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Modelling and Analysis of Retinal Ganglion Cells Through System Identification

Kerr, Dermot, McGinnity, Martin and Coleman, SA (2014) Modelling and Analysis of Retinal Ganglion Cells Through System Identification. In: International Conference on Neural Computation Theory and Applications (NCTA 2014), Rome, Italy. SCITEPRESS (Science and Technology Publications, Lda.). 7 pp. [Conference contribution]

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URL: http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0005069701580164

DOI: 10.5220/0005069701580164

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 system identification techniques to express the biological input-output coupling mathematically, and computational modelling techniques to model highly complex neuronal structures, we will "identify" ganglion cell behaviour with visual scenes, and represent the mapping between perception and response automatically.

Item Type:Conference contribution (Paper)
Keywords:System Identification, Retinal Ganglion Cells, Linear-Nonlinear Model
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:30855
Deposited By: Dr Dermot Kerr
Deposited On:21 Jan 2015 11:17
Last Modified:21 Jan 2015 11:17

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