Classification and Statistical Analysis of Auditory FMRI Data Using Linear Discriminative Analysis and Quadratic Discriminative Analysis
Pritesh G. Shah , Bharti W. Gawali
Abstract
Functional magnetic resonance imaging (fMRI) has the ability to not only get insight into how human brain functions but also to study the human brain of normal and diseased subjects. One of the methods to analyze the fMRI data is univariate approach, another approach is Multivariate discriminative approach. However for classification, there exists number of statistical techniques. In this paper, we perform classification of fMRI data using Fishers Linear Discriminative Analysis (LDA). The re-substitution error for the LDA calculated to be 0.1875. It is concluded that, the data are consistent with the multivariate normal distribution.
Keywords
Functional magnetic resonance imaging (fMRI), Linear Discriminative Analysis (LDA), Quadratic Discriminative Analysis (QDA), Statistical Parametric Mapping (SPM)
References
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[3] Functional Imaging Biomedical Informatics Research Network (FBIRN): http://fbirnbdr.nbirn.net:8080/BDR/
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[5] S. Strother et al, “The quantitative evaluation of functional neuroimaging experiments: The NPAIRS data analysis framework”, NeuroImage, 15(4):747-771, 2002.
Cites this article as
P. G. Shah, B. W. Gawali,
"Classification and Statistical Analysis of Auditory FMRI Data Using Linear Discriminative Analysis and Quadratic Discriminative Analysis", International Journal of Innovative Research in Engineering & Management (ijircst), Vol-2, Issue-6, Page No-56-61, 2014. Available from:
Corresponding Author
Pritesh G. Shah
Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
