Analysing connectivity with Granger causality and dynamic causal modelling

Friston, Karl, Moran, Rosalyn and Seth, Anil K (2013) Analysing connectivity with Granger causality and dynamic causal modelling. Current Opinion in Neurobiology, 23 (2). pp. 172-178. ISSN 0959-4388

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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.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology Including cancer and carcinogens > RC0280 By region, system, or organ of the body, or type of tumor, A-Z > RC0280.B7 Brain
Depositing User: Marianne Cole
Date Deposited: 20 Aug 2015 12:28
Last Modified: 06 Mar 2017 06:47
URI: http://sro.sussex.ac.uk/id/eprint/56181

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