000145945 001__ 145945
000145945 005__ 20190316234718.0
000145945 0247_ $$2doi$$a10.1109/TNSRE.2008.926712
000145945 022__ $$a1534-4320
000145945 02470 $$2ISI$$a000262557000005
000145945 037__ $$aARTICLE
000145945 245__ $$aCharacterizing the EEG Correlates of Exploratory Behavior
000145945 269__ $$a2008
000145945 260__ $$bInstitute of Electrical and Electronics Engineers$$c2008
000145945 336__ $$aJournal Articles
000145945 500__ $$aIDIAP-RR 08-28
000145945 520__ $$aThis study aims to characterize the EEG correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using fMRI. Based on a usual paradigm in reinforcement learning, this study has shown bilateral activation in the frontal and parietal cortex. To our knowledge, no previous study has been done on it using EEG. The study of the exploratory behavior using EEG signals raises two difficulties. First, the labels of trial as exploitation or exploration cannot be directly derived from the subject action. In order to access this information, a model of how the subject makes his decision must be built. The exploration related information can be then derived from it. Second, because of the complexity of the task, its EEG correlates are not necessarily time locked with the action. So the EEG processing methods used should be designed in order to handle signals that shift in time across trials. Using the same experimental protocol as the fMRI study, results show that the bilateral frontal and parietal areas are also the most discriminant. This strongly suggests that the EEG signal also conveys information about the exploratory behavior.
000145945 6531_ $$aDecision making
000145945 6531_ $$aelectroencephalography (EEG)
000145945 6531_ $$aexploratory behavior
000145945 6531_ $$areinforcement learning
000145945 6531_ $$a[BACS]
000145945 700__ $$0242174$$g174078$$aBourdaud, Nicolas
000145945 700__ $$0241256$$g137762$$aChavarriaga, Ricardo
000145945 700__ $$aGalán, Ferran
000145945 700__ $$aMillán, José del R.$$g149175$$0240030
000145945 773__ $$j16$$tIEEE Transactions on Neural Systems and Rehabilitation Engineering$$k6$$q549-556
000145945 8564_ $$uhttp://publications.idiap.ch/index.php/publications/showcite/bourdaud:rr08-28$$zURL
000145945 8564_ $$uhttps://infoscience.epfl.ch/record/145945/files/bourdaud-ieee-tnsre-2008.pdf$$zn/a$$s3331844$$yn/a
000145945 909C0 $$xU10381$$0252189$$pLIDIAP
000145945 909C0 $$pCNBI$$xU12103$$0252018
000145945 909C0 $$xU12599$$0252517$$pCNP
000145945 909CO $$qGLOBAL_SET$$pSTI$$particle$$ooai:infoscience.tind.io:145945
000145945 917Z8 $$x155154
000145945 917Z8 $$x176513
000145945 917Z8 $$x174078
000145945 917Z8 $$x149175
000145945 937__ $$aCNBI-ARTICLE-2009-001
000145945 937__ $$aLIDIAP-ARTICLE-2008-002
000145945 970__ $$abourdaud:ieee-tnsre:2008/LIDIAP
000145945 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000145945 980__ $$aARTICLE