Adaptation to Changes in Higher-Order Stimulus Statistics in the Salamander Retina

Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.

[1]  Olivier Marre,et al.  Features and functions of nonlinear spatial integration by retinal ganglion cells , 2012, Journal of Physiology-Paris.

[2]  H. B. Barlow,et al.  Possible Principles Underlying the Transformations of Sensory Messages , 2012 .

[3]  Joseph J Atick,et al.  Could information theory provide an ecological theory of sensory processing? , 2011, Network.

[4]  Vijay Balasubramanian,et al.  Natural Images from the Birthplace of the Human Eye , 2011, PloS one.

[5]  Gasper Tkacik,et al.  Local statistics in natural scenes predict the saliency of synthetic textures , 2010, Proceedings of the National Academy of Sciences.

[6]  Charles P. Ratliff,et al.  Retina is structured to process an excess of darkness in natural scenes , 2010, Proceedings of the National Academy of Sciences.

[7]  Gasper Tkacik,et al.  Optimal population coding by noisy spiking neurons , 2010, Proceedings of the National Academy of Sciences.

[8]  Fred Rieke,et al.  Review the Challenges Natural Images Pose for Visual Adaptation , 2022 .

[9]  Vijay Balasubramanian,et al.  Receptive fields and functional architecture in the retina , 2009, The Journal of physiology.

[10]  A. Fairhall,et al.  Timescales of Inference in Visual Adaptation , 2009, Neuron.

[11]  B. Vijay What is the "contrast" in contrast adaptation? , 2009 .

[12]  Kolia Siamack Sadeghi,et al.  Progress on deciphering the retinal code , 2009 .

[13]  T. Hosoya,et al.  Estimating Receptive Fields from Responses to Natural Stimuli with Asymmetric Intensity Distributions , 2008, PloS one.

[14]  Eero P. Simoncelli,et al.  Spatio-temporal correlations and visual signalling in a complete neuronal population , 2008, Nature.

[15]  W. Geisler Visual perception and the statistical properties of natural scenes. , 2008, Annual review of psychology.

[16]  Michael J. Berry,et al.  Sophisticated temporal pattern recognition in retinal ganglion cells. , 2008, Journal of neurophysiology.

[17]  Ron Meir,et al.  Selective Adaptation in Networks of Heterogeneous Populations: Model, Simulation, and Experiment , 2008, PLoS Comput. Biol..

[18]  Stephen A. Baccus,et al.  Retinal Adaptation to Object Motion , 2007, Neuron.

[19]  A. Fairhall,et al.  Sensory adaptation , 2007, Current Opinion in Neurobiology.

[20]  Pamela Reinagel,et al.  Benefits of Contrast Normalization Demonstrated in Neurons and Model Cells , 2007, The Journal of Neuroscience.

[21]  B. Borghuis,et al.  Cellular Basis for Contrast Gain Control over the Receptive Field Center of Mammalian Retinal Ganglion Cells , 2007, The Journal of Neuroscience.

[22]  Michael J. Berry,et al.  Selectivity for multiple stimulus features in retinal ganglion cells. , 2006, Journal of neurophysiology.

[23]  Eero P. Simoncelli,et al.  Spike-triggered neural characterization. , 2006, Journal of vision.

[24]  M. Carandini,et al.  The Statistical Computation Underlying Contrast Gain Control , 2006, The Journal of Neuroscience.

[25]  Michael J. Berry,et al.  Functional organization of ganglion cells in the salamander retina. , 2006, Journal of neurophysiology.

[26]  Robert A. Frazor,et al.  Independence of luminance and contrast in natural scenes and in the early visual system , 2005, Nature Neuroscience.

[27]  M. Meister,et al.  Dynamic predictive coding by the retina , 2005, Nature.

[28]  Michael J. Berry,et al.  Redundancy in the Population Code of the Retina , 2005, Neuron.

[29]  W. Bialek,et al.  Features and dimensions: Motion estimation in fly vision , 2005, q-bio/0505003.

[30]  H. Sompolinsky,et al.  Adaptation without parameter change: Dynamic gain control in motion detection , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[31]  M. Landy,et al.  A visual mechanism tuned to black , 2004, Vision Research.

[32]  I. Nelken,et al.  Multiple Time Scales of Adaptation in Auditory Cortex Neurons , 2004, The Journal of Neuroscience.

[33]  Michael J. Berry,et al.  Recording spikes from a large fraction of the ganglion cells in a retinal patch , 2004, Nature Neuroscience.

[34]  William Bialek,et al.  Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions , 2002, Neural Computation.

[35]  Eero P. Simoncelli,et al.  A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.

[36]  Adrienne L. Fairhall,et al.  What Causes a Neuron to Spike? , 2003, Neural Computation.

[37]  E. Chichilnisky,et al.  Adaptation to Temporal Contrast in Primate and Salamander Retina , 2001, The Journal of Neuroscience.

[38]  Adrienne L. Fairhall,et al.  Efficiency and ambiguity in an adaptive neural code , 2001, Nature.

[39]  R. Reid,et al.  Predicting Every Spike A Model for the Responses of Visual Neurons , 2001, Neuron.

[40]  Eero P. Simoncelli,et al.  Natural image statistics and neural representation. , 2001, Annual review of neuroscience.

[41]  William Bialek,et al.  Adaptive Rescaling Maximizes Information Transmission , 2000, Neuron.

[42]  P. Lennie,et al.  Rapid adaptation in visual cortex to the structure of images. , 1999, Science.

[43]  Michael J. Berry,et al.  Adaptation of retinal processing to image contrast and spatial scale , 1997, Nature.

[44]  H. Markram,et al.  The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[45]  L. Abbott,et al.  Synaptic Depression and Cortical Gain Control , 1997, Science.

[46]  William Bialek,et al.  Entropy and Information in Neural Spike Trains , 1996, cond-mat/9603127.

[47]  Markus Meister,et al.  Multi-neuronal signals from the retina: acquisition and analysis , 1994, Journal of Neuroscience Methods.

[48]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[49]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[50]  J. Victor The dynamics of the cat retinal X cell centre. , 1987, The Journal of physiology.

[51]  C. Enroth-Cugell,et al.  Chapter 9 Visual adaptation and retinal gain controls , 1984 .

[52]  S. Laughlin,et al.  Predictive coding: a fresh view of inhibition in the retina , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[53]  S. Laughlin A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.

[54]  R. Shapley,et al.  The contrast gain control of the cat retina , 1979, Vision Research.

[55]  C F Stevens,et al.  A mechanism for spike frequency adaptation , 1976, The Journal of physiology.

[56]  F. Attneave Some informational aspects of visual perception. , 1954, Psychological review.

[57]  E. D. Adrian,et al.  The Basis of Sensation , 1928, The Indian Medical Gazette.