2013 • In Suykens, J.A.K.; Argyriou, A.; De Brabanter, K.et al. (Eds.) International workshop on advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013), Book of Abstracts
[en] In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed e ffects compared to univariate techniques, they lack an established and accessible software framework. Here we introduce the \Pattern Recognition for Neuroimaging Toolbox" (PRoNTo), an open-source, cross-platform and MATLAB-based software comprising many necessary functionalities for machine learning modelling of neuroimaging data.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Schrouff, Jessica ; Université de Liège - ULiège > Centre de recherches du cyclotron
Rosa, Maria; University College London - UCL
Rondina, Jane; King's College London
Chu, Carlton; NIMH-NIH
Marquand, Andre; King's College London
Ashburner, John; University College London - UCL
Richiardi, Jonas; Stanford University
Phillips, Christophe ; Université de Liège - ULiège > Centre de recherches du cyclotron
Mourão-Miranda, Janaina; University College London - UCL
Language :
English
Title :
Pattern Recognition for Neuroimaging Toolbox
Publication date :
2013
Event name :
International workshop on advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013)
Event place :
Leuven, Belgium
Event date :
8-10/07/2013
Audience :
International
Main work title :
International workshop on advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013), Book of Abstracts
