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

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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.

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Acknowledgment

This research was supported by Grant-in-Aid for Scientific Research (KAKENHI) number 18300179, Ministry of Education, Culture, Sports, Science and Technology.

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Authors and Affiliations

  1. National Institute of Advanced Industrial Science and Technology (AIST), Grid Technology Research Center, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba City, Ibaraki, 305-8568, Japan

    Epifanio Bagarinao & Yoshio Tanaka

  2. Functional Brain Imaging Laboratory, Department of Gerontechnology, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8522, Japan

    Kayako Matsuo & Toshiharu Nakai

Authors
  1. Epifanio Bagarinao
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  2. Kayako Matsuo
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  3. Toshiharu Nakai
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  4. Yoshio Tanaka
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Correspondence to Epifanio Bagarinao.

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Bagarinao, E., Matsuo, K., Nakai, T. et al. BAX: A Toolbox for the Dynamic Analysis of Functional MRI Datasets. Neuroinform 6, 109–115 (2008). https://doi.org/10.1007/s12021-008-9017-y

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  • DOI: https://doi.org/10.1007/s12021-008-9017-y

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