Abstract
Peoples' risk-Taking behavior varies from timid and careful, low-risk individuals to bold and careless, high-risk individuals. Can we use EEG to predict who is who? In the present study, we use the balloon analogue risk task (BART) in an EEG experiment in order to find out potential correlates in the EEG signal that allow us to distinguish high risk-Takers from low risk-Takers. SpecificaIly, we examine the feedback-related negativity components (FRN) in the EEG spectrum and ERP components as potential candidates for such a distinction. Using a sampie of 17 participants, we find a reliable, larger FRN for risk avoiders as weIl as increased delta and theta power in several central electrode sites. These results represent the first step towards robust bio-markers of risk-Taking behavior.
Original language | English |
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Title of host publication | 5th International Winter Conference on Brain-Computer Interface, BCI 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 16-19 |
Number of pages | 4 |
ISBN (Electronic) | 9781509050963 |
DOIs | |
Publication status | Published - 2017 Feb 16 |
Event | 5th International Winter Conference on Brain-Computer Interface, BCI 2017 - Gangwon Province, Korea, Republic of Duration: 2017 Jan 9 → 2017 Jan 11 |
Publication series
Name | 5th International Winter Conference on Brain-Computer Interface, BCI 2017 |
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Other
Other | 5th International Winter Conference on Brain-Computer Interface, BCI 2017 |
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Country/Territory | Korea, Republic of |
City | Gangwon Province |
Period | 17/1/9 → 17/1/11 |
Bibliographical note
Funding Information:This research was supported by the Basic Science Research Program through the National Research Foundation 01' Korea (NRF) 1'unded by the Ministry 01' Science, leT & Future planning (NRF-2013R I A I A I O I I , NRF-2015S I A5A8018) and the Brain Korea 21 plus program through the National Research Foundation 01' Korea (NRF) 1'unded by the Ministry 01' Education.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
ASJC Scopus subject areas
- Signal Processing
- Human-Computer Interaction