Article (Scientific journals)
PRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica; Rosa, Maria Joao; Rondina, Jane et al.
2013In Neuroinformatics, 11 (3), p. 319-337
Peer Reviewed verified by ORBi
 

Files


Full Text
Schrouff_Rosa.pdf
Publisher postprint (1.1 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
machine learning; neuroimaging; toolbox; image analysis; multivariate pattern analysis
Abstract :
[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 effects compared to univariate techniques, they lack an established and accessible software framework. The goal of this work was to build a toolbox comprising all the necessary functionalities for multivariate analyses of neuroimaging data, based on machine learning models. The “Pattern Recognition for Neuroimaging Toolbox” (PRoNTo) is open-source, cross-platform, MATLAB-based and SPM compatible, therefore being suitable for both cognitive and clinical neuroscience research. In addition, it is designed to facilitate novel contributions from developers, aiming to improve the interaction between the neuroimaging and machine learning communities. Here, we introduce PRoNTo by presenting examples of possible research questions that can be addressed with the machine learning framework implemented in PRoNTo, and cannot be easily investigated with mass univariate statistical analysis.
Research center :
Computer Science Department, University College London
Institute of Psychology, King's College, London
Wellcome Trust, London
GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège
Ecole Polytechnique Fédérale de Lausanne
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Human health sciences: Multidisciplinary, general & others
Author, co-author :
Schrouff, Jessica ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Rosa, Maria Joao
Rondina, Jane
Marquand, Andre
Chu, Carlton
Ashburner, John
Phillips, Christophe  ;  Université de Liège - ULiège > GIGA > GIGA CRC In vivo Imaging - Neuroimaging, data acquisition and processing ; Université de Liège - ULiège > Centre de recherches du cyclotron
Richiardi, Jonas
Mourão-Miranda, Janaina
Language :
English
Title :
PRoNTo: Pattern Recognition for Neuroimaging Toolbox
Publication date :
February 2013
Journal title :
Neuroinformatics
ISSN :
1539-2791
eISSN :
1559-0089
Publisher :
Humana Press, United States
Volume :
11
Issue :
3
Pages :
319-337
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
PASCAL2 Harvest Project
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]
UCL - University College London [GB]
Wellcome Trust [GB]
FCT - Fundação para a Ciência e a Tecnologia [PT]
SNSF - Swiss National Science Foundation [CH]
Funding text :
Swiss National Science Foundation (PP00P2-123438) and Center for Biomedical Imaging (CIBM) of the EPFL and Universities and Hospitals of Lausanne and Geneva; The King’s College London Centre of Excellence in Medical Engineering, funded by the Wellcome Trust and EPSRC under grant no. WT088641/Z/09/Z
Available on ORBi :
since 22 January 2013

Statistics


Number of views
417 (59 by ULiège)
Number of downloads
317 (26 by ULiège)

Scopus citations®
 
320
Scopus citations®
without self-citations
280
OpenCitations
 
343

Bibliography


Similar publications



Contact ORBi