227-0973-00L Translational Neuromodeling
| Semester | Frühjahrssemester 2023 |
| Dozierende | K. Stephan |
| Periodizität | jährlich wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 8 KP |
| Prüfende | K. Stephan |
| Form | benotete Semesterleistung |
| Prüfungssprache | Englisch |
| Repetition | Repetition nur nach erneuter Belegung der Lerneinheit möglich. |
| Zulassungsbedingung | Good knowledge of principles of statistics, good programming skills (MATLAB is required; Julia an additional bonus). |
| Zusatzinformation zum Prüfungsmodus | Students 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 or Julia), 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 the (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) quality and clarity of the oral presentation, (iv) quality and clarity of the written project report. The code is to be submitted by 1 June 2023 (23:59 CET); the oral presentations take place on 2 June 2023. 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. |