227-0973-00L  Translational Neuromodeling

SemesterSpring Semester 2022
LecturersK. Stephan
Periodicityyearly recurring course
Language of instructionEnglish


Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits8 credits
ExaminersK. Stephan
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Admission requirementGood knowledge of principles of statistics,
good programming skills (MATLAB, Julia, or Python).
Additional information on mode of examinationStudents are required to use one of the examples discussed in the course as a basis for either developing their own generative model or for applying an existing model to a clinical question in an original manner.
The model/ analysis is to be submitted as open source code (in MATLAB, Julia or Python), and the motivation and results are presented in a 15 min oral presentation followed by 15 min critical discussion. Group work (up to 3 students) is required. The submitted code must be executable without any dependencies on specific operating systems or local setups.
Grading will depend on (i) originality of the question that is addressed, (ii) quality and degree of completion of the modeling, (iii) clarity and functionality of the code, (iv) the quality and clarity of the oral presentation, (iv) the quality and clarity of the written project report.
The code is to be submitted by 02.06.2022; the oral presentations take place on 03.06.2022
Admission to the final project is subject to students having successfully obtained at least 40% of the points for each exercise (1 miss allowed) during the semester.