a long record of shedding light on the spatial and temporal dynamics of large-scale neural processing in the brain[1,2]. The VEPCON dataset[31] combines raw EEG data, T1-weighted (T1w) MRI, and DWI for 20 human partici pants, with as derivatives, VEPs, inverse solution matrices, brain parcellations and connectomes at 5 different spatial scales (Fig. 1). High-density EEG was recorded in two active paradigms where participants categorically discriminated face images from scrambled counterparts, or coherent from incoherent motion in random dot kinematograms.

Results

Conclusion