Methods & Models for fMRI Analysis
Would you like to obtain good knowledge of the theoretical foundations of SPM and DCM and apply these methods to empirical fMRI data that you have acquired yourself?
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.
First part - Basic analysis of fMRI data (UZH/ETH and MED):
Date
Time and Place
Students
Topic
Links
19.09
08:15-12:00 ETZ F91
UZH/ETH students only
Introduction to basic probability theory and Bayes with hands-on examples (Eduardo Aponte)
26.09
08:15-10:00
UZH/ETH students
Scanning own experiment (Jakob Heinzle & Sara Tomiello)
08:15-10:00 ETZ F91
MED students
Intro to basic math med (linear algebra, matrix, correlation, basic statistics) (Dario Schöbi)
10:15-12:00 LFW E13
all students
Why is fMRI important for medicine? (Klaas Enno Stephan)
03.10
08:15-10:00
MED students
Scanning own experiment (Jakob Heinzle & Sandra Iglesias)
08:15-10:00 LFW E13
UZH/ETH students
Intro to basic math med (linear algebra, matrix, correlation, , simple statistics) (Dario Schöbi)
10:15-12:00 LFW E13
all students
Foundations of functional MRI: neurophysiology and physics (Jakob Heinzle)
10.10
08:15-10:00 LFW E13
all students
Introduction to Spatial preprocessing of fMRI images (Lars Kasper)
17.10
08:15-10:00 LFW E13
all students
The General Linear Model for fMRI analyses (Jakob Heinzle)
10:15-12:00 LFW E13
all students
Analysis of own data (GLM) (Jakob Heinzle)
24.10
08:15-10:00 LFW E13
all students
Classical (frequentist) inference and multiple comparison correction (Klaas Enno Stephan)
10:15-12:00 LFW E13
all students
Analysis of own data (1st level) (Klaas Enno Stephan)
31.10
08:15-10:00 LFW E13
all students
Event-related fMRI and design efficiency (Jakob Heinzle)
10:15-12:00 LFW E13
all students
Comparison of different designs from scanning (Jakob Heinzle)
07.11
08:15-10:00 LFW E13
all students
Experimental design and Resting State Analysis (Sandra Iglesias, Sara Tomiello)
10:15-12:00 LFW E13
all students
Short presentation of results of analysis of own data (MED/UZH)
Second part - Advanced topics (ETH):
Date
Time
Students
Topic
Links
14.11
08:15-12:00 LFW E13
ETH
Group level analysis (Sandra Iglesias)
10:15-12:00 LFW E13
ETH
Tutorial (Sandra Iglesias)
21.11
08:15-10:00 LFW E13
ETH
Noise models in fMRI and noise correction (Lars Kasper)
10:15-12:00 LFW E13
ETH
PhysIO (own data) (Lars Kasper)
28.11
08:15-10:00 LFW E13
ETH
Bayesian inference and Bayesian model selection (Klaas Enno Stephan)
10:15-12:00 LFW E13
ETH
BMA and BMS (Klaas Enno Stephan)
05.12
08:15-10:00 LFW E13
ETH
Computational Neuroimaging (model-based fMRI) (Andreea Diaconescu)
10:15-12:00 LFW E13
ETH
Tutorial (Sandra Iglesias)
12.12
08:15-10:00 LFW E13
ETH
Introduction to Dynamic Causal Modelling (Stefan Frässle)
10:15-12:00 LFW E13
ETH
DCM analysis (Stefan Frässle)
19.12
10:00-11:30 LFW E13
ETH
Exam
Exam dates and testat:
First part (Medizin Mantelstudium and UZH students): No formal exam, but in order to get the testat and ECTS, you need to present your data analysis in a short presentation during the tutorial on Tuesday, 07.11.2017, 10:15-12:00, Room: LFW E 13.
Main exam (all other students): Tuesday, 19.12.2017, 10:00-11:30, Room: LFW E13
Material for the exam: Bring with you something to write (pen), your Legi and an ID. No other material is allowed!
Contact:
Sandra Iglesias: iglesias@biomed.ee.ethz.ch
Jakob Heinzle: heinzle@biomed.ee.ethz.ch