Introduction to basic methods of computational modelling of biological neurons and neural circuits.
| Paper title | Computational Neuroscience |
|---|---|
| Paper code | COSC422 |
| Subject | Computer Science |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Not offered in 2022 (On campus) |
| Domestic Tuition Fees (NZD) | $1,371.61 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Restriction
- NEUR 422
- Eligibility
There are no formal prerequisites for the 400-level papers, but prior knowledge is assumed.
- Contact
Computer Science Adviser (adviser@cs.otago.ac.nz)
- More information link
- View further information about COSC 422 (i.e. syllabus of lectures, supplementary materials, resources and assignments)
- Teaching staff
- Lecturer: To be advised
- Paper Structure
- The paper will look at how humans and animals process information at the level of
single neurons in the brain and later how neural activity is used to modify synaptic
connections, which is the mechanism that underlies formation of memories. Along with
the principles and methods of computational neuroscience, we will also learn how to
implement neurons and small neural circuits in NEURON, which is a freely available
computational neuroscience software, widely used all over the world. Given the interdisciplinary
nature of this paper, we will ensure that students first learn all the fundamental
concepts before they are applied in hands-on experience with NEURON.
Assessment:- Two programming assignments using NEURON: 2 x 25% = 50%
- Final closed-book exam: 50%
- Teaching Arrangements
- There is one 2-hour lecture per week.
- Textbooks
- Principles of Computational Modelling in Neuroscience, by David Sterratt, Bruce Graham, Andrew Gillies, and David Willshaw, published by Cambridge University Press, Cambridge, U.K., 2011.
- Graduate Attributes Emphasised
- Interdisciplinary perspective, Scholarship, Communication, Ethics.
View more information about Otago's graduate attributes. - Learning Outcomes
- The paper will give students an understanding of:
- Fundamental mechanisms of biological information processing at the level of individual neurons
- Fundamental mechanisms of biological information processing at the level of small neural circuits
- How to implement neurons and small circuits in NEURON and hands-on experience with the subject
- Limitations of computation in the study of the brain
- Interdisciplinary collaboration and multidisciplinary perspective
- Ethical considerations of the study of the brain
