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Encyclopedia of Computational Neuroscience pp 1–3Cite as

Statistical Analysis of Neuroimaging Data

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Definition

The main goal of “statistical analysis of neuroimaging data” is to use statistical methods to extract useful neuroscientific information, from neuroimaging data such as fMRI, EEG, and MEG, which are derived from measurement of the dynamics of electrical and magnetic activity generated from the neural and vascular activities inside the live brain.

Detailed Description

A typical example is the statistical analysis of fMRI data, where the activation and deactivation of voxels (as measured by the BOLD signal) in response to some specific task of interest may be elucidated in a map called the activation map. Similarly for EEG/MEG data analysis, one of the main interests of statistical analysis is to estimate the activation of areas in response to specific stimuli to the live brain. It provides the basis for further elaborate statistical analysis, such as the analysis of dynamic causalities between the activated voxels in the estimated activation map.

“The statistical methods used...

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References

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Author information

Authors and Affiliations

  1. Institute of Statistical Mathematics, Tokyo, 106-8569, Japan

    Prof. Tohru Ozaki

Authors
  1. Prof. Tohru Ozaki
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Corresponding author

Correspondence to Tohru Ozaki .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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Ozaki, T. (2014). Statistical Analysis of Neuroimaging Data. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_539-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_539-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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