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Exploiting Complexity Information for Brain Activation Detection

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  • Yan Zhang
  • Jiali Liang
  • Qiang Lin
  • Zhenghui Hu

Abstract

We present a complexity-based approach for the analysis of fMRI time series, in which sample entropy (SampEn) is introduced as a quantification of the voxel complexity. Under this hypothesis the voxel complexity could be modulated in pertinent cognitive tasks, and it changes through experimental paradigms. We calculate the complexity of sequential fMRI data for each voxel in two distinct experimental paradigms and use a nonparametric statistical strategy, the Wilcoxon signed rank test, to evaluate the difference in complexity between them. The results are compared with the well known general linear model based Statistical Parametric Mapping package (SPM12), where a decided difference has been observed. This is because SampEn method detects brain complexity changes in two experiments of different conditions and the data-driven method SampEn evaluates just the complexity of specific sequential fMRI data. Also, the larger and smaller SampEn values correspond to different meanings, and the neutral-blank design produces higher predictability than threat-neutral. Complexity information can be considered as a complementary method to the existing fMRI analysis strategies, and it may help improving the understanding of human brain functions from a different perspective.

Suggested Citation

  • Yan Zhang & Jiali Liang & Qiang Lin & Zhenghui Hu, 2016. "Exploiting Complexity Information for Brain Activation Detection," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-9, April.
    • Handle: RePEc:plo:pone00:0152418
    DOI: 10.1371/journal.pone.0152418
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    References listed on IDEAS

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    1. Singer, Wolf, 2009. "The Brain, a Complex Self-organizing System," European Review, Cambridge University Press, vol. 17(2), pages 321-329, May.
    2. Ze Wang & Yin Li & Anna Rose Childress & John A Detre, 2014. "Brain Entropy Mapping Using fMRI," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-8, March.
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