Article (Scientific journals)
Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes
Schrouff, Jessica; Kussé, Caroline; Wehenkel, Louis et al.
2012In PLoS ONE, 7 (4)
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Keywords :
machine learning; neuroimagery; fMRI
Abstract :
[en] Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. 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. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets.
Research center :
GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège
Disciplines :
Life sciences: Multidisciplinary, general & others
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Schrouff, Jessica ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Kussé, Caroline ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Maquet, Pierre  ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Phillips, Christophe  ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Language :
English
Title :
Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes
Publication date :
2012
Journal title :
PLoS ONE
eISSN :
1932-6203
Publisher :
Public Library of Science, San Franscisco, United States - California
Volume :
7
Issue :
4
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
FRIA - Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture [BE]
FMRE - Fondation Médicale Reine Elisabeth [BE]
Laboratórios Bial [PT]
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since 02 June 2012

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