Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 신재영 | - |
dc.date.accessioned | 2019-12-05T07:25:29Z | - |
dc.date.available | 2019-12-05T07:25:29Z | - |
dc.date.issued | 2018-02 | - |
dc.identifier.citation | SCIENTIFIC DATA, v. 5, Article no. 180003 | en_US |
dc.identifier.issn | 2052-4463 | - |
dc.identifier.uri | https://www.nature.com/articles/sdata20183 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/117504 | - |
dc.description.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. | en_US |
dc.description.sponsorship | This research was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2015R1C1A1A02037032), by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00451), by the Brain Korea 21 PLUS Program through the NRF funded by the Ministry of Science, ICT & Future Planning, and by the BIMoS graduate school of Berlin Institute of Technology. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | NATURE PUBLISHING GROUP | en_US |
dc.subject | BRAIN-COMPUTER INTERFACES | en_US |
dc.subject | BCI | en_US |
dc.subject | COMMUNICATION | en_US |
dc.subject | COMPETITION | en_US |
dc.subject | OPERATE | en_US |
dc.subject | IMAGERY | en_US |
dc.title | Data Descriptor: Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset | en_US |
dc.type | Article | en_US |
dc.relation.volume | 5 | - |
dc.relation.page | 180003-180003 | - |
dc.relation.journal | SCIENTIFIC DATA | - |
dc.contributor.googleauthor | Shin, Jaeyoung | - |
dc.contributor.googleauthor | von Luehmann, Alexander | - |
dc.contributor.googleauthor | Kim, Do-Won | - |
dc.contributor.googleauthor | Mehnert, Jan | - |
dc.contributor.googleauthor | Hwang, Han-Jeong | - |
dc.contributor.googleauthor | Mueller, Klaus-Robert | - |
dc.relation.code | 2018003986 | - |
dc.sector.campus | S | - |
dc.sector.daehak | RESEARCH INSTITUTE[S] | - |
dc.sector.department | INSTITUTE OF BIOMEDICAL ENGINEERING | - |
dc.identifier.pid | naraeshigo | - |
dc.identifier.researcherID | T-5173-2018 | - |
dc.identifier.orcid | http://orcid.org/0000-0003-2899-6893 | - |
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