Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Dynamic Causal Modelling with Neural Population Models

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_57

Definition

Dynamic causal models with neural populations are state-space models that impose a specified dynamical systems form to the generation of neuroimaging and electrophysiological data. The forms of these models constitute neurobiologically motivated and identifiable parameterizations, where empirical observations offer conditional descriptions of parameter space following application of a Bayesian inversion scheme. They comprise separate generative processes at the neuronal level and at the observation level through a set of deterministic or stochastic differential equations and an observer functional, respectively.

Detailed Description

Dynamic causal models were first invented in 2003 for the purpose of estimating human brain connectivity and task-dependent functional integration using functional magnetic resonance imaging (fMRI) (Friston et al. 2003). The framework was extended for electrophysiological domains including noninvasive electroencephalography (EEG) and...

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Virginia Tech Carilion Research InstituteRoanokeUSA