Methods & Models for fMRI Analysis

Would you like to obtain good knowledge of the theoretical foundations of SPM and DCM and their application to empirical fMRI data?

This course teaches state-of-the-art methods and models for fMRI data analysis. It covers all aspects of statistical parametric mapping (SPM), incl. preprocessing, the general linear model, frequentist and Bayesian inference, multiple comparison corrections, and event-related designs, and Dynamic Causal Modelling (DCM), a novel approach for identification of nonlinear neuronal systems from neurophysiological data. A particular emphasis of the course will be on methodological questions arising in the context of neuroeconomic and clinical studies.

 

CURRENT AND PREVIOUS COURSES

Methods & Models for fMRI HS (fall semester) 2019

Methods & Models for fMRI HS (fall semester) 2018

Methods & Models for fMRI HS (fall semester) 2017

Methods & Models for fMRI HS (fall semester) 2016

Methods & Models for fMRI HS (fall semester) 2015