A study of problems encountered in Granger causality analysis from a neuroscience perspective

DOI Web Site Web Site 5 Citations
  • Patrick A. Stokes
    Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139;
  • Patrick L. Purdon
    Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02144

Search this article

Description

<jats:title>Significance</jats:title> <jats:p>Granger causality analysis is a statistical method for investigating the flow of information between time series. Granger causality has become more widely applied in neuroscience, due to its ability to characterize oscillatory and multivariate data. However, there are ongoing concerns regarding its applicability in neuroscience. When are these methods appropriate? How reliably do they recover the functional structure of the system? Also, what do they tell us about oscillations in neural systems? In this paper, we analyze fundamental properties of Granger causality and illustrate statistical and conceptual problems that make Granger causality difficult to apply and interpret in neuroscience studies. This work provides important conceptual clarification of Granger causality methods and suggests ways to improve analyses of neuroscience data in the future.</jats:p>

Journal

Citations (5)*help

See more

Report a problem

Back to top