Course description
Designed for doctoral candidates in neuroscience and related fields, this course will show you how network theory is useful to analyse your data, giving you hands-on experience on neuroimaging modeling from sMRI, DWI, fMRI, PET, EEG and MEG data. Importantly the same principles can be applied to other types of data such as multi-omics or clinical variables. Participants will construct, visualize, and quantify brain networks and will be able to build their own software with graphical user interface just by changing a few lines of code.
Prerequisites and Selection
Prerequisite courses, or equivalent
Basic knowledge of brain imaging
Selection
Selection will be based on:
1) the relevance of the course syllabus for the applicant’s individual study plan/research (according to written motivation).
2) start date of doctoral studies (priority given to earlier start date).
Course director
Assoc. Prof. Joana B. Pereira
Prof. Peter Fransson
Course syllabus
K8F5697
Department
Department of Clinical Neuroscience
Doctoral programme
Neuroscience
Type of course
**Other course
Keywords
graph theory, deep learning