psy241 - Computation in Neuroscience (Complete module description)
Module label | Computation in Neuroscience |
Module code | psy241 |
Credit points | 6.0 KP |
Workload | 180 h |
Institute directory | Department of Psychology |
Applicability of the module |
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Responsible persons |
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Prerequisites | Enrolment in Master's programme Neurocognitive Psychology. Module psy241 is only relevant for students who started their studies before winter term 19/20. (All other students study module psy240.) |
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:** [nop] + Neuropsychological / neurophysiological knowledge + experimental methods ++ statistics & scientific programming + critical & analytical thinking + knowledge transfer + group work [/nop] |
Module contents | **Part 1: Introduction to scientific programming I (theoretical-practical seminar)** - Basic data types and structures - Flow control (conditions, loops, errors) - Testing and debugging - Functions **Part 2: Introduction to scientific programming II (theoretical-practical seminar)** - Classes and objects - Parallel processing - Frequency analysis methods - EEG processing **Part 3: Scientific programming I (excercise)** - Implementation of examples from part 1 **Part 4: Scientific programming II (exercise)** - Implementation of examples from part 2 |
Recommended reading | - Mathworks (2009): MATLAB online documentation - Wallisch P., et al. (2009): MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB. Elsevier/Academic |
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Language of instruction | English |
Duration (semesters) | 2 Semester |
Module frequency | The module will be offered every winter term. |
Module capacity | unlimited |
Type of module | Pflicht / Mandatory |
Module level | MM (Mastermodul / Master module) |
Teaching/Learning method | Part 1: theoretical-practical seminar; Part 2: theoretical-practical seminar; Part 3: excercise; Part 4: excercise; additional tutorials |
Type of course | Comment | SWS | Frequency | Workload of compulsory attendance |
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Theory-practice seminars | 2 semester hours per week for winter and summer term |
4 | SuSe and WiSe | 56 |
Exercises | 1 semester hour per week for winter and summer term. |
2 | SuSe and WiSe | 28 |
Tutorial | 2 semester hours per week in winter and summer term |
SuSe and WiSe | 0 | |
Total module attendance time | 84 h |
Examination | Prüfungszeiten | Type of examination |
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Final exam of module | exam period at the end of the summer term |
The participants will have to independently develop and program a solution for a given neuroscientific problem. Both the written code as well as the documentation of the approach taken will be assessed. Bonus for regularly handing in a total of 12 programming exercises. |