Investigating the functional role of callosal connections with dynamic causal models

Klaas E Stephan, Will D. Penny, John C Marshall, Gereon R Fink, Karl J Friston

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)16-36
Number of pages21
JournalAnnals of the New York Academy of Sciences
Volume1064
DOIs
Publication statusPublished - Dec 2005

Keywords

  • Algorithms
  • Bayes Theorem
  • Brain Mapping
  • Cerebral Cortex
  • Computer Simulation
  • Corpus Callosum
  • Diffusion Magnetic Resonance Imaging
  • Functional Laterality
  • Humans
  • Magnetic Resonance Imaging
  • Neurological Models
  • Verbal Behavior
  • Visual Pathways
  • Visual Perception

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