Literature DB >> 29883736

Solved problems for Granger causality in neuroscience: A response to Stokes and Purdon.

Lionel Barnett1, Adam B Barrett1, Anil K Seth2.   

Abstract

Granger-Geweke causality (GGC) is a powerful and popular method for identifying directed functional ('causal') connectivity in neuroscience. In a recent paper, Stokes and Purdon (2017b) raise several concerns about its use. They make two primary claims: (1) that GGC estimates may be severely biased or of high variance, and (2) that GGC fails to reveal the full structural/causal mechanisms of a system. However, these claims rest, respectively, on an incomplete evaluation of the literature, and a misconception about what GGC can be said to measure. Here we explain how existing approaches resolve the first issue, and discuss the frequently-misunderstood distinction between functional and effective neural connectivity which underlies Stokes and Purdon's second claim.
Copyright © 2018 Elsevier Inc. All rights reserved.

Keywords:  Effective connectivity; Functional connectivity; Granger causality; Statistical inference

Mesh:

Year:  2018        PMID: 29883736     DOI: 10.1016/j.neuroimage.2018.05.067

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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