scholarly journals Visual Information flow in Wilson-Cowan networks

2020 ◽  
Author(s):  
Alexander Gomez Villa ◽  
Marcelo Bertalmío ◽  
Jesus Malo
Keyword(s):  
Image Coding ◽  
Visual Information ◽  
Luminance Contrast ◽  
Natural Scenes ◽  
Local Contrast ◽  
Visual Responses ◽  
Cortical Model ◽  
Efficient Coding ◽  
Total Correlation ◽  
Divisive Normalization

In this work we study the communication efficiency of a psychophysically-tuned cascade of Wilson-Cowan and Divisive Normalization layers that simulate the retina-V1 pathway. This is the first analysis of Wilson-Cowan networks in terms of multivariate total correlation. The parameters of the cortical model have been derived through the relation between the steady state of the Wilson-Cowan model and the Divisive Normalization model.Efficiency has been analyzed in two ways: First, we provide an analytical expression for the reduction of the total correlation among the responses of a V1-like population after the Wilson-Cowan interaction. Second, we empirically study the efficiency with visual stimuli and statistical tools that were not available before: (1) a recent, radiometrically calibrated, set of natural scenes, and (2) a recent technique to estimate the multivariate total correlation in bits from sets of visual responses which only involves univariate operations, thus giving better redundancy estimates.The theoretical and the empirical results show that although this cascade of layers was not optimized for statistical independence in any way, the redundancy between the responses gets substantially reduced along the pathway. Specifically, we show that (1) the efficiency of a Wilson-Cowan network is similar to its equivalent Divisive Normalization, (2) while initial layers (Von-Kries adaptation and Weber-like brightness) contribute to univariate equalization, the bigger contributions to the reduction in total correlation come from the nonlinear local contrast and the local oriented filters, and (3) psychophysically-tuned models are more efficient in the more populated regions of the luminance-contrast plane. These results are an alternative confirmation of the Efficient Coding Hypothesis for the Wilson-Cowan systems. And from an applied perspective, they suggest that neural field models could be an option in image coding to perform image compression.

scholarly journals Visual Discomfort and Variations in Chromaticity in Art and Nature

2021 ◽  
Vol 15 ◽  
Author(s):  
Olivier Penacchio ◽  
Sarah M. Haigh ◽  
Xortia Ross ◽  
Rebecca Ferguson ◽  
Arnold J. Wilkins
Keyword(s):  
Good Predictor ◽  
Luminance Contrast ◽  
Visual Ecology ◽  
Visual Images ◽  
Natural Scenes ◽  
Statistical Regularity ◽  
Metabolic Demand ◽  
Visual Discomfort ◽  
Efficient Coding ◽  
Natural Stimuli

Visual discomfort is related to the statistical regularity of visual images. The contribution of luminance contrast to visual discomfort is well understood and can be framed in terms of a theory of efficient coding of natural stimuli, and linked to metabolic demand. While color is important in our interaction with nature, the effect of color on visual discomfort has received less attention. In this study, we build on the established association between visual discomfort and differences in chromaticity across space. We average the local differences in chromaticity in an image and show that this average is a good predictor of visual discomfort from the image. It accounts for part of the variance left unexplained by variations in luminance. We show that the local chromaticity difference in uncomfortable stimuli is high compared to that typical in natural scenes, except in particular infrequent conditions such as the arrangement of colorful fruits against foliage. Overall, our study discloses a new link between visual ecology and discomfort whereby discomfort arises when adaptive perceptual mechanisms are overstimulated by specific classes of stimuli rarely found in nature.

scholarly journals Spatio-chromatic information available from different neural layers via Gaussianization

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jesús Malo
Keyword(s):  
Visual Information ◽  
Dynamic Range ◽  
Natural Images ◽  
Natural Scenes ◽  
Spatial Filters ◽  
Statistical Tool ◽  
Information Theoretic ◽  
Transmitted Information ◽  
Total Correlation ◽  
Optimal Information

Abstract How much visual information about the retinal images can be extracted from the different layers of the visual pathway? This question depends on the complexity of the visual input, the set of transforms applied to this multivariate input, and the noise of the sensors in the considered layer. Separate subsystems (e.g. opponent channels, spatial filters, nonlinearities of the texture sensors) have been suggested to be organized for optimal information transmission. However, the efficiency of these different layers has not been measured when they operate together on colorimetrically calibrated natural images and using multivariate information-theoretic units over the joint spatio-chromatic array of responses. In this work, we present a statistical tool to address this question in an appropriate (multivariate) way. Specifically, we propose an empirical estimate of the information transmitted by the system based on a recent Gaussianization technique. The total correlation measured using the proposed estimator is consistent with predictions based on the analytical Jacobian of a standard spatio-chromatic model of the retina–cortex pathway. If the noise at certain representation is proportional to the dynamic range of the response, and one assumes sensors of equivalent noise level, then transmitted information shows the following trends: (1) progressively deeper representations are better in terms of the amount of captured information, (2) the transmitted information up to the cortical representation follows the probability of natural scenes over the chromatic and achromatic dimensions of the stimulus space, (3) the contribution of spatial transforms to capture visual information is substantially greater than the contribution of chromatic transforms, and (4) nonlinearities of the responses contribute substantially to the transmitted information but less than the linear transforms.

scholarly journals The emergence of multiple retinal cell types through efficient coding of natural movies

2018 ◽  
Author(s):  
Samuel A. Ocko ◽  
Jack Lindsey ◽  
Surya Ganguli ◽  
Stephane Deny
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Ganglion Cells ◽  
Receptive Fields ◽  
Cell Types ◽  
Retinal Cell ◽  
Retinal Eccentricity ◽  
Natural Scenes ◽  
Efficient Coding ◽  
Cell Densities

AbstractOne of the most striking aspects of early visual processing in the retina is the immediate parcellation of visual information into multiple parallel pathways, formed by different retinal ganglion cell types each tiling the entire visual field. Existing theories of efficient coding have been unable to account for the functional advantages of such cell-type diversity in encoding natural scenes. Here we go beyond previous theories to analyze how a simple linear retinal encoding model with different convolutional cell types efficiently encodes naturalistic spatiotemporal movies given a fixed firing rate budget. We find that optimizing the receptive fields and cell densities of two cell types makes them match the properties of the two main cell types in the primate retina, midget and parasol cells, in terms of spatial and temporal sensitivity, cell spacing, and their relative ratio. Moreover, our theory gives a precise account of how the ratio of midget to parasol cells decreases with retinal eccentricity. Also, we train a nonlinear encoding model with a rectifying nonlinearity to efficiently encode naturalistic movies, and again find emergent receptive fields resembling those of midget and parasol cells that are now further subdivided into ON and OFF types. Thus our work provides a theoretical justification, based on the efficient coding of natural movies, for the existence of the four most dominant cell types in the primate retina that together comprise 70% of all ganglion cells.

scholarly journals The threshold of binocularity: natural image statistics explain the reduction of visual acuity in peripheral vision

2017 ◽  
Author(s):  
David W. Hunter ◽  
Paul B. Hibbard
Keyword(s):  
Visual Acuity ◽  
Visual Cortex ◽  
Visual Processing ◽  
Visual Information ◽  
Peripheral Vision ◽  
Visual Performance ◽  
Natural Image ◽  
Natural Scenes ◽  
Natural Image Statistics ◽  
Efficient Coding

AbstractVisual acuity is greatest in the centre of the visual field, peaking in the fovea and degrading significantly towards the periphery. The rate of decay of visual performance with eccentricity depends strongly on the stimuli and task used in measurement. While detailed measures of this decay have been made across a broad range of tasks, a comprehensive theoretical account of this phenomenon is lacking. We demonstrate that the decay in visual performance can be attributed to the efficient encoding of binocular information in natural scenes. The efficient coding hypothesis holds that the early stages of visual processing attempt to form an efficient coding of ecologically valid stimuli. Using Independent Component Analysis to learn an efficient coding of stereoscopic images, we show that the ratio of binocular to monocular components varied with eccentricity at the same rate as human stereo acuity and Vernier acuity. Our results demonstrate that the organisation of the visual cortex is dependent on the underlying statistics of binocular scenes and, strikingly, that monocular acuity depends on the mechanisms by which the visual cortex processes binocular information. This result has important theoretical implications for understanding the encoding of visual information in the brain.

Responses of cells in the tail of the caudate nucleus during visual discrimination learning

1995 ◽  
Vol 74 (3) ◽  
pp. 1083-1094 ◽  
Author(s):  
V. J. Brown ◽  
R. Desimone ◽  
M. Mishkin
Keyword(s):  
Caudate Nucleus ◽  
Visual Discrimination ◽  
Visual Information ◽  
Visual Learning ◽  
Visual Fields ◽  
Receptive Fields ◽  
Visual Responses ◽  
Neuronal Responses ◽  
Association Learning ◽  
Visual Properties

1. The tail of the caudate nucleus and adjacent ventral putamen (ventrocaudal neostriatum) are major projection sites of the extrastriate visual cortex. Visual information is then relayed, directly or indirectly, to a variety of structures with motor functions. To test for a role of the ventrocaudal neostriatum in stimulus-response association learning, or habit formation, neuronal responses were recorded while monkeys performed a visual discrimination task. Additional data were collected from cells in cortical area TF, which serve as a comparison and control for the caudate data. 2. Two monkeys were trained to perform an asymmetrically reinforced go-no go visual discrimination. The stimuli were complex colored patterns, randomly assigned to be either positive or negative. The monkey was rewarded with juice for releasing a bar when a positive stimulus was presented, whereas a negative stimulus signaled that no reward was available and that the monkey should withhold its response. Neuronal responses were recorded both while the monkey performed the task with previously learned stimuli and while it learned the task with new stimuli. In some cases, responses were recorded during reversal learning. 3. There was no evidence that cells in the ventrocaudal neostriatum were influenced by the reward contingencies of the task. Cells did not fire preferentially to the onset of either positive or negative stimuli; neither did cells fire in response to the reward itself or in association with the motor response of the monkey. Only visual responses were apparent. 4. The visual properties of cells in these structures resembled those of cells in some of the cortical areas projecting to them. Most cells responded selectively to different visual stimuli. The degree of stimulus selectivity was assessed with discriminant analysis and was found to be quantitatively similar to that of inferior temporal cells tested with similar stimuli. Likewise, like inferior temporal cells, many cells in the ventrocaudal neostriatum had large, bilateral receptive fields. Some cells had "doughnut"-shaped receptive fields, with stronger responses in the periphery of both visual fields than at the fovea, similar to the fields of some cells in the superior temporal polysensory area. Although the absence of task-specific responses argues that ventrocaudal neostriatal cells are not themselves the mediators of visual learning in the task employed, their cortical-like visual properties suggest that they might relay visual information important for visuomotor plasticity in other structures. (ABSTRACT TRUNCATED AT 400 WORDS)

A collicular visual cortex: Neocortical space for an ancient midbrain visual structure

Science ◽  
2019 ◽  
Vol 363 (6422) ◽  
pp. 64-69 ◽  
Author(s):  
Riccardo Beltramo ◽  
Massimo Scanziani
Keyword(s):  
Cerebral Cortex ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Cortical Area ◽  
Moving Objects ◽  
Visual Responses ◽  
Visual Cortical Area ◽  
Postrhinal Cortex ◽  
Visual Cortical

Visual responses in the cerebral cortex are believed to rely on the geniculate input to the primary visual cortex (V1). Indeed, V1 lesions substantially reduce visual responses throughout the cortex. Visual information enters the cortex also through the superior colliculus (SC), but the function of this input on visual responses in the cortex is less clear. SC lesions affect cortical visual responses less than V1 lesions, and no visual cortical area appears to entirely rely on SC inputs. We show that visual responses in a mouse lateral visual cortical area called the postrhinal cortex are independent of V1 and are abolished upon silencing of the SC. This area outperforms V1 in discriminating moving objects. We thus identify a collicular primary visual cortex that is independent of the geniculo-cortical pathway and is capable of motion discrimination.

Lateral geniculate neurons in behaving primates. I. Responses to two-dimensional stimuli

1991 ◽  
Vol 66 (3) ◽  
pp. 777-793 ◽  
Author(s):  
J. W. McClurkin ◽  
T. J. Gawne ◽  
B. J. Richmond ◽  
L. M. Optican ◽  
D. L. Robinson
Keyword(s):  
Receptive Field ◽  
Visual Information ◽  
Receptive Fields ◽  
Nonlinear Behavior ◽  
Temporal Patterns ◽  
Two Dimensional ◽  
Visual Responses ◽  
Linear Summation ◽  
Lateral Geniculate ◽  
Opposite Contrast

1. Using behaving monkeys, we studied the visual responses of single neurons in the parvocellular layers of the lateral geniculate nucleus (LGN) to a set of two-dimensional black and white patterns. We found that monkeys could be trained to make sufficiently reliable and stable fixations to enable us to plot and characterize the receptive fields of individual neurons. A qualitative examination of rasters and a statistical analysis of the data revealed that the responses of neurons were related to the stimuli. 2. The data from 5 of the 13 "X-like" neurons in our sample indicated the presence of antagonistic center and surround mechanisms and linear summation of luminance within center and surround mechanisms. We attribute the lack of evidence for surround antagonism in the eight neurons that failed to exhibit center-surround antagonism either to a mismatch between the size of the pixels in the stimuli and the size of the receptive field or to the lack of a surround mechanism (i.e., the type II neurons of Wiesel and Hubel). 3. The data from five other neurons confirm and extend previous reports indicating that the surround regions of X-like neurons can have nonlinearities. The responses of these neurons were not modulated when a contrast-reversing, bipartite stimulus was centered on the receptive field, which suggests a linear summation within the center and surround mechanisms. However, it was frequently the case for these neurons that stimuli of identical pattern but opposite contrast elicited responses of similar polarity, which indicates nonlinear behavior. 4. We found a wide variety of temporal patterns in the responses of individual LGN neurons, which included differences in the magnitude, width, and number of peaks of the initial on-transient and in the magnitude of the later sustained component. These different temporal patterns were repeatable and clearly different for different visual patterns. These results suggest that visual information may be carried in the shape as well as in the amplitude of the response waveform.

Dependency Reduction with Divisive Normalization: Justification and Effectiveness

2011 ◽  
Vol 23 (11) ◽  
pp. 2942-2973 ◽  
Author(s):  
Siwei Lyu
Keyword(s):  
Quantitative Evaluation ◽  
Statistical Properties ◽  
Theoretical Justification ◽  
Low Input ◽  
Efficient Coding ◽  
Sensory Signals ◽  
Divisive Normalization ◽  
Multivariate T

Efficient coding transforms that reduce or remove statistical dependencies in natural sensory signals are important for both biology and engineering. In recent years, divisive normalization (DN) has been advocated as a simple and effective nonlinear efficient coding transform. In this work, we first elaborate on the theoretical justification for DN as an efficient coding transform. Specifically, we use the multivariate t model to represent several important statistical properties of natural sensory signals and show that DN approximates the optimal transforms that eliminate statistical dependencies in the multivariate t model. Second, we show that several forms of DN used in the literature are equivalent in their effects as efficient coding transforms. Third, we provide a quantitative evaluation of the overall dependency reduction performance of DN for both the multivariate t models and natural sensory signals. Finally, we find that statistical dependencies in the multivariate t model and natural sensory signals are increased by the DN transform with low-input dimensions. This implies that for DN to be an effective efficient coding transform, it has to pool over a sufficiently large number of inputs.

The use of visual information in natural scenes

2005 ◽  
Vol 12 (6) ◽  
pp. 938-953 ◽  
Author(s):  
Maxine McCotter ◽  
Frederic Gosselin ◽  
Paul Sowden ◽  
Philippe Schyns
Keyword(s):  
Visual Information ◽  
Natural Scenes
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