Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data

PloS One
Sutao SongLi Yao

Abstract

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart...Continue Reading

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Citations

Oct 31, 2013·Computational and Mathematical Methods in Medicine·Lijun WangBin Yan
Jun 14, 2013·Computational and Mathematical Methods in Medicine·Yu LeiBin Yan
Apr 12, 2015·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Eugene BelilovskyMatthew B Blaschko
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Oct 13, 2011·NeuroImage·Teresa WuAlexandra Badea
Nov 23, 2016·International Journal of Neural Systems·Bruno DireitoAntónio Dourado
Mar 28, 2017·Human Brain Mapping·Yin LiangBin Wang
Jun 1, 2018·Computational Intelligence and Neuroscience·Jing ZhangZhiying Long
Feb 14, 2021·Computer Methods and Programs in Biomedicine·Zahraa A Al-Saffar, Tülay Yildirim
Mar 20, 2020·Computational Statistics & Data Analysis·A Skripnikov, G Michailidis
Sep 4, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Wei HuangHuafu Chen

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Methods Mentioned

BETA
PCA
MDS

Software Mentioned

libsvm
Matlab
SPM2
Matlab Toolbox for
Windows XP
SVM

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