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227-0967-00L 3 Credits MSC , NDS D-HEST , D-MAVT , D-PHYS , D-ITET
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Computational Neuroimaging Clinic

Lecturers & Examiners: Prof. Dr. Klaas Stephan
Prerequisite: Successful completion of course "Methods & Models for fMRI Data Analysis", "Translational Neuromodeling" or "Computational Psychiatry"
VVZ CR n/a

Last Updated: 2026-02-05 16:01:33

Abstract

This seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.

Objective

1. Consolidation of theoretical knowledge (obtained in the following courses: 'Methods & models for fMRI data analysis', 'Translational Neuromodeling', 'Computational Psychiatry') in a practical setting. 2. Acquisition of practical problem solving strategies for computational modeling of neuroimaging data.

Content

This seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.

General Information

Language
English
Levels
MSC , NDS
Frequency
Semesterly recurring

Examination

Type
ungraded semester performance
Oral exam (presentation 15 min. and questions 15 min) concerning computational/statistical methods related to one of the practical problems the seminar dealt with.

Course Components

Type Title Time & Place Hours
lecture Computational Neuroimaging Clinic
Place: WIL-F-105 at TNU (Wilfriedstrasse 6, 8032 Zürich)
  • Wed 10:00-12:00 (Ex te rn)
2 h weekly

Offered In