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Multivoxel Pattern Analysis for fMRI Data : A Review
Joint Authors
Mahmoudi, Abdelhak
Brovelli, Andrea
Boussaoud, Driss
Takerkart, Sylvain
Regragui, Fakhita
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-06
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions.
The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model.
One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination.
Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks.
MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions.
In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs).
In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves.
American Psychological Association (APA)
Mahmoudi, Abdelhak& Takerkart, Sylvain& Regragui, Fakhita& Boussaoud, Driss& Brovelli, Andrea. 2012. Multivoxel Pattern Analysis for fMRI Data : A Review. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-511659
Modern Language Association (MLA)
Mahmoudi, Abdelhak…[et al.]. Multivoxel Pattern Analysis for fMRI Data : A Review. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-511659
American Medical Association (AMA)
Mahmoudi, Abdelhak& Takerkart, Sylvain& Regragui, Fakhita& Boussaoud, Driss& Brovelli, Andrea. Multivoxel Pattern Analysis for fMRI Data : A Review. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-511659
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-511659