Conductance-based dynamic causal modeling: A mathematical review of its application to cross-power spectral densities
Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity. Since its introduction in 2003 for functional magnetic resonance imaging data, DCM has been extended to electrophysiological data, and several variants hav...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-12-01
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| Series: | NeuroImage |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921009356 |