A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI

• Published in: NeuroImage (Orlando, Fla.) Vol. 200; pp. 174 - 190
• Main Authors: Zeidman, Peter, Jafarian, Amirhossein, Corbin, Nadège, Seghier, Mohamed L., Razi, Adeel, Price, Cathy J., Friston, Karl J.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.10.2019; Elsevier Limited; Academic Press
• Subjects: Adult; Bayesian analysis; Blood; Brain; Brain - diagnostic imaging; Brain - physiology; Cognitive ability; Connectome - methods; Datasets as Topic; Functional magnetic resonance imaging; Guidelines as Topic; Hemodynamics; Humans; Hypotheses; Magnetic Resonance Imaging - methods; Mathematical models; Medical imaging; Models, Theoretical; Nervous system; Neural networks; Neuroimaging; NMR; Nuclear magnetic resonance; Research Design; Semantics; Software; Statistical analysis

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs of researchers in cognitive and clinical neu...