psy240 - Computation in Neuroscience (Course overview)

psy240 - Computation in Neuroscience (Course overview)

Department of Psychology 9 KP
Module components Semester courses Examination
Lecture
  • No access 6.02.240_1 - Show lecturers
    • Dr. rer. nat. Heiko Stecher

    Tuesday: 12:15 - 13:45, weekly (from 18/10/22)

    38 students can attend in presence, the others can attend online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group.

Seminar
Exercises
  • No access 6.02.240_3 - Show lecturers
    • Dr. rer. nat. Heiko Stecher

    Tuesday: 14:15 - 15:45, weekly (from 18/10/22)

    38 students can attend in presence, the others can attend online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group.

Tutorial
  • No access 6.02.240_T - Show lecturers
    • Dr. rer. nat. Heiko Stecher

    Wednesday: 14:15 - 15:45, weekly (from 19/10/22)

Hinweise zum Modul
Prerequisites
Enrolment in Master's programme Neurocognitive Psychology.
Reference text
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
Module examination
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).
Skills to be acquired in this module
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