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Modelling and Analysis of Retinal Ganglion Cells with Neural Networks

Kerr, D, Coleman, SA and McGinnity, TM (2014) Modelling and Analysis of Retinal Ganglion Cells with Neural Networks. In: Irish Machine Vision and Image Processing 2014. UU. 6 pp. [Conference contribution]

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Abstract

Modelling biological systems is difficult due to insufficient knowledge about the internal components and organisation, and the complexity of the interactions within the system. At cellular level existing computational models of visual neurons can be derived by quantitatively fitting particular sets of physiological data using an input-output analysis where a known input is given to the system and its output is recorded. These models need to capture the full spatio-temporal description of neuron behaviour under natural viewing conditions. At a computational level we aspire to take advantage of state-of-the-art techniques to accurately model non-standard types of retinal ganglion cells. Using neural network techniques we model the highly complex neuronal structures of visual processing retinal cells and represent the mapping between perception and response automatically

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:30242
Deposited By: Dr Sonya Coleman
Deposited On:24 Sep 2014 15:35
Last Modified:24 Sep 2014 15:35

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