Name
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/IJCNN.2015.7280759 | Neural Networks |
Keywords | Field | DocType |
cellular biophysics,electro-oculography,medical signal processing,neurophysiology,physiological models,visual evoked potentials,action potentials,computational combinations,electrophysiological recordings,human vision system,human visual system,input-output response,internal components,mammalian retina,nonlinear models,optic nerve,preprocessing method,retinal ganglion cells,retinal neural structure,spike responses,spiking models,spiking neuron,visual stimulation,Retinal Ganglion Cells,Spike generation,Virtual Retina | Neuroscience,Retinal ganglion cell,Computer science,Human visual system model,Artificial intelligence,Retinal,Neuron,Electrophysiology,Computer vision,Retinal ganglion,Pattern recognition,Retina,Optic nerve | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Philip J. Vance | 1 | 41 | 4.92 |
| Sonya Coleman | 2 | 216 | 36.84 |
| Dermot Kerr | 3 | 50 | 13.84 |
| Gautham P. Das | 4 | 15 | 2.72 |
| T. Martin Mcginnity | 5 | 518 | 66.30 |