227-0971-00L  Computational Psychiatry

SemesterHerbstsemester 2016
DozierendeK. Stephan
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch



Lehrveranstaltungen

NummerTitelUmfangDozierende
227-0971-00 SComputational Psychiatry
Block course from August 29 to September 2, 2016.
60s Std.
29.08.08-18HG E 3 »
30.08.08-18HG E 3 »
31.08.08-18HG E 3 »
01.09.08-18HG E 3 »
02.09.08-18HG E 3 »
K. Stephan

Katalogdaten

KurzbeschreibungThis five-day course teaches state-of-the-art methods in computational psychiatry. It covers various computational models of cognition (e.g., learning and decision-making) and brain physiology (e.g., effective connectivity) of relevance for psychiatric disorders. The course not only provides theoretical background, but also demonstrates open source software in application to concrete examples.
LernzielThis course aims at bridging the gap between mathematical modelers and clinical neuroscientists by teaching computational techniques in the context of clinical applications. The hope is that the acquisition of a joint language and tool-kit will enable more effective communication and joint translational research between fields that are usually worlds apart.
InhaltThis five-day course teaches state-of-the-art methods in computational psychiatry. It covers various computational models of cognition (e.g., learning and decision-making) and brain physiology (e.g., effective connectivity) of relevance for psychiatric disorders. The course not only provides theoretical background, but also demonstrates open source software in application to concrete examples.

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte3 KP
PrüfendeK. Stephan
Formbenotete Semesterleistung
PrüfungsspracheEnglisch
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum PrüfungsmodusStudents wishing to obtain credit points are required to solve a set of exercises. These exercises involve programming simulations or analyses (in MATLAB) based on the modeling frameworks discussed in the course; code and results must be submitted for assessment. Grading takes into account clarity and correctness of the code, as well as the originality of the application. The exercises are made available after the course and must be submitted within two weeks.

Lernmaterialien

 
Hauptlinkhttps://www.tnu.ethz.ch/de/teaching.html
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Gruppen

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Einschränkungen

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Angeboten in

StudiengangBereichTyp
Biomedical Engineering MasterWahlfächer der VertiefungWInformation