227-0967-00L  Computational Neuroimaging Clinic

SemesterHerbstsemester 2016
DozierendeK. Stephan
Periodizitätjedes Semester wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarVoraussetzung: Erfolgreiche Abschluss der Lehrveranstaltung "Methods & Models for fMRI Data Analysis" (227-0969-00L).


KurzbeschreibungThis 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.
Lernziel1. 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.
InhaltThis 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.
Voraussetzungen / BesonderesThe participants are expected to have successfully completed at least one of the following courses:
'Methods & models for fMRI data analysis',
'Translational Neuromodeling',
'Computational Psychiatry'