Title :
Modelling of a retinal ganglion cell with simple spiking models
Author :
P. Vance;S.A. Coleman;D. Kerr;G.P. Das;T.M. McGinnity
Author_Institution :
School of Computing and Intelligent Systems, University of Ulster at Magee, Londonderry, N. Ireland, UK
fDate :
7/1/2015 12:00:00 AM
Abstract :
Modelling aspects of the human vision system, including the retina, is difficult due to insufficient knowledge about the internal components, organisation and complexity of the interactions within the system. Retinal ganglion cells are considered a core component of the human visual system as they convey the accumulated data as action potentials onto the optic nerve. Current techniques capable of mapping this input-output response involve computational combinations of linear and nonlinear models that are generally complex and lack any relevance to the underlying biophysics. This paper aims to model a retinal ganglion cell with a simple spiking neuron combined with a pre-processing method, which accounts for the preceding retinal neural structure. Performance of the models is compared with the spike responses obtained in the electrophysiological recordings from a mammalian retina subjected to visual stimulation.
Keywords :
"Machine vision","Retina","Visualization","Analytical models","Neurons","Biological system modeling"
Conference_Titel :
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN :
2161-4407
DOI :
10.1109/IJCNN.2015.7280759