Simultaneous EEG-fMRI dataset

Published: 2 October 2023| Version 2 | DOI: 10.17632/crhybxpdy6.2
Contributors:
Jonathan Gallego-Rudolf,
,
,
,

Description

This multimodal neuroimaging repository comprises simultaneously and independently acquired Electroencephalographic (EEG) and Magnetic Resonance Imaging (MRI) data, originally presented in our research article: “Preservation of EEG spectral power features during simultaneous EEG-fMRI”. Eyes-closed and eyes-open resting-state EEG data were recorded outside the Magnetic Resonance (MR) environment, inside the MR scanner without image acquisition and during the simultaneous acquisition of functional MRI (fMRI). Additionally, participants performed an eyes opening-eyes closure block-design task during the outside scanner and simultaneous EEG-fMRI conditions. The EEG data acquired outside the scanner provides a reference signal free of MR-related artifacts, the data acquired inside the scanner records the contribution of the ballistocardiographic (BCG) but not the gradient artifact, and the EEG recorded during fMRI acquisition captures both the gradient and the BCG artifacts. Functional MRI data were obtained with and without simultaneous EEG recording, and structural images were collected with and without the subjects wearing the EEG cap. This represents one of the largest open-access EEG-fMRI datasets available and will enable other researchers to: 1) Characterize the impact of gradient and BCG artifacts on EEG data, 2) Assess the effectiveness of novel artifact removal approaches, 3) Perform hardware-setup comparison studies, 4) Address the quality of structural and functional MRI data collected with this EEG cap, and 5) Validate multimodal integrative analysis on simultaneously acquired resting-state and task EEG-fMRI.

Files

Steps to reproduce

This dataset includes 20 male participants (mean/std age = 26/3.8 years) without any diagnosis of neurological/psychiatric diseases or substance abuse history. EEG data were collected using a GES 400 MR-compatible system equipped with a 32-channel Geodesic Sensor Net EEG cap (Electrical Geodesics Inc., OR, USA), with a sampling rate of 1000 Hz and Cz as the reference electrode. Net Station software v. 5.3 was used for data recording. Brain images were obtained with a Discovery-MR750 3.0 T MR scanner (General Electric, WI, USA), using a 32-channel array head coil. Functional images were acquired using a BOLD-contrast Gradient Recalled Echoplanar Imaging T2* sequence, while anatomical data were collected using a Spoiled Gradient Recalled sequence. MRIs were anonymized using the mri_deface tool from Freesurfer. Both EEG and MRI data were organized according to the BIDS standard specification using the data2bids function from Fieldtrip and the heuristic DICOM converter tool, respectively. The derivatives folder includes the gradient artifact corrected version of the EEG data files acquired simultaneously with fMRI. The artifact was removed using an average artifact subtraction approach implemented in the Net Station software v. 5.3. Further details regarding data collection and preparation of the repository can be found in our data article: “Simultaneous and independent Electroencephalography and Magnetic Resonance Imaging: A multimodal neuroimaging dataset”.

Institutions

Universidad Nacional Autonoma de Mexico Instituto de Neurobiologia

Categories

Magnetic Resonance Imaging, Neuroimaging, Electroencephalography, Multimodality Imaging

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