{"title":"Pop or not? EEG correlates of risk-taking behavior in the balloon analogue risk task","authors":"Yiyu Chen, C. Wallraven","doi":"10.1109/IWW-BCI.2017.7858146","DOIUrl":null,"url":null,"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. Specifically, we examine the feedback-related negativity components (FRN) in the EEG spectrum and ERP components as potential candidates for such a distinction. Using a sample of 17 participants, we find a reliable, larger FRN for risk avoiders as well 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.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2017.7858146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
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. Specifically, we examine the feedback-related negativity components (FRN) in the EEG spectrum and ERP components as potential candidates for such a distinction. Using a sample of 17 participants, we find a reliable, larger FRN for risk avoiders as well 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.