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Accepted (AM)Open Access (License Unspecified), Open
Journal article
A Bayesian probit model with spatially varying coefficients for brain decoding using fMRI data
Statistics in medicine, v 35(24), pp 4380-4397
01 Oct 2016
PMID: 27222305
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recent advances in human neuroimaging have shown that it is possible to accurately decode how the brain perceives information based only on non-invasive functional magnetic resonance imaging measurements of brain activity. Two commonly used statistical approaches, namely, univariate analysis and multivariate pattern analysis often lead to distinct patterns of selected voxels. One current debate in brain decoding concerns whether the brain's representation of sound categories is localized or distributed. We hypothesize that the distributed pattern of voxels selected by most multivariate pattern analysis models can be an artifact due to the spatial correlation among voxels. Here, we propose a Bayesian spatially varying coefficient model, where the spatial correlation is modeled through the variance-covariance matrix of the model coefficients. Combined with a proposed region selection strategy, we demonstrate that our approach is effective in identifying the truly localized patterns of the voxels while maintaining robustness to discover truly distributed pattern. In addition, we show that localized or clustered patterns can be artificially identified as distributed if without proper usage of the spatial correlation information in fMRI data. Copyright (c) 2016 John Wiley & Sons, Ltd.
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Details
- Title
- A Bayesian probit model with spatially varying coefficients for brain decoding using fMRI data
- Creators
- Fengqing Zhang - Northwestern UniversityWenxin Jiang - Northwestern UniversityPatrick Wong - Chinese Univ Hong Kong, Dept Linguist & Modern Languages, Shatin, Hong Kong, Peoples R ChinaJi-Ping Wang - Northwestern University
- Publication Details
- Statistics in medicine, v 35(24), pp 4380-4397
- Publisher
- Wiley
- Number of pages
- 18
- Grant note
- 477513; 14117514 / Research Grants Council of Hong Kong; Hong Kong Research Grants Council 01120616 / Health and Medical Research Fund of Hong Kong Liu Che Woo Institute of Innovative Medicine at The Chinese University of Hong Kong Global Parent Child Resource Centre Limited School of Professional Studies R01DC013315 / US National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Northwestern University Information Technology R01DC013315 / NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Deafness & Other Communication Disorders (NIDCD) Office of the President, Weinberg College of Arts and Sciences, Kellogg School of Management
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000385490200007
- Scopus ID
- 2-s2.0-84971310975
- Other Identifier
- 991019169903204721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Mathematical & Computational Biology
- Medical Informatics
- Medicine, Research & Experimental
- Public, Environmental & Occupational Health
- Statistics & Probability