Contrast sensitivity adaptation in a virtual spiking retina and its adequation with mammalians retinas
- Adrien Wohrer, Guillaume Masson, Laurent Perrinet, Pierre Kornprobst, Thierry Vieville. Contrast sensitivity adaptation in a virtual spiking retina and its adequation with mammalians retinas. In Perception, pages 67. 2009 abstract
- Kuffler. Discharge patterns and functionnal organization of mammalian retina.. Journal of Neurophysiology, 16:37--68, 1953 abstract
- R. W. Rodieck. Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vision Research, 5:583-601, 1965 abstract
- C. Enroth-Cugell, J. G. Robson. The Contrast Sensitivity of Retinal Ganglion Cells of the Cat.. Journal of Physiology, (187):517-23, 1966 abstract
- K. I. Naka, W. A. Rushton. S-potentials from luminosity units in the retina of fish (Cyprinidae).. Journal of Physiology, 185(3):587--99, 1966 abstract
- Mandyam V. Srinivasan, Simon B. Laughlin, A Dubs. Predictive coding: A fresh view of inhibition in the retina. Proceedings of the Royal Society of London. Series B, Biological Sciences, 216(1205):427--59, 1982 abstractInterneurons exhibiting centre--surround antagonism within their receptive fields are commonly found in peripheral visual pathways. We propose that this organization enables the visual system to encode spatial detail in a manner that minimizes the deleterious effects of intrinsic noise, by exploiting the spatial correlation that exists within natural scenes. The antagonistic surround takes a weighted mean of the signals in neighbouring receptors to generate a statistical prediction of the signal at the centre. The predicted value is subtracted from the actual centre signal, thus minimizing the range of outputs transmitted by the centre. In this way the entire dynamic range of the interneuron can be devoted to encoding a small range of intensities, thus rendering fine detail detectable against intrinsic noise injected at later stages in processing. This predictive encoding scheme also reduces spatial redundancy, thereby enabling the array of interneurons to transmit a larger number of distinguishable images, taking into account the expected structure of the visual world. The profile of the required inhibitory field is derived from statistical estimation theory. This profile depends strongly upon the signal: noise ratio and weakly upon the extent of lateral spatial correlation. The receptive fields that are quantitatively predicted by the theory resemble those of X-type retinal ganglion cells and show that the inhibitory surround should become weaker and more diffuse at low intensities. The latter property is unequivocally demonstrated in the first-order interneurons of the fly's compound eye. The theory is extended to the time domain to account for the phasic responses of fly interneurons. These comparisons suggest that, in the early stages of processing, the visual system is concerned primarily with coding the visual image to protect against subsequent intrinsic noise, rather than with reconstructing the scene or extracting specific features from it. The treatment emphasizes that a neuron's dynamic range should be matched to both its receptive field and the statistical properties of the visual pattern expected within this field. Finally, the analysis is synthetic because it is an extension of the background suppression hypothesis (Barlow & Levick 1976), satisfies the redundancy reduction hypothesis (Barlow 1961 a, b) and is equivalent to deblurring under certain conditions (Ratliff 1965)..
- L R Stanford. Conduction velocity variations minimize conduction time differences among retinal ganglion cell axons, URL . Science, 238(4825):358-360, 1987 abstractThe visual system is able to accurately represent the spatiotemporal relations among the elements of a changing visual scene as the image moves across the retinal surface. This precise spatiotemporal mapping occurs despite great variability in retinal position and conduction velocity even among retinal ganglion cells of the same physiological class-a variability that would seem to reduce the precision with which spatiotemporal information can be transmitted to central visual areas. There was a strong negative relation between the intraretinal and extraretinal conduction time for axons of individual ganglion cells of the X-cell class. The effect of this relation was to produce a nearly constant total transmission time between the soma of a retinal X cell and its central target site. Thus, the variation in the conduction velocities of retinal ganglion cell axons may ensure that, regardless of the constraints imposed by retinal topography, a precise spatiotemporal central representation of the retinal image is maintained..
- Joseph J. Atick, Norman A. Redlich. What Does the Retina Know about Natural Scenes?. Neural Computation, 4(2):196--210, 1992 abstract
- Markus Meister, L. Lagnado, D. A. Baylor. Concerted signaling by retinal ganglion cells.. Science, 270(5239):1207--10, 1995 abstractTo analyze the rules that govern communication between eye and brain, visual responses were recorded from an intact salamander retina. Parallel observation of many retinal ganglion cells with a microelectrode array showed that nearby neurons often fired synchronously, with spike delays of less than 10 milliseconds. The frequency of such synchronous spikes exceeded the correlation expected from a shared visual stimulus up to 20-fold. Synchronous firing persisted under a variety of visual stimuli and accounted for the majority of action potentials recorded. Analysis of receptive fields showed that concerted spikes encoded information not carried by individual cells; they may represent symbols in a multineuronal code for vision..
- Sheila Nirenberg, Markus Meister. The Light Response of Retinal Ganglion Cells Is Truncated by a Displaced Amacrine Circuit. Neuron, 18:637?-50, 1997 abstract
- S.M. Smirnakis, M.J. Berry, D.K. Warland, William Bialek, Markus Meister. Adaptation of retinal processing to image contrast and spatial scale. Nature, 386:69-73, 1997 abstract
- DK Warland, P. Reinagel, Markus Meister. Decoding visual information from a population of retinal ganglion cells. Journal of Neurophysiology, 78:2336-2350, 1997 abstract
- Sheila Nirenberg, Peter E Latham. Population coding in the retina. Current Opinion in Neurobiology, (8):488--93, 1998 abstract
- Markus Meister, Michael J. Berry. The Neural Code of the Retina. Neuron, 22:435--50, 1999 abstract
- Jonathan D. Victor. Temporal Aspects of Neural Coding in the Retina and Lateral Geniculate. Network: Computation in Neural Systems, 10:R1-R66, 1999 abstract
- P Reinagel, R C Reid. Temporal coding of visual information in the thalamus., URL . Journal of Neuroscience, 20(14):5392--400, 2000 abstractThe amount of information a sensory neuron carries about a stimulus is directly related to response reliability. We recorded from individual neurons in the cat lateral geniculate nucleus (LGN) while presenting randomly modulated visual stimuli. The responses to repeated stimuli were reproducible, whereas the responses evoked by nonrepeated stimuli drawn from the same ensemble were variable. Stimulus-dependent information was quantified directly from the difference in entropy of these neural responses. We show that a single LGN cell can encode much more visual information than had been demonstrated previously, ranging from 15 to 102 bits/sec across our sample of cells. Information rate was correlated with the firing rate of the cell, for a consistent rate of 3.6 +/- 0.6 bits/spike (mean +/- SD). This information can primarily be attributed to the high temporal precision with which firing probability is modulated; many individual spikes were timed with better than 1 msec precision. We introduce a way to estimate the amount of information encoded in temporal patterns of firing, as distinct from the information in the time varying firing rate at any temporal resolution. Using this method, we find that temporal patterns sometimes introduce redundancy but often encode visual information. The contribution of temporal patterns ranged from -3.4 to +25.5 bits/sec or from -9.4 to +24.9% of the total information content of the responses..
- Rufin van Rullen, Simon J. Thorpe. Rate coding versus temporal order coding: what the retina ganglion cells tell the visual cortex. Neural Computation, 13(6):1255--83, 2001 abstract
- Eric Castet, S. Jeanjean, Guillaume S. Masson. 'Saccadic suppression'- no need for an active extra-retinal mechanism., URL . Trends in Neurosciences, 24(6):316-8, 2001 abstract
- Markus Meister, Toshihiko Hosoya. Are Retinal Ganglion Cells Independent Encoders?. Nature, 2001 abstract
- Botond Roska, Frank Werblin. Vertical interactions across ten parallel, stacked respresentations in the mammalian retina.. Nature, 410:583--7, 2001 abstract
- Eero P. Simoncelli, David J. Heeger. Representing retinal image speed in visual cortex. Nature Neuroscience, 4:461 -- 2, 2001 abstract
- E J Chichilnisky. A simple white noise analysis of neuronal light responses.. Network: Computation in Neural Systems, 12(2):199--213, 2001 May abstractA white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed..
- Eric Castet, S. Jeanjean, Guillaume S. Masson. Motion perception of saccade-induced retinal translation., URL . Proceedings of the National Academy of Sciences USA, 99(23):15159-63, 2002 abstract
- Adam M Sillito, Helen E Jones. Corticothalamic interactions in the transfer of visual information.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 357(1428):1739--52, 2002 abstractThalamic function does not stand apart, as a discrete processing step, from the cortical circuitry. The thalamus receives extensive feedback from the cortex and this influences the firing pattern, synchronization and sensory response mode of relay cells. A crucial question concerns the extent to which the feedback simply controls the state and transmission mode of relay cells and the extent to which the feedback participates in the specific processing of sensory information. Using examples from experiments examining the influence of feedback from the visual cortex to the lateral geniculate nucleus (LGN), we argue that thalamic mechanisms are selectively focused by visually driven feedback to optimize the thalamic contribution to segmentation and global integration. This involves effects on both the temporal and spatial parameters characterizing the responses of LGN cells and includes, for example, motion-driven feedback effects from MT (middle temporal visual area) relayed via layer 6 of V1 (primary visual cortex)..
- J. Hans van Hateren, L. Ruttiger, H. Sun, B. B. Lee. Processing of Natural Temporal Stimuli by Macaque Retinal Ganglion Cells. Journal of Neuroscience, 22(22):9945---60, 2002 abstract
- L. S. Balasuriya. An artificial retina with a self-organised retinal receptive field tessellation. In Proceedings of the Biologically-inspired Machine Vision, Theory and Application symposium, Artificial Intelligence and the Simulation of Behaviour Convention, Aberystwyth, 2003 abstract
- Helga Kolb. How the Retina Works Much of the construction of an image takes place in the retina itself through the use of specialized neural circuits. American Scientist, 91, 2003 abstract
- E. J. Chichilnisky, R. S. Kalmar. Temporal Resolution of Ensemble Visual Motion Signals in Primate Retina. Journal of Neuroscience, 23(17):6681--9, 2003 abstract
- Stephen J Eglen, Peter J Diggle, John B Troy. Homotypic constraints dominate positioning of on- and off-center beta retinal ganglion cells.. Visual Neuroscience, 22(6):859--871, 2005 abstractBeta retinal ganglion cells (RGCs) of the cat are classified as either on-center or off-center, according to their response to light. The cell bodies of these on- and off-center RGCs are spatially distributed into regular patterns, known as retinal mosaics. In this paper, we investigate the nature of spatial dependencies between the positioning of on- and off-center RGCs by analysing maps of RGCs and simulating these patterns. We introduce principled approaches to parameter estimation, along with likelihood-based techniques to evaluate different hypotheses. Spatial constraints between cells within-type and between-type are assumed to be controlled by two univariate interaction functions and one bivariate interaction function. By making different assumptions on the shape of the bivariate interaction function, we can compare the hypothesis of statistical independence against the alternative hypothesis of functional independence, where interactions between type are limited to preventing somal overlap. Our findings suggest that the mosaics of on- and off-center beta RGCs are likely to be generated assuming functional independence between the two types. By contrast, allowing a more general form of bivariate interaction function did not improve the likelihood of generating the observed maps. On- and off-center beta RGCs are therefore likely to be positioned subject only to homotypic constraints and the physical constraint that no two somas of opposite type can occupy the same position..
- Jonathan W Pillow, Liam Paninski, Valerie J Uzzell, Eero P. Simoncelli, E J Chichilnisky. Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model.. Journal of Neuroscience, 25(47):11003--13, 2005 abstractSensory encoding in spiking neurons depends on both the integration of sensory inputs and the intrinsic dynamics and variability of spike generation. We show that the stimulus selectivity, reliability, and timing precision of primate retinal ganglion cell (RGC) light responses can be reproduced accurately with a simple model consisting of a leaky integrate-and-fire spike generator driven by a linearly filtered stimulus, a postspike current, and a Gaussian noise current. We fit model parameters for individual RGCs by maximizing the likelihood of observed spike responses to a stochastic visual stimulus. Although compact, the fitted model predicts the detailed time structure of responses to novel stimuli, accurately capturing the interaction between the spiking history and sensory stimulus selectivity. The model also accounts for the variability in responses to repeated stimuli, even when fit to data from a single (nonrepeating) stimulus sequence. Finally, the model can be used to derive an explicit, maximum-likelihood decoding rule for neural spike trains, thus providing a tool for assessing the limitations that spiking variability imposes on sensory performance..
- Toshihiko Hosoya, Stephen A Baccus, Markus Meister. Dynamic predictive coding by the retina, URL . Nature, 436(7047):71-7, 2005 abstract
- José-Ma\ nuel Alonso, C.-I. Yeh, C. Weng, C. Stoelzel. Retinogeniculate connections: a balancing act between connection specificity and receptive field diversity. Progress in Brain Research, 154:3--13, 2006 abstract
All material (c) L. Perrinet. Please check the copyright notice.
This work was supported by European integrated project FP6-015879, "FACETS".