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Inferring Effective Connectivity from fMRI Data

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fMRI: From Nuclear Spins to Brain Functions

Part of the book series: Biological Magnetic Resonance ((BIMR,volume 30))

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Abstract

A formal understanding of processes that result from the interaction of multiple elements is hardly possible without mathematical models of system dynamics. This is important in neuroscience, particularly in neuroimaging, where inference on causal mechanisms in neural systems, for example, effective connectivity, requires a model-based approach. Here, we focus on a Bayesian framework for inferring effective connectivity from functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM). DCM is a generative model of fMRI data which links hidden neural activity via a biophysical forward model to measured data. Bayesian inversion provides both the parameter distributions of the model parameters and (an approximation to) the model evidence; the latter provides a principled basis for model selection. Following a methodological discussion of DCM, we conclude with an outline of its potential use for clinical applications.

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Authors and Affiliations

  1. Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & Swiss Federal Institute of Technology (ETH Zurich), Wilfriedstr. 6, 8032, Zurich, Switzerland

    Klaas E. Stephan & Sandra Iglesias

  2. Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK

    Klaas E. Stephan, Baojuan Li & Karl J. Friston

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  1. Klaas E. Stephan
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  2. Baojuan Li
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  3. Sandra Iglesias
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  4. Karl J. Friston
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Correspondence to Klaas E. Stephan .

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Editors and Affiliations

  1. Maastricht Brain Imaging Centre, Maastricht University, Maastricht, The Netherlands

    Kamil Uludag

  2. University of Minnesota Medical School, Minneapolis, Minnesota, USA

    Kamil Ugurbil

  3. Department of Chemistry and Biochemistry, University of Denver, Denver, Colorado, USA

    Lawrence Berliner

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Stephan, K., Li, B., Iglesias, S., Friston, K. (2015). Inferring Effective Connectivity from fMRI Data. In: Uludag, K., Ugurbil, K., Berliner, L. (eds) fMRI: From Nuclear Spins to Brain Functions. Biological Magnetic Resonance, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7591-1_13

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