neu246 - Computational Neuroscience - Biophysical Modeling (Vollständige Modulbeschreibung)
Modulbezeichnung | Computational Neuroscience - Biophysical Modeling |
Modulkürzel | neu246 |
Kreditpunkte | 6.0 KP |
Workload | 180 h |
Einrichtungsverzeichnis | Department für Neurowissenschaften |
Verwendbarkeit des Moduls |
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Zuständige Personen |
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Teilnahmevoraussetzungen | Enrolment in Master program Neuroscience
Students from other study programs are welcome if space is available |
Kompetenzziele | Goals of this module: upon completion of this module, students… Skills to be acquired/ competencies: ++ Neuroscience knowledge |
Modulinhalte | This course consists of three weeks full-time work on the topic Biophysical modeling, which is introduced in lectures, discussed in depth using selected literature in the seminar and consolidated in computer-based hands-on exercises (in Matlab or Python). Portfolio tasks consists of programming and the interpretation of programming. Specific topics: Conductance-based single cell models using differential equations (passive membrane equation, integrate-and-fire, Hodgkin-Huxley) |
Literaturempfehlungen | Skripts for each course day will be provided prior to the course |
Links | |
Unterrichtssprache | Englisch |
Dauer in Semestern | 1 Semester |
Angebotsrhythmus Modul | Annualy, second half of winter term (January-February, after neu242) |
Aufnahmekapazität Modul | 18 |
Modulart | Wahlpflicht / Elective |
Modullevel | EB (Ergänzungsbereich / Complementary) |
Vorkenntnisse | Enrolment in Master program Neuroscience Students from other study programs are welcome if space is available. This module requires good programming skills! (As taught in neu710 or neu715.) |
Lehrveranstaltungsform | Kommentar | SWS | Angebotsrhythmus | Workload Präsenz |
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Vorlesung | 2 | WiSe | 28 | |
Übung | 4 | WiSe | 42 | |
Präsenzzeit Modul insgesamt | 70 h |
Prüfung | Prüfungszeiten | Prüfungsform |
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Gesamtmodul | During the course (assignment tasks) |
Portfolio, consisting of short tests, programming tasks, and interpretation of modeling / data analysis results |