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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Introduction to Computational Neuroscience (INFR09037)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 9 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryCognitive 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.
Course description - 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
Entry Requirements (not applicable to Visiting Students)
Pre-requisites 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.
Information for Visiting Students
Pre-requisitesNone
Course Delivery Information
Not being delivered
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.
Reading List
-Abbott and Dayan (2001) Theoretical Neuroscience. MIT press (recommended)
- Trappenberg (2009) Fundamentals of Computational Neuroscience (recommended)
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserDr Nigel Goddard
Tel: (0131 6)51 3091
Email: Nigel.Goddard@ed.ac.uk
Course secretaryMr Pim Totterdell
Tel: (0131 6)50 4565
Email: P.Totterdell@ed.ac.uk
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