Course catalogue doctoral education - VT24

  • Application can be done between 2023-10-16 and 2023-11-15
Application closed
Title Network Neuroscience
Course number 5697
Programme Neuroscience
Language English
Credits 1.5
Date 2023-10-02 -- 2023-10-26
Responsible KI department Department of Clinical Neuroscience
Specific entry requirements Basic knowledge of brain imaging
Purpose of the course The purpose of this course is to provide students with the foundations of network theory. This course will cover all aspects of creating network models from neuroimaging data (theory, assumptions, visualization, and quantifying models).
Intended learning outcomes After the course, the doctoral student shall have obtained a thorough knowledge about core concepts about network neuroscience. This includes to be able to: 1) create network models; 2) apply and interpret network measures calculated from models (centrality measures, shortest paths, community detection etc); 3) implement a network analysis and visualize the results; 4) show understanding about how network models have been applied within the neurosciences; 5) show understanding about how network models relate to theory; 6) apply recent developments within network neuroscience including multilayer connectivity and deep learning analyses of brain networks
Contents of the course The basics of network models, measures to quantify networks, history of network science and applications of network models in neuroscience, exercises in how to construct network models in the second version of our software BRAPH (Brain Analysis using Graph Theory; and recent developments in network neuroscience. Each student will also do an individual research project applying elements from the course onto data, which can be provided by the organizers or by the student’s own PhD projects.
Teaching and learning activities Lectures, seminars, demonstrations, laboratory exercises, individual mini research project, oral presentation, short written report.
Compulsory elements Mandatory attendance to lectures and presentation. Absence during lectures will require completing supplementary written tasks.
Examination Individual mini research project. This can be carried out on the student’s own data or open data provided. The analysis should be presented in a 10 minute presentation. The students are also required to submit a short written report on their project.
Literature and other teaching material Selected original research and review papers will be distributed well in advance of the course.
Number of students 8 - 20
Selection of students Selection will be based on 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) start date of doctoral studies (priority given to earlier start date)
More information Course schedule:
02/10/2023. 09:00 to 15:00
05/10/2023. 09:00 to 15:00
06/10/2023. 09:00 to 15:00
09/10/2023. 09:00 to 15:00
13/10/2023. 09:00 to 15:00
26/10/2023. 09:00 to 15:00 - Examination

Course Location:
Stora Sammanträdesrummet, Nobels Väg 9, 4th floor, KI Solna.
Additional course leader Peter Fransson
Latest course evaluation Not available
Course responsible Joana Braga Pereira
Department of Clinical Neuroscience
Contact person -