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COSC422 Computational Neuroscience

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 2018
Domestic Tuition Fees (NZD) $1,282.09
International Tuition Fees (NZD) $5,357.07

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Restriction
NEUR 422
Eligibility
There are no formal prerequisites for the 400-level papers, but prior knowledge is assumed. Admission to these papers is restricted not only by numbers, but by satisfactory grades in 300-level COSC papers.
Contact
Computer Science Adviser
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.
Course outline
View the course outline for COSC 422
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

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Timetable

Not offered in 2018

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
None

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 2019
Domestic Tuition Fees Tuition Fees for 2019 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

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)

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

^ Top of page

Timetable

Not offered in 2019

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
None