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.
Prerequisites / Notice
The participants are expected to have successfully completed at least one of the following courses: 'Methods & models for fMRI data analysis', 'Translational Neuromodeling', 'Computational Psychiatry'
Performance assessment
Performance assessment information (valid until the course unit is held again)
Repetition only possible after re-enrolling for the course unit.
Admission requirement
The participants are expected to have successfully completed at least one of the following courses: 'Methods & models for fMRI data analysis', Translational Neuromodeling', or 'Computational Psychiatry'
Additional information on mode of examination
Oral presentation and oral exam (20 min) concerning methods related to one of the practical problems the seminar dealt with.
Performance assessment as a semester course