PMID- 26793434
OWN - NLM
STAT- MEDLINE
DCOM- 20161006
LR  - 20181113
IS  - 2213-1582 (Electronic)
IS  - 2213-1582 (Linking)
VI  - 10
DP  - 2016
TI  - Classification of autistic individuals and controls using cross-task 
      characterization of fMRI activity.
PG  - 78-88
LID - 10.1016/j.nicl.2015.11.010 [doi]
AB  - Multivariate pattern analysis (MVPA) has been applied successfully to task-based 
      and resting-based fMRI recordings to investigate which neural markers distinguish 
      individuals with autistic spectrum disorders (ASD) from controls. While most 
      studies have focused on brain connectivity during resting state episodes and 
      regions of interest approaches (ROI), a wealth of task-based fMRI datasets have 
      been acquired in these populations in the last decade. This calls for techniques 
      that can leverage information not only from a single dataset, but from several 
      existing datasets that might share some common features and biomarkers. We 
      propose a fully data-driven (voxel-based) approach that we apply to two different 
      fMRI experiments with social stimuli (faces and bodies). The method, based on 
      Support Vector Machines (SVMs) and Recursive Feature Elimination (RFE), is first 
      trained for each experiment independently and each output is then combined to 
      obtain a final classification output. Second, this RFE output is used to 
      determine which voxels are most often selected for classification to generate 
      maps of significant discriminative activity. Finally, to further explore the 
      clinical validity of the approach, we correlate phenotypic information with 
      obtained classifier scores. The results reveal good classification accuracy 
      (range between 69% and 92.3%). Moreover, we were able to identify discriminative 
      activity patterns pertaining to the social brain without relying on a priori ROI 
      definitions. Finally, social motivation was the only dimension which correlated 
      with classifier scores, suggesting that it is the main dimension captured by the 
      classifiers. Altogether, we believe that the present RFE method proves to be 
      efficient and may help identifying relevant biomarkers by taking advantage of 
      acquired task-based fMRI datasets in psychiatric populations.
FAU - Chanel, Guillaume
AU  - Chanel G
AD  - Swiss Center for Affective Sciences, Campus Biotech, University of Geneva, 
      Geneva, Switzerland; Computer Vision and Multimedia Laboratory, University of 
      Geneva, Geneva, Switzerland.
FAU - Pichon, Swann
AU  - Pichon S
AD  - Swiss Center for Affective Sciences, Campus Biotech, University of Geneva, 
      Geneva, Switzerland; Faculty of Psychology and Educational Sciences, University 
      of Geneva, Geneva, Switzerland.
FAU - Conty, Laurence
AU  - Conty L
AD  - Laboratoire de Psychopathologie et Neuropsychologie EA 2027, Universite Paris 8, 
      France.
FAU - Berthoz, Sylvie
AU  - Berthoz S
AD  - CESP, INSERM, Univ. Paris-Sud, Univ. Paris Descartes, UVSQ, Universite 
      Paris-Saclay, Paris, France; Departement de Psychiatrie de l'Institut Mutualiste 
      Montsouris, Paris, France.
FAU - Chevallier, Coralie
AU  - Chevallier C
AD  - Laboratoire de Neuroscience Cognitive, INSERM U960, Ecole Normale Superieure, 
      Paris, France.
FAU - Grezes, Julie
AU  - Grezes J
AD  - Laboratoire de Neuroscience Cognitive, INSERM U960, Ecole Normale Superieure, 
      Paris, France; Centre de Neuroimagerie de Recherche (CENIR), Centre de Recherche 
      de l'Institut du Cerveau et de la Moelle epiniere (CRICM), Universite Pierre et 
      Marie Curie-Paris 6 UMRS 975, Inserm U975, CNRS UMR 7225, Institut du cerveau et 
      de la moelle epiniere (ICM), Paris 75013, France.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20151117
PL  - Netherlands
TA  - Neuroimage Clin
JT  - NeuroImage. Clinical
JID - 101597070
SB  - IM
MH  - Adult
MH  - Anhedonia
MH  - Anxiety
MH  - Attention/physiology
MH  - Autism Spectrum Disorder/*classification/*physiopathology/psychology
MH  - Brain/*physiopathology
MH  - Brain Mapping/*methods
MH  - Facial Expression
MH  - Facial Recognition/physiology
MH  - Female
MH  - Humans
MH  - Magnetic Resonance Imaging/*methods
MH  - Male
MH  - Middle Aged
MH  - Social Perception
MH  - Support Vector Machine
MH  - Visual Perception/physiology
MH  - Young Adult
PMC - PMC4683429
OTO - NOTNLM
OT  - Anger
OT  - Autistic spectrum disorder
OT  - Body perception
OT  - Diagnosis
OT  - Emotion
OT  - Face perception
OT  - Pattern classification
OT  - Recursive Feature Elimination
OT  - SVM
OT  - fMRI
EDAT- 2016/01/23 06:00
MHDA- 2016/10/08 06:00
PMCR- 2015/11/17
CRDT- 2016/01/22 06:00
PHST- 2015/06/15 00:00 [received]
PHST- 2015/11/12 00:00 [revised]
PHST- 2015/11/14 00:00 [accepted]
PHST- 2016/01/22 06:00 [entrez]
PHST- 2016/01/23 06:00 [pubmed]
PHST- 2016/10/08 06:00 [medline]
PHST- 2015/11/17 00:00 [pmc-release]
AID - S2213-1582(15)30027-9 [pii]
AID - 10.1016/j.nicl.2015.11.010 [doi]
PST - epublish
SO  - Neuroimage Clin. 2015 Nov 17;10:78-88. doi: 10.1016/j.nicl.2015.11.010. 
      eCollection 2016.