psy240 - Computation in Neuroscience (Veranstaltungsübersicht)

psy240 - Computation in Neuroscience (Veranstaltungsübersicht)

Department für Psychologie 9 KP
Modulteile Semesterveranstaltungen Sommersemester 2024 Prüfungsleistung
Vorlesung
(
2h/week in winter and summer term
)
Seminar
Übung
(
1h/week in winter and summer term
)
  • Eingeschränkter Zugang 6.02.240_4 - Scientific Programming II Lehrende anzeigen
    • Dr. rer. nat. Heiko Stecher

    Dienstag: 14:00 - 15:00, wöchentlich (ab 02.04.2024)

    The exercises will take place in the first half of the session followed by a tutorial in the second half.

Tutorium
(
voluntary
)
  • Eingeschränkter Zugang 6.02.240_T - Matlab tutorial Lehrende anzeigen
    • Dr. rer. nat. Heiko Stecher

    Montag: 12:00 - 14:00, wöchentlich (ab 27.05.2024)
    Montag: 18:00 - 20:00, wöchentlich (ab 08.04.2024)

Hinweise zum Modul
Teilnahmevoraussetzungen

Enrolment in Master's programme Neurocognitive Psychology.

Hinweise

Important note:
Passing the exam of psy240 is mandatory for starting a Practical Project (psy260) and the Master's thesis.

Prüfungszeiten

exam period at the end of the summer term

Prüfungsleistung Modul

In a 120-minute written exam the participants will have to program MATLAB-scripts for a selection of neuroscientific data-analysis problems, demonstrating their skills in the different topics. The scripts and comments will be written on university-provided laptops and handed in via email or USB-drive.

Students need to hand in 1-2 programming tasks in the exercises to be allowed to take part in the exam.

Required active participation for gaining credits:
script for the presentation of experimental stimuli in part 5
attendance of at least 70% in the seminar 'computer-controlled experimentation', part 5 within one semester (will be checked in StudIP).

Kompetenzziele

Goals of module:
Students will acquire scientific programming skills as well as specific knowledge of
computational methods in neuroscience and cognition. They will learn to judge the
appropriateness and complexity of computational problems and solutions.

Competencies:
+ Neuropsychological / neurophysiological knowledge
+ experimental methods
++ statistics & scientific programming
+ critical & analytical thinking
+ knowledge transfer
+ group work