publication . Article . 2011

Effective connectivity: Influence, causality and biophysical modeling

Jean Daunizeau; Jean Daunizeau; Alard Roebroeck; Pedro A. Valdes-Sosa; Karl J. Friston;
Open Access
  • Published: 01 Sep 2011 Journal: NeuroImage, volume 58, issue 2, pages 339-361 (issn: 1053-8119, Copyright policy)
  • Publisher: Elsevier BV
  • Country: Netherlands
Abstract
AbstractThis is the final paper in a Comments and Controversies series dedicated to “The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution”. We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of B...
Subjects
free text keywords: Cognitive Neuroscience, Neurology, Comments and Controversies, Granger Causality, Effective connectivity, Dynamic Causal Modeling, EEG, fMRI, Bayesian probability, Prior probability, Machine learning, computer.software_genre, computer, Bayes' theorem, Model selection, Econometrics, Causality, Identifiability, Computer science, Causal model, Artificial intelligence, business.industry, business
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
Communities
Neuroinformatics
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