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) 2023
Methods & Models for fMRI HS (fall semester) 2022
Methods & Models for fMRI HS (fall semester) 2021
Methods & Models for fMRI HS (fall semester) 2020
Methods & Models for fMRI HS (fall semester) 2019
Methods & Models for fMRI HS (fall semester) 2018
Methods & Models for fMRI HS (fall semester) 2017