227-0973-00L Translational Neuromodeling
Semester | Frühjahrssemester 2020 |
Dozierende | K. Stephan |
Periodizität | jährlich wiederkehrende Veranstaltung |
Lehrsprache | Englisch |
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
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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 and/or Python). |
Zusatzinformation zum Prüfungsmodus | 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. |