Abstract
We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.
| Original language | English |
|---|---|
| Article number | 180003 |
| Journal | Scientific data |
| Volume | 5 |
| DOIs | |
| Publication status | Published - 2018 Feb 13 |
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ASJC Scopus subject areas
- Statistics and Probability
- Information Systems
- Education
- Computer Science Applications
- Statistics, Probability and Uncertainty
- Library and Information Sciences
Cite this
Data descriptor : Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset. / Shin, Jaeyoung; Von Lühmann, Alexander; Kim, Do Won; Mehnert, Jan; Hwang, Han Jeong; Muller, Klaus.
In: Scientific data, Vol. 5, 180003, 13.02.2018.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Data descriptor
T2 - Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset
AU - Shin, Jaeyoung
AU - Von Lühmann, Alexander
AU - Kim, Do Won
AU - Mehnert, Jan
AU - Hwang, Han Jeong
AU - Muller, Klaus
PY - 2018/2/13
Y1 - 2018/2/13
N2 - We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.
AB - We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.
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UR - http://www.scopus.com/inward/citedby.url?scp=85042032692&partnerID=8YFLogxK
U2 - 10.1038/sdata.2018.3
DO - 10.1038/sdata.2018.3
M3 - Article
C2 - 29437166
AN - SCOPUS:85042032692
VL - 5
JO - Scientific data
JF - Scientific data
SN - 2052-4463
M1 - 180003
ER -