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.
Lectures (incl. practical sessions) take place on Tuesdays, 8:15 - 12:00, due to Covid-19 all lectures will be held online.
In this year's course, we will analyze data which was acquired in previous years. Unfortunately, the current sitaution does not allow us to scan our own data this year.
We will use Moodle (https://moodle-app2.let.ethz.ch) to share slides etc.
First part - Basic analysis of fMRI data (UZH/ETH and MED):
22.09. 08:15-10:00 Foundations of functional fMRI: neurophysiology and physics (Jakob Heinzle)
10:15-12:00 Setting up Matlab and SPM on own computers, Basic functions of SPM (Jakob Heinzle)
29.09. 08:15-10:00 Why is fMRI important for medicine? (Klaas Enno Stephan)
10:15-12:00 Introduction to SPM and Course data (Sandra Iglesias, Jakob Heinzle)
06.10. 08:15-10:00 Introduction to Spatial preprocessing of fMRI images (Jakob Heinzle)
10:15-12:00 Analysis of own data - Preprocessing (Jakob Heinzle, Sandra Iglesias)
13.10. 08:15-10:00 (ETH/UZH) Noise models in fMRI and noise correction (Matthias Müller-Schrader)
10:15-12:00 PhysIO (Matthias Müller-Schrader)
20.10. 08:15-10:00 The General Linear Model for fMRI analyses and inference I (Klaas Enno Stephan)
10:15-12:00 Analysis of own data - Research question and GLM (Sandra Iglesias, Jakob Heinzle)
27.10. 08:15-10:00 The General Linear Model for fMRI analyses and inference II (Klaas Enno Stephan)
10:15-12:00: Analysis of own data - First level analysis and inference (Sandra Iglesias, Jakob Heinzle)
03.11. 08:15-10:00 Event-related fMRI and design efficiency (Jakob Heinzle)
10:15-12:00 Analysis of own data and preparation of short presentation (Jakob Heinzle, Sandra Iglesias)
10.11. 08:15-10:00 Experimental design and Resting State Analysis (Inês Borges Pereira, Sandra Iglesias)
10:15-12:00 Short presentation of results of analysis of own data (MED)
Second part - Advanced topics (UZH/ETH):
17.11. 08:15-10:00 Group level analysis (Sandra Iglesias)
10:15-12:00 Tutorial: Group level analysis (Sandra Iglesias)
24.11. 08:15-10:00 Bayesian inference and Bayesian model selection (Klaas Enno Stephan)
10:15-12:00 Tutorial: BMA and BMS (Klaas Enno Stephan)
01.12. 08:15-10:00 Computational Neuroimaging (model-based fMRI) (Birte Toussaint)
10:15-12:00 Tutorial: Model based fMRI (Birte Toussaint)
08.12. 08:15-10:00 Introduction to Dynamic Causal Modelling (Stefan Frässle)
10:15-12:00 Tutorial: DCM analysis (Stefan Frässle)
15.12. 10:00-11:30 Exam (UZH/ETH)
Exam dates and testat:
First part (Medizin Mantelstudium): No formal exam, but in order to get the testat, you need to present your data analysis in a short presentation during the tutorial on Tuesday, 10.11.2020', 10:15-12:00, These presentations will be held online via ZOOM.
Main exam (all other students): Tuesday, 19.01.2021, Oral exam, 30 Minutes slots with 3 students.
Sandra Iglesias: firstname.lastname@example.org
Jakob Heinzle: email@example.com