Reference : Decoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain r...
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/131334
Decoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain reactivation
English
Schrouff, Jessica mailto [Université de Liège - ULg > > Centre de recherches du cyclotron >]
Kussé, Caroline [Université de Liège - ULg > > Centre de recherches du cyclotron >]
Wehenkel, Louis [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Maquet, Pierre [Université de Liège - ULg > > Centre de recherches du cyclotron >]
Phillips, Christophe [Université de Liège - ULg > > Centre de recherches du cyclotron >]
3-Jul-2012
2012 Second International Workshop on Pattern Recognition in NeuroImaging (PRNI 2012): proceedings
IEEE Computer Society Conference Publishing Services
Yes
International
Los Alamitos
Ca
2nd International Workshop on Pattern Recognition in NeuroImaging (PRNI 2012)
from 02-07-2012 to 04-07-2012
London
United Kingdom
[en] brain decoding ; fMRI ; spontaneous activity ; memory consolidation
[en] While Multi-Variate Pattern Analysis techniques based on machine learning have now been regularly applied to neuroimaging data, decoding brain activity is usually performed in highly controlled experimental paradigms. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. Moreover, in the case of spontaneous brain activity, the mental states can not be linked to any external or internal stimulation, which makes it a highly difficult condition to decode. This study tests the classification of brain activity, acquired on 14 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. Application of the obtained model on rest sessions allowed classifying spontaneous brain activity linked to the task which, overall, correlated with their behavioural performance to the task.
Centre de Recherches du Cyclotron - CRC
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS ; Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA ; BIAL foundation ; PAI/IAP Interuniversity Pole of Attraction ; Research Fund of the ULg ; Fondation Reine Elisabeth
http://hdl.handle.net/2268/131334
http://www.mlnl.cs.ucl.ac.uk/prni2012/index.html

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