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

Time, Frequency & Time-Varying Causality Measures in Neuroscience