Analysing connectivity with Granger causality and dynamic causal modelling

Karl Friston, Rosalyn Moran, Anil K Seth

Research output: Contribution to journalArticle (Academic Journal)peer-review

313 Citations (Scopus)

Abstract

This review considers state-of-the-art analyses of functional integration in neuronal macrocircuits. We focus on detecting and estimating directed connectivity in neuronal networks using Granger causality (GC) and dynamic causal modelling (DCM). These approaches are considered in the context of functional segregation and integration and--within functional integration--the distinction between functional and effective connectivity. We review recent developments that have enjoyed a rapid uptake in the discovery and quantification of functional brain architectures. GC and DCM have distinct and complementary ambitions that are usefully considered in relation to the detection of functional connectivity and the identification of models of effective connectivity. We highlight the basic ideas upon which they are grounded, provide a comparative evaluation and point to some outstanding issues.

Original languageEnglish
Pages (from-to)172-8
Number of pages7
JournalCurrent Opinion in Neurobiology
Volume23
Issue number2
DOIs
Publication statusPublished - Apr 2013

Keywords

  • Brain
  • Brain Mapping
  • Causality
  • Computer Simulation
  • Humans
  • Models, Neurological
  • Nerve Net
  • Neurons
  • Nonlinear Dynamics

Fingerprint Dive into the research topics of 'Analysing connectivity with Granger causality and dynamic causal modelling'. Together they form a unique fingerprint.

Cite this