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BAX: A Toolbox for the Dynamic Analysis of Functional MRI Datasets

BAX: A Toolbox for the Dynamic Analysis of Functional MRI Datasets We developed a toolbox called BAX (brain activation explorer) for the dynamic analysis of functional magnetic resonance imaging (fMRI) datasets using the general linear model. The toolbox provides a graphical user interface where several routines can be accessed to extract different sets of information from a given series of functional images. The dynamic analysis can be implemented using either an incremental approach or a sliding window approach. In particular, BAX can be used to construct dynamic activation maps that can be used to assess the contribution of newly added volumes in the final activation map, detect problematic segments in the dataset, or localize in time dynamic changes in brain activity. Consistency maps, which graphically represent the number of times voxels are consecutively detected as active in a given analysis, can also be constructed using either incremental or sliding window analysis. BAX runs under Matlab (MathWorks, Inc.) and requires some routines from SPM2 (Wellcome Department of Cognitive Neurology, London, UK) for its operation. It can be freely downloaded at http://www.medgrid.org/ website. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neuroinformatics Springer Journals

BAX: A Toolbox for the Dynamic Analysis of Functional MRI Datasets

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References (11)

Publisher
Springer Journals
Copyright
Copyright © 2008 by Humana Press
Subject
Biomedicine; Computational Biology/Bioinformatics; Biotechnology; Neurology ; Computer Appl. in Life Sciences ; Neurosciences
ISSN
1539-2791
eISSN
1559-0089
DOI
10.1007/s12021-008-9017-y
pmid
18465269
Publisher site
See Article on Publisher Site

Abstract

We developed a toolbox called BAX (brain activation explorer) for the dynamic analysis of functional magnetic resonance imaging (fMRI) datasets using the general linear model. The toolbox provides a graphical user interface where several routines can be accessed to extract different sets of information from a given series of functional images. The dynamic analysis can be implemented using either an incremental approach or a sliding window approach. In particular, BAX can be used to construct dynamic activation maps that can be used to assess the contribution of newly added volumes in the final activation map, detect problematic segments in the dataset, or localize in time dynamic changes in brain activity. Consistency maps, which graphically represent the number of times voxels are consecutively detected as active in a given analysis, can also be constructed using either incremental or sliding window analysis. BAX runs under Matlab (MathWorks, Inc.) and requires some routines from SPM2 (Wellcome Department of Cognitive Neurology, London, UK) for its operation. It can be freely downloaded at http://www.medgrid.org/ website.

Journal

NeuroinformaticsSpringer Journals

Published: May 9, 2008

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