227-0967-00L  Computational Neuroimaging Clinic

SemesterFrühjahrssemester 2020
DozierendeK. Stephan
Periodizitätjedes Semester wiederkehrende Veranstaltung
LehrspracheEnglisch


KurzbeschreibungThis seminar teaches problem solving skills for computational neuroimaging (incl. associated computational analyses of 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., concerning mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
Lernziel1. Consolidation of theoretical knowledge (obtained in one of 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.
InhaltThis seminar teaches problem solving skills for computational neuroimaging (incl. associated computational analyses of 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., concerning mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
Voraussetzungen / BesonderesThe participants are expected to be familiar with general principles of statistics and have successfully completed at least one of the following courses:
'Methods & models for fMRI data analysis',
'Translational Neuromodeling',
'Computational Psychiatry'