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Time, Frequency & Time-Varying Causality Measures in Neuroscience

Sezen Cekic,D. Grandjean,O. Renaud

Published 2017 in arXiv: Applications

ABSTRACT

This article proposes a systematic methodological review and objective criticism of existing methods enabling the derivation of time-varying Granger-causality statistics in neuroscience. The increasing interest and the huge number of publications related to this topic calls for this systematic review which describes the very complex methodological aspects. The capacity to describe the causal links between signals recorded at different brain locations during a neuroscience experiment is of primary interest for neuroscientists, who often have very precise prior hypotheses about the relationships between recorded brain signals that arise at a specific time and in a specific frequency band. The ability to compute a time-varying frequency-specific causality statistic is therefore essential. Two steps are necessary to achieve this: the first consists of finding a statistic that can be interpreted and that directly answers the question of interest. The second concerns the model that underlies the causality statistic and that has this time-frequency specific causality interpretation. In this article, we will review Granger-causality statistics with their spectral and time-varying extensions.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    arXiv: Applications

  • Publication date

    2017-04-11

  • Fields of study

    Mathematics, Psychology

  • Identifiers
    arXiv 1704.03177
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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