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.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | IEEE |
Number of pages | 8 |
DOIs | |
Publication status | Published (in print/issue) - 12 Jul 2015 |
Event | 2015 International Joint Conference on Neural Networks (IJCNN), - Killarney Duration: 12 Jul 2015 → … |
Conference
Conference | 2015 International Joint Conference on Neural Networks (IJCNN), |
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Period | 12/07/15 → … |
Keywords
- Retinal Ganglion Cells
- Virtual Retina
- Spike generation