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High-Dimensional Classification for Brain Decoding

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Big and Complex Data Analysis

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

Brain decoding involves the determination of a subject’s cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a finite set, and the neuroimaging data comprise voluminous amounts of spatiotemporal data measuring some aspect of the neural signal. The associated statistical problem is one of the classifications from high-dimensional data. We explore the use of functional principal component analysis, mutual information networks, and persistent homology for examining the data through exploratory analysis and for constructing features characterizing the neural signal for brain decoding. We review each approach from this perspective, and we incorporate the features into a classifier based on symmetric multinomial logistic regression with elastic net regularization. The approaches are illustrated in an application where the task is to infer, from brain activity measured with magnetoencephalography (MEG), the type of video stimulus shown to a subject.

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Acknowledgements

This article is based on work from Nicole Croteau’s MSc thesis. F.S. Nathoo is supported by an NSERC discovery grant and holds a Tier II Canada Research Chair in Biostatistics for Spatial and High-Dimensional Data. The authors thank Rachel Levanger for useful discussions on the implementation of persistent homology for space-time data.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada

    Nicole Croteau, Farouk S. Nathoo, Jiguo Cao & Ryan Budney

Authors
  1. Nicole Croteau
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  2. Farouk S. Nathoo
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  3. Jiguo Cao
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  4. Ryan Budney
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Corresponding author

Correspondence to Farouk S. Nathoo .

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Editors and Affiliations

  1. Department of Mathematics & Statistics, Brock University, St. Catherines, Ontario, Canada

    S. Ejaz Ahmed

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Croteau, N., Nathoo, F.S., Cao, J., Budney, R. (2017). High-Dimensional Classification for Brain Decoding. In: Ahmed, S. (eds) Big and Complex Data Analysis. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-41573-4_15

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