Undergraduate Course: Introduction to Computational Neuroscience (INFR09037)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 9 (Year 3 Undergraduate) |
Credits | 10 |
| Home subject area | Informatics |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | Cognitive processes, language processing, and vision, are examples of human behaviour that are all ultimately implemented in neural hardware. The study of the biological implementation of these processes plays a crucial role in thinking about such processes as it both restricts and inspires models, and moreover serves as an alternative computational paradigm. This course introduces students to computational neuroscience, which studies how the brain computes based on the neural hardware. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Successful completion of Year 2 of Cognitive Science degree, an Informatics Single or Combined Degree, or equivalent by permission of the School. The students are expected to have a decent grounding in mathematics and familiarity with linear algebra, first order differential equations, and basic probability theory. |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
- Demonstrate a basic knowledge of neuroscience and neural computation.
- Abstract neuroscience experimental data to a model and should be able to critically evaluate these models.
- Understand the major limitations in verifying models experimentally. |
Assessment Information
Written Examination 100
Assessed Assignments 0
Oral Presentations 0 |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
- Gross brain anatomy and experimental techniques
- Basics of neurons: morphology, action potentials
- Synaptic communication
- Coding of information in the nervous system, for instance in the visual system
- Neural implementation of cognitive processes, like decision making
- Description of learning and memory in neural terms
- Considerations for modelling the nervous system |
| Transferable skills |
Not entered |
| Reading list |
-Abbott and Dayan (2001) Theoretical Neuroscience. MIT press (recommended)
- Trappenberg (2009) Fundamentals of Computational Neuroscience (recommended) |
| Study Abroad |
Not entered |
| Study Pattern |
Lectures 20
Tutorials 10
Timetabled Laboratories 0
Non-timetabled assessed assignments 0
Private Study/Other 70
Total 100 |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Nigel Goddard
Tel: (0131 6)51 3091
Email: Nigel.Goddard@ed.ac.uk |
Course secretary | Miss Tamise Totterdell
Tel: 0131 650 9970
Email: t.totterdell@ed.ac.uk |
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