psy240 - Computation in Neuroscience (Complete module description)
| Module label | Computation in Neuroscience |
| Modulkürzel | psy240 |
| Credit points | 9.0 KP |
| Workload | 270 h |
| Institute directory | Department of Psychology |
| Verwendbarkeit des Moduls |
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| Zuständige Personen |
Stecher, Heiko (Module responsibility)
Stecher, Heiko (Prüfungsberechtigt)
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| Prerequisites | Enrolment in Master's programme Neurocognitive Psychology. |
| 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 |
| Module contents | Part 1: Introduction to scientific programming I (lecture): winter
Basic data types and structures Flow control (conditions, loops, errors) Testing and debugging Functions Part 2: Introduction to scientific programming II (lecture): summer Complex data structures
EEG processing
Frequency analysis methods Introduction to toolboxes
Part 3: Scientific programming I (excercise): winter Implementation of examples from part 1 Part 4: Scientific programming II (exercise): summer Implementation of examples from part 2 Part 5: Computer-controlled experimentation (seminar): summer Computer hardware basics Scripting and programming experiments Combining stimulus delivery with EEG, Eyetracking, etc. Temporal precision |
| Literaturempfehlungen |
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| Links | |
| Language of instruction | English |
| Duration (semesters) | 2 Semester |
| Module frequency | The module will start every winter term. |
| Module capacity | unlimited |
| Reference text | Important note: Passing the exam of psy240 is mandatory for starting a Practical Project (psy260) and the Master's thesis. |
| Modullevel / module level | MM (Mastermodul / Master module) |
| Modulart / typ of module | Pflicht / Mandatory |
| Lehr-/Lernform / Teaching/Learning method | Part 1 and 2: lectures; Part 3 and 4: excercises; Part 5: seminar; additional tutorials |
| Vorkenntnisse / Previous knowledge |
| Form of instruction | Comment | SWS | Frequency | Workload of compulsory attendance |
|---|---|---|---|---|
| Lecture | 2h/week in winter and summer term |
4 | SoSe und WiSe | 56 |
| Seminar | 2 | SoSe | 28 | |
| Exercises | 1h/week in winter and summer term |
2 | SoSe und WiSe | 28 |
| Tutorial | voluntary |
SoSe und WiSe | 0 | |
| Präsenzzeit Modul insgesamt | 112 h | |||
| Examination | Prüfungszeiten | Type of examination |
|---|---|---|
| Final exam of module | exam period at the end of the summer term |
In a 90-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 'Presentation', part 5 (will be checked in StudIP). |
