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Investigation into Sub-Receptive Fields of Retinal Ganglion Cells with Natural Images
- Source :
- IJCNN
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Determining the receptive field of a retinal ganglion cell is critically important when formulating a computational model that maps the relationship between the stimulus and response. This process is traditionally undertaken using reverse correlation to estimate the receptive field. By stimulating the retina with artificial stimuli, such as alternating checkerboards, bars or gratings and recording the neural response it is possible to estimate the cell’s receptive field by analysing the stimuli that produced the response. Artificial stimuli such as white noise is known to not stimulate the full range of the cell’s responses. By using natural image stimuli, it is possible to estimate the receptive field and obtain a resulting model that more accurately mimics the cells’ responses to natural stimuli. This paper extends on previous work to seek further improvements in estimating a ganglion cell’s receptive field by considering that the receptive field can be divided into subunits. It is thought that these subunits may relate to receptive fields which are associated with bipolar retinal cells. The findings of this preliminary study show that by using subunits to define the receptive field we achieve a significant improvement over existing approaches when deriving computational models of the cell’s response.
- Subjects :
- 0301 basic medicine
Retina
Computational model
Computer science
Retinal
Retinal ganglion
03 medical and health sciences
chemistry.chemical_compound
Reverse correlation
030104 developmental biology
0302 clinical medicine
medicine.anatomical_structure
Retinal ganglion cell
chemistry
Receptive field
medicine
Neuroscience
030217 neurology & neurosurgery
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 International Joint Conference on Neural Networks (IJCNN)
- Accession number :
- edsair.doi...........7b05f911a158c1979551415750ddbb6d