Assessing parameter identifiability for Dynamic Causal Modelling of fMRI data

Assessing parameter identifiability for Dynamic Causal Modelling of fMRI data

Deterministic dynamic causal modelling (DCM) for fMRI data is a sophisticated approach to analyse effective connectivity in terms of directed interactions between brain regions of interest. To date it is difficult to know if acquired fMRI data will yield precise estimation of DCM parameters. Focusin...

Full description

Bibliographic Details
Main Authors: Carolin eArand, Elisa eScheller, Benjamin eSeeber, Jens eTimmer, Stefan eKlöppel, Bjoern eSchelter
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-02-01
Series:Frontiers in Neuroscience
Subjects:
functional magnetic resonance imaging
dynamic causal modelling
model parameters
parameter identifiability
profile likelihood
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00043/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00043/full

Similar Items