Evaluating rank-order code performance using a biologically-derived retinal model

We propose a model of the primate retinal ganglion cell layout corresponding to the foveal-pit to test rank-order codes as a means of sensory information transmission in primate vision. We use the model for encoding images in rank-order. We observe that the model is functional only when the lateral inhibition technique is used to remove redundancy from the sampled data. Further, more than 80% of the input information can be decoded by the time only up to 10% of the ganglion cells of our model have fired their first spikes.

[1]  Jacques Gautrais,et al.  Rank order coding , 1998 .

[2]  A. Cowey,et al.  The ganglion cell and cone distributions in the monkey's retina: Implications for central magnification factors , 1985, Vision Research.

[3]  Stephen B. Furber,et al.  Maximising information recovery from rank-order codes , 2007, SPIE Defense + Commercial Sensing.

[4]  D. Dacey,et al.  Dendritic field size and morphology of midget and parasol ganglion cells of the human retina. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[5]  J. Sjöstrand,et al.  Resolution, separation of retinal ganglion cells, and cortical magnification in humans , 2001, Vision Research.

[6]  Rufin van Rullen,et al.  Rate Coding Versus Temporal Order Coding: What the Retinal Ganglion Cells Tell the Visual Cortex , 2001, Neural Computation.

[7]  B J Melloni,et al.  How the retina works. , 1971, American Family Physician.

[8]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[9]  Steve Furber,et al.  Information recovery from rank-order encoded images , 2006 .

[10]  R. W. Rodieck Quantitative analysis of cat retinal ganglion cell response to visual stimuli. , 1965, Vision research.

[11]  J. Sjöstrand,et al.  Quantitative estimations of foveal and extra-foveal retinal circuitry in humans , 1999, Vision Research.

[12]  D. Field,et al.  Natural image statistics and efficient coding. , 1996, Network.

[13]  H. K. Hartline,et al.  INHIBITION IN THE EYE OF LIMULUS , 1956, The Journal of general physiology.

[14]  J. Sjöstrand,et al.  How many ganglion cells are there to a foveal cone? , 1994, Graefe's Archive for Clinical and Experimental Ophthalmology.

[15]  B. Boycott,et al.  Functional architecture of the mammalian retina. , 1991, Physiological reviews.

[16]  Basabdatta B. Sen,et al.  Information recovery from rank-order encoded images , 2008 .

[17]  Vladimir S. Petrovic,et al.  Subjective tests for image fusion evaluation and objective metric validation , 2007, Inf. Fusion.

[18]  H. Kolb,et al.  The midget pathways of the primate retina , 2004, Documenta Ophthalmologica.

[19]  L. Croner,et al.  Receptive fields of P and M ganglion cells across the primate retina , 1995, Vision Research.

[20]  C. Curcio,et al.  Topography of ganglion cells in human retina , 1990, The Journal of comparative neurology.

[21]  Vladimir Petrovic,et al.  Objective evaluation of signal-level image fusion performance , 2005 .

[22]  Denis Fize,et al.  Speed of processing in the human visual system , 1996, Nature.

[23]  D. Dacey The mosaic of midget ganglion cells in the human retina , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[24]  David R. Williams,et al.  Seeing through the photoreceptor mosaic , 1986, Trends in Neurosciences.

[25]  Heinz Wässle,et al.  Parallel processing in the mammalian retina , 2004, Nature Reviews Neuroscience.

[26]  B. Boycott,et al.  Retinal ganglion cell density and cortical magnification factor in the primate , 1990, Vision Research.

[27]  Simon J. Thorpe,et al.  Coding static natural images using spiking event times: do neurons Cooperate? , 2004, IEEE Transactions on Neural Networks.

[28]  H. Wässle,et al.  Physiological identification of a morphological class of cat retinal ganglion cells. , 1975, The Journal of physiology.