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Investigating the Functional Role of Callosal Connections with Dynamic Causal Models
Author(s) -
STEPHAN KLAAS E.,
PENNY WILL D.,
MARSHALL JOHN C.,
FINK GEREON R.,
FRISTON KARL J.
Publication year - 2005
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1340.008
Subject(s) - corpus callosum , neuroscience , neuroimaging , context (archaeology) , diffusion mri , computer science , contrast (vision) , psychology , cognitive science , artificial intelligence , biology , magnetic resonance imaging , medicine , paleontology , radiology
The anatomy of the corpus callosum has been described in considerable detail. Tracing studies in animals and human postmortem experiments are currently complemented by diffusion‐weighted imaging, which enables noninvasive investigations of callosal connectivity to be conducted. In contrast to the wealth of anatomical data, little is known about the principles by which interhemispheric integration is mediated by callosal connections. Most importantly, we lack insights into the mechanisms that determine the functional role of callosal connections in a context‐dependent fashion. These mechanisms can now be disclosed by models of effective connectivity that explain neuroimaging data from paradigms that manipulate interhemispheric interactions. In this article, we demonstrate that dynamic causal modeling (DCM), in conjunction with Bayesian model selection (BMS), is a powerful approach to disentangling the various factors that determine the functional role of callosal connections. We first review the theoretical foundations of DCM and BMS before demonstrating the application of these techniques to empirical data from a single subject.