Over the past decade, dynamic causal modelling (DCM) has become the predominant way of characterising effective connectivity within networks of distributed neuronal responses, as measured with fMRI or electromagnetic responses.
This three-day course will be divided into theoretical and practical sessions using DCM in the SPM software package as well as the TAPAS toolbox (Translational Algorithms for Psychiatry-Advancing Science). Students will gain experience in:
- Preliminary GLM analysis and time series extraction using SPM for fMRI
- Bayesian methods in neuroimaging
- Testing hypotheses about neural connectivity using DCM
- Group-level connectivity analysis and prediction of clinical and cognitive variables
This course is ideally suited to people who have experience of basic fMRI analysis using the General Linear model (GLM) in any software package.
Optional background reading:
Generative models for clinical applications in computational psychiatry. Frässle et al., Wiley Interdisciplinary Reviews: Cognitive Science, 2018. https://doi.org/10.1002/wcs.1460
A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI. Zeidman et al., NeuroImage, 2019. https://doi.org/10.1016/j.neuroimage.2019.06.031
Coordinator & Accessibility Issues
Dr. Tali Weiss