227-0973-00L Translational Neuromodeling
|Semester||Spring Semester 2020|
|Periodicity||yearly recurring course|
|Language of instruction||English|
|Performance assessment information (valid until the course unit is held again)|
|Performance assessment as a semester course|
|ECTS credits||8 credits|
|Type||graded semester performance|
|Language of examination||English|
|Repetition||Repetition only possible after re-enrolling for the course unit.|
|Admission requirement||Good knowledge of principles of statistics,|
good programming skills (MATLAB and/or Python).
|Additional information on mode of examination||Students are required to use one of the examples discussed in the course as a basis for developing their own generative model and use it for simulations and/or inference in application to a clinical question (a real or fictitious one).|
This model is to be submitted as open source code (in MATLAB or Python), and the motivation and results are presented in a 10 min oral presentation followed by critical discussion. Group work (up to 3 students) is permitted. The submitted code must be executable without any dependencies on specific operating systems or local setups (e.g., no absolute pathnames).
Grading will depend on (i) originality of the question that is addressed, (ii) clarity, technical correctness and practicability of the code, (iii) the quality of the oral presentation and discussion in the report.
The code is to be submitted by 28 May 2020; the oral presentations take place on 29 May 2020 (12-18h).
Admission to the final project is subject to students having successfully completed at least 50% of the exercises during the semester.