CSE2330

Introduction to Computational Neuroscience ( 6 points, SCA Band 2, 0.125 EFTSL)

Leader: A Paplinski

Offered:
Clayton Second semester 2005 (Day)

Synopsis: Basic components of a neural system: neurons, synapses, dendrities, receptive fields. Hodgkin-Huxley model and its simulation on a computer. Inter-neuron communication and the principle of synaptic learning. Fundamentals of Neurobiology. Structure of the brain and brain regions. Fundamental concepts of data and signal encoding and processing. Filtering, approximation and interpolation, clustering, principal component analysis. Basic neural network architectures: pattern association, auto associative, feedforward, competitive and recurrent networks. Plasticity and Learning. Hebb rule, supervised, reinforced, error-correcting, unsupervised and competititve learning. Self organising maps.

Assessment: Practical work and assignments: 50% + Final examination: 50%

Contact Hours: Two hours of lectures and two hours of practical classes per week.

Prerequisites: The unit requires knowledge and maturity as obtained by completion of first year units either from the Faculty of Medicine or the Faculty of Information Technology.