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Unit information: Computational Neuroscience in 2016/17

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Unit name Computational Neuroscience
Unit code COMSM2127
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Houghton
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Department of Computer Science
Faculty Faculty of Engineering

Description

This unit introduces the quantitative theory and models of computations performed by the brain. The lectures will progress through different levels of abstraction: from detailed models of single neurones based on neurophysiology to high-level models of interactions between networks of neurones explaining human behaviour. The following topics are discussed:

1. Models of a single neurone: integrate and fire model based on neurophysiology.

2. Models of neural networks: models of different types of memory in hippocampus and cortex, models of feature extraction in thalamus and visual cortex.

3. Models of neural systems: models of decision making, reinforcement learning and cognitive control.

Reading and References

Lecture notes. Background reading to include: * Dayan P & Abbott LF (2001) Theoretical Neuroscience: Computational and Mathematical Modelling of Neural Systems, MIT Press. Recommended. * O'Reilly RC & Munataka Y (2000) Computational Explorations in Cognitive Neuroscience, MIT Press. * Feng J (Ed.) (2003) Computational Neuroscience: A Comprehensive Approach, Chapman & Hall. * Eliasmith C & Anderson C (2002) Neural Engineering: Computation, Representation and Dynamics in Neurobiological Systems, Bradford Book. * Rolls E & Deco G (2002) Computational Neuroscience of Vision, Oxford University Press.

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