This seminar teaches problem solving skills for the design and analysis of neuroimaging data (fMRI, EEG). It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich. Examples may include mass-univariate and multivariate analyses of fMRI data, dynamic causal modeling of fMRI and EEG data.
Objective
1. Consolidation of theoretical knowledge (obtained in the 'Methods & models for fMRI data analysis' lecture) 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 the design and analysis of neuroimaging data (fMRI, EEG). It deals with a wide variety of real-life problems that are brought to this meeting from the euroimaging community at Zurich. Examples may include mass-univariate and multivariate analyses of fMRI data, dynamic causal modeling of fMRI and EEG data, or analyses of neuroimaging data on the basis of Bayesian models of behaviour.
Performance assessment
Performance assessment information (valid until the course unit is held again)