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Neural Networks for fMRI Spatio-temporal Analysis

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Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

Most of the analysis techniques applied to functional magnetic resonance imaging (fMRI) consider only the temporal information of the data. In this paper, a new method combining temporal and spatial information is proposed for the fMRI data analysis. The nonlinear autoregressive with exogenous inputs (NARX) model realized by radial basis function (RBF) neural network is used to model the fMRI data. This new approach models the fMRI waveform in each voxel as a regression model that combines the time series of neighboring voxels together with its own. Both simulated as well as real fMRI data were tested using the proposed algorithm. Results show that this new approach can model the fMRI data very well and as a result, can detect the activated areas of human brain successfully and accurately.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117576

    Luo Huaien & Sadasivan Puthusserypady

Authors
  1. Luo Huaien
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  2. Sadasivan Puthusserypady
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

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© 2004 Springer-Verlag Berlin Heidelberg

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Huaien, L., Puthusserypady, S. (2004). Neural Networks for fMRI Spatio-temporal Analysis. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_201

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_201

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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