Overview
Summary
This dataset is comprised of neuroimaging data collected at the Nathan Kline Institute (NKI). The dataset represents simultaneously collected electroencephalography (EEG) and function magnetic resonance imaging (fMRI) recordings obtained from 22 individuals between the ages of 23 and 51 years-old. EEG data contains 64-channel EEG recordings using a customized Brain Products BrainCapMR consisting of 61 cortical channels, two EOG channels placed below (channel 63) and above (channel 64) the left eye, and one ECG channel (channel 32) placed on the back. This dataset also contains eye tracking and physiological recordings. Eye tracking recordings were collected inside the scanner using EyeLink 1000 (SR Research Ltd.) with eye position and pupil dilation were recorded using an infrared based eye tracker. Physiological recordings were collected using BIOPAC MP150 (BIOPAC Systems, Inc.) using a respiratory transducer belt to monitor breathing. All individuals were consented in accordance and compliance with the Institutional Review Board (IRB) at NKI. Individuals provided demographic information and behavioral data. Behavioral data included participants filling out a survey on their last month of sleep (Pittsburgh Sleep Study), the amount of sleep they had the previous night, and their caffeine intake (if any) before the scan session. The primary goal of this study is to understand the neural underpinnings of brain function evaluating the correlation between electrical activity and hemodynamic fluctuations derived from neuroimaging data.
The uploaded dataset, organized according to Brain Imaging Data Structure (BIDS) format includes de-identified and de-faced brain images (MPRAGE, fMRI), EEG, eye-tracking, heart rate, respiration, and de-identified phenotypic data from the 22 subjects for whom explicit consent for open-science sharing of data was obtained. We provide raw and preprocessed data.
This dataset includes:
- EEG outside MRI scanner for
checkerboard task (sampling frequency 5000Hz, 200s)
- EEG inside MRI scanner for
checkerboard task (sampling frequency 5000Hz, 200s)
- Simultaneous EEG-fMRI for
checkerboard task (sampling frequency 5000Hz, 200s)
- Simultaneous EEG-fMRI during
resting state fMRI scan (TR=2.1s, 600s)
- Simultaneous EEG-fMRI video:
Inscapes (TR=2.1s, 600s)
- Simultaneous EEG-fMRI video:
“The Present” (TR=2.1s, 258s)
- Simultaneous EEG-fMRI video:
“Despicable Me (English)” (TR=2.1s, 600s)
- Simultaneous EEG-fMRI video:
“Despicable Me (Hungarian)” (TR=2.1s, 600s)
- Simultaneous EEG-fMRI video:
“Monkey1”, “Monkey2”, “Monkey5” (TR=2.1s,
300s)
- EyeLink 1000 Plus eye tracking data (sampling frequency 250Hz
or 1000Hz)
- BIOPAC MP150 respiratory data
(sampling frequency 62.5Hz)
- T1 anatomical scan (defaced)
Data Release Download
The data are available for download in an Amazon Web Services S3 bucket: s3://fcp-indi/data/Projects/NATVIEW_EEGFMRI/
Instructions on how to download individual files on the S3 bucket can be seen here.
A webpage with direct downloads per subject can be seen here.
Code
Code used for data collection and preprocessing are available in the project's github page.
Personnel
Project lead: Principal investigators: Core Research Team:- Qawi K Telesford, PhD
- Eduardo Gonzalez-Moreira, PhD
- Ting Xu, PhD
- Yiwen Tian
- Stanley Colcombe, PhD
- Jessica Cloud
- Brian Edward Russ, PhD
- Arnaud Falchier, PhD
- Maximilian Nentwich, PhD
- Jens Madsen, PhD
- Lucas Parra, PhD
- Charles Schroeder, PhD
- Michael Milham, MD, PhD
- Alexandre Rosa Franco, PhD
- Victor Pereira-Sanchez, MD, PhD
- Alexandre R. Franco, PhD
- Yiwen Tian
Data privacy
All imaging data in this release has been de-identified, removing any personal identifying information (as defined by the Health Insurance Portability and Accountability) from data files, including facial features. Data and code are shared under the CC BY 4.0 license.
Funding
BRAIN Initiative Grant, R24MH114806
National Institute of Mental Health Grant, P50MH109429
Publications
PREPRINT: Telesford QK, Gonzalez-Moreira E, Xu T, Tian Y, Colcombe S, Cloud J, Russ BE, Falchier A, Nentwich M, Madsen J, Parra L, Schroeder C, Milham M, Franco AR (2022). Naturalistic viewing: An open-access dataset using simultaneous EEG-fMRI. bioRxiv. doi: https://doi.org/10.1101/2022.11.23.517540