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
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2019.06.031

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 neuroscience. In this guide, we step through an exemplar fMRI analysis in detail, reviewing the current implementation of DCM and demonstrating recent developments in group-level connectivity analysis. In the appendices, we detail the theory underlying DCM and the assumptions (i.e., priors) in the models. In the first part of the guide (current paper), we focus on issues specific to DCM for fMRI. This is accompanied by all the necessary data and instructions to reproduce the analyses using the SPM software. In the second part (in a companion paper), we move from subject-level to group-level modelling using the Parametric Empirical Bayes framework, and illustrate how to test for commonalities and differences in effective connectivity across subjects, based on imaging data from any modality. •This guide walks through a group effective connectivity study using DCM and PEB.•Part 1, presented here, covers first level analysis using DCM for fMRI.•It clarifies the specific neural and haemodynamic models in DCM and their priors.•An accompanying dataset is provided with step-by-step analysis instructions.