scholarly journals Reconstruction of natural images from responses of primate retinal ganglion cells

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Nora Brackbill ◽  
Colleen Rhoades ◽  
Alexandra Kling ◽  
Nishal P Shah ◽  
Alexander Sher ◽  
...  
Keyword(s):  
Receptive Field ◽  
Ganglion Cells ◽  
Natural Images ◽  
Natural Image ◽  
Retinal Ganglion ◽  
Natural Image Statistics ◽  
Image Statistics ◽  
Visual Message ◽  
Spatial Properties ◽  
Reconstruction Filter

The visual message conveyed by a retinal ganglion cell (RGC) is often summarized by its spatial receptive field, but in principle also depends on the responses of other RGCs and natural image statistics. This possibility was explored by linear reconstruction of natural images from responses of the four numerically-dominant macaque RGC types. Reconstructions were highly consistent across retinas. The optimal reconstruction filter for each RGC – its visual message – reflected natural image statistics, and resembled the receptive field only when nearby, same-type cells were included. ON and OFF cells conveyed largely independent, complementary representations, and parasol and midget cells conveyed distinct features. Correlated activity and nonlinearities had statistically significant but minor effects on reconstruction. Simulated reconstructions, using linear-nonlinear cascade models of RGC light responses that incorporated measured spatial properties and nonlinearities, produced similar results. Spatiotemporal reconstructions exhibited similar spatial properties, suggesting that the results are relevant for natural vision.

scholarly journals Reconstruction of natural images from responses of primate retinal ganglion cells

2020 ◽  
Author(s):  
Nora Brackbill ◽  
Colleen Rhoades ◽  
Alexandra Kling ◽  
Nishal P. Shah ◽  
Alexander Sher ◽  
...  
Keyword(s):  
Receptive Field ◽  
Ganglion Cells ◽  
Natural Images ◽  
Natural Image ◽  
Retinal Ganglion ◽  
Natural Image Statistics ◽  
Image Statistics ◽  
Visual Message ◽  
Spatial Properties ◽  
Reconstruction Filter

AbstractThe visual message conveyed by a retinal ganglion cell (RGC) is often summarized by its spatial receptive field, but in principle also depends on the responses of other RGCs and natural image statistics. This possibility was explored by linear reconstruction of natural images from responses of the four numerically-dominant macaque RGC types. Reconstructions were highly consistent across retinas. The optimal reconstruction filter for each RGC – its visual message – reflected natural image statistics, and resembled the receptive field only when nearby, same-type cells were included. ON and OFF cells conveyed largely independent, complementary representations, and parasol and midget cells conveyed distinct and expected features. Correlated activity and nonlinearities had statistically significant but minor effects on reconstruction. Simulated reconstructions, using linear-nonlinear cascade models of RGC light responses that incorporated measured spatial properties and nonlinearities, produced similar results. Spatiotemporal reconstructions exhibited similar spatial properties, suggesting that the results are relevant for natural vision.

scholarly journals Neural Sensitivity to Natural Image Statistics Changes during Middle Childhood

2020 ◽  
Author(s):  
Benjamin Balas ◽  
Alyson Saville
Keyword(s):  
Middle Childhood ◽  
Visual Processing ◽  
Event Related Potentials ◽  
Developmental Trajectory ◽  
Natural Images ◽  
Natural Image ◽  
Natural Image Statistics ◽  
Image Perception ◽  
Image Statistics ◽  
Related Potentials

AbstractNatural images have lawful statistical properties that the adult visual system is sensitive to, both in terms of behavior and neural responses to natural images. The developmental trajectory of sensitivity to natural image statistics remains unclear, however. In behavioral tasks, children appear to slowly acquire adult-like sensitivity to natural image statistics during middle childhood (Ellemberg et al., 2012), but in other tasks, infants exhibit some sensitivity to deviations of natural image structure (Balas & Woods, 2014). Here, we used event-related potentials (ERPs) to examine how sensitivity to natural image statistics changes during childhood at distinct stages of visual processing (the P1 and N1 components). We asked children (5-10 years old) and adults to view natural texture images with either positive/negative contrast, and natural/synthetic texture appearance (Portilla & Simoncelli, 2000) to compare electrophysiological responses to images that did or did not violate natural statistics. We hypothesized that children may only acquire sensitivity to these deviations from natural texture appearance late in middle childhood. Counter to this hypothesis, we observed significant responses to unnatural contrast and texture statistics at the N1 in all age groups. At the P1, however, only young children exhibited sensitivity to contrast polarity. The latter effect suggests greater sensitivity earlier in development to some violations of natural image statistics. We discuss these results in terms of changing patterns of invariant texture processing during middle childhood and ongoing refinement of the representations supporting natural image perception.

scholarly journals The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images

2017 ◽  
Vol 29 (10) ◽  
pp. 2769-2799 ◽  
Author(s):  
P. N. Loxley
Keyword(s):  
Receptive Field ◽  
Spatial Frequency ◽  
Generative Model ◽  
Natural Image ◽  
Two Dimensional ◽  
Natural Image Statistics ◽  
Image Statistics ◽  
Gabor Function ◽  
Gabor Functions ◽  
Probabilistic Generative Model

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

scholarly journals Two-Dimensional Hermite Filters Simplify the Description of High-Order Statistics of Natural Images

2016 ◽  
Author(s):  
Qin Hu ◽  
Jonathan Victor
Keyword(s):  
Order Statistics ◽  
Dimensional Subspace ◽  
High Order ◽  
Natural Images ◽  
Natural Image ◽  
Two Dimensional ◽  
Natural Image Statistics ◽  
Image Statistics ◽  
High Order Statistics ◽  
Orthogonal Set

AbstractNatural image statistics play a crucial role in shaping biological visual systems, understanding their function and design principles, and designing effective computer-vision algorithms. High-order statistics are critical for conveying local features, but they are challenging to study – largely because their number and variety is large. Here, via the use of two-dimensional Hermite (TDH) functions, we identify a covert symmetry in high-order statistics of natural images that simplifies this task. This emerges from the structure of TDH functions, which are an orthogonal set of functions that are organized into a hierarchy of ranks. Specifically, we find that the shape (skewness and kurtosis) of the distribution of filter coefficients depends only on the projection of the function onto a 1-dimensional subspace specific to each rank. The characterization of natural image statistics provided by TDH filter coefficients reflects both their phase and amplitude structure, and we suggest an intuitive interpretation for the special subspace within each rank.

scholarly journals Simple Model for Encoding Natural Images by Retinal Ganglion Cells with Nonlinear Spatial Integration

2021 ◽  
Author(s):  
Jian K. Liu ◽  
Tim Gollisch
Keyword(s):  
Receptive Field ◽  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Weighted Average ◽  
Natural Images ◽  
Simple Extension ◽  
Retinal Ganglion ◽  
Spatial Integration ◽  
Model Framework ◽  
Standard Models

A central goal in sensory neuroscience is to understand the neuronal signal processing involved in the encoding of natural stimuli. A critical step towards this goal is the development of successful computational models of this encoding. For ganglion cells in the vertebrate retina, the development of satisfactory models for responses to natural visual scenes is an ongoing challenge. Standard models typically apply linear integration of visual stimuli over space, yet many ganglion cells are known to show nonlinear spatial integration in natural stimulus contexts. We here study the encoding of natural images by retinal ganglion cells, using multielectrode-array recordings from isolated salamander retinas. We assess how responses to natural and blurred images depend on first- and second-order statistics of spatial patterns inside the receptive field. This leads us to a simple extension of current standard ganglion cell models, which are based on linear spatial integration. We show that taking not only the weighted average of light intensity inside the receptive field into account but also its variance over space yields substantially improved response predictions of responses to novel images. Finally, we demonstrate how this model framework can be used to assess the spatial scale of nonlinear spatial integration. Our results underscore the importance of nonlinear spatial stimulus integration in the retina in responses to natural images. Furthermore, the introduced model framework provides a simple, yet powerful extension of standard models and may serve as a benchmark for the development of more detailed models of the nonlinear structure of receptive fields.

scholarly journals Redundancy between spectral and higher-order texture statistics for natural image segmentation

2021 ◽  
Author(s):  
Daniel Herrera-Esposito ◽  
Leonel Gomez-Sena ◽  
Ruben Coen-Cagli
Keyword(s):  
Image Segmentation ◽  
Peripheral Vision ◽  
Higher Order ◽  
Natural Images ◽  
Natural Image ◽  
Natural Image Statistics ◽  
Image Statistics ◽  
Texture Model ◽  
Spectral Statistics ◽  
Perceptual Segmentation

Visual texture, defined by local image statistics, provides important information to the human visual system for perceptual segmentation. Second-order or spectral statistics (equivalent to the Fourier power spectrum) are a well-studied segmentation cue. However, the role of higher-order statistics (HOS) in segmentation remains unclear, particularly for natural images. Recent experiments indicate that, in peripheral vision, the HOS of the widely adopted Portilla-Simoncelli texture model are a weak segmentation cue compared to spectral statistics, despite the fact that both are necessary to explain other perceptual phenomena and to support high-quality texture synthesis. Here we test whether this discrepancy reflects a property of natural image statistics. First, we observe that differences in spectral statistics across segments of natural images are redundant with differences in HOS. Second, using linear and nonlinear classifiers, we show that each set of statistics individually affords high performance in natural scenes and texture segmentation tasks, but combining spectral statistics and HOS produces relatively small improvements. Third, we find that HOS improve segmentation for a subset of images, although these images are difficult to identify. We also find that different subsets of HOS improve segmentation to a different extent, in agreement with previous physiological and perceptual work. These results show that the HOS add modestly to spectral statistics for natural image segmentation. We speculate that tuning to natural image statistics under resource constraints could explain the weak contribution of HOS to perceptual segmentation in human peripheral vision.

scholarly journals Spatial receptive field properties of rat retinal ganglion cells

2011 ◽  
Vol 28 (5) ◽  
pp. 403-417 ◽  
Author(s):  
WALTER F. HEINE ◽  
CHRISTOPHER L. PASSAGLIA
Keyword(s):  
Receptive Field ◽  
Ganglion Cell ◽  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Cell Types ◽  
Quantitative Information ◽  
Retinal Ganglion ◽  
X And Y Cells ◽  
Y Cells

AbstractThe rat is a popular animal model for vision research, yet there is little quantitative information about the physiological properties of the cells that provide its brain with visual input, the retinal ganglion cells. It is not clear whether rats even possess the full complement of ganglion cell types found in other mammals. Since such information is important for evaluating rodent models of visual disease and elucidating the function of homologous and heterologous cells in different animals, we recorded from rat ganglion cells in vivo and systematically measured their spatial receptive field (RF) properties using spot, annulus, and grating patterns. Most of the recorded cells bore likeness to cat X and Y cells, exhibiting brisk responses, center-surround RFs, and linear or nonlinear spatial summation. The others resembled various types of mammalian W cell, including local-edge-detector cells, suppressed-by-contrast cells, and an unusual type with an ON–OFF surround. They generally exhibited sluggish responses, larger RFs, and lower responsiveness. The peak responsivity of brisk-nonlinear (Y-type) cells was around twice that of brisk-linear (X-type) cells and several fold that of sluggish cells. The RF size of brisk-linear and brisk-nonlinear cells was indistinguishable, with average center and surround diameters of 5.6 ± 1.3 and 26.4 ± 11.3 deg, respectively. In contrast, the center diameter of recorded sluggish cells averaged 12.8 ± 7.9 deg. The homogeneous RF size of rat brisk cells is unlike that of cat X and Y cells, and its implication regarding the putative roles of these two ganglion cell types in visual signaling is discussed.

scholarly journals Bicycronic construct for optogenetic prosthesis of ganglion cell receptive field of degenerated retina

2019 ◽  
Vol 486 (2) ◽  
pp. 258-261
Author(s):  
L. E. Petrovskaya ◽  
M. V. Roshchin ◽  
G. R. Smirnova ◽  
D. E. Kolotova ◽  
P. M. Balaban ◽  
...  
Keyword(s):  
Receptive Field ◽  
Ganglion Cell ◽  
Retinal Ganglion Cell ◽  
Distinctive Feature ◽  
Action Potentials ◽  
Ganglion Cells ◽  
Retinal Ganglion ◽  
Light Stimulation ◽  
Genetic Construct ◽  
Stimulation Of

For the purpose of optogenetic prosthetics of the receptive field of the retinal ganglion cell, we have created a bicistronic genetic construct that carries genes of excitatory (channelorhodopsin2) and inhibitory (anionic channelorhodopsin) rhodopsins. A distinctive feature of this construct is the combination of two genes into one construct with the mutant IRES inserted between them, which ensures precise ratio of the expression levels of the first and second gene in each transfected cell. It was found that the illumination of the central part of transfected neuron with light with a wavelength of 470 nm causes the generation of action potentials in the cell. At the same time, light stimulation of the periphery of the neuron causes cessation of the generation of action potentials. Thus, we were able to simulate the ON-OFF interaction of the receptive field of the retinal ganglion cell using optogenetic methods. Theoretically, this construction can be used for optogenetic prosthetics of degenerative retina in case of its delivery to ganglion cells using lentiviral vectors.

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