Cell Receptive Fields Research Articles

Realistic Mathematical Model of Retinal Outer Plexiform Layer for Edge Detection.

Edge information is essential for object recognition and motion detection. It is reported that photoreceptors, horizontal cells and bipolar cells in the outer retina involved for edge detection. Moreover, it is known that the center and the surround receptive field structure found in the bipolar cell layer is thought to be related to an initial process of edge detection. In the present study, we constructed retinal network models including photoreceptors, horizontal cells, and bipolar cells using single-compartment neurons to investigate those contributions for edge detection. We simulate fixation of a natural image with changing the size of the horizontal cell receptive field and confirmed that the constructed model successfully extracts edges in the image. Furthermore, most of the edge in the scene is extracted when the size of the horizontal cell receptive field matched with that reported in anatomical evidence. To evaluate the performance of edge detection, we compare the result of edge detection with the Canny algorithm. As a result, we conformed that the model well detects fine edges similar to the Canny edge detection.

Glycinergic and GABAergic interneurons shift the location and differentially alter the size of ganglion cell receptive field centers in the mammalian retina

By using the multi-electrode array (MEA) recording technique in conjunction with white-noise checkerboard stimuli and reverse correlation methods, we studied modulatory actions of glycinergic and GABAergic interneurons on spatiotemporal profiles of ganglion cells (GCs) in dark-adapted mouse retinas. We found that application of 2 µM strychnine decreased receptive field center radii of GCs by a mean value of 11%, and shifted the GC receptive field (RF) centers by a mean distance of 28.3 µm. On the other hand, 200 µM picrotoxin + 100 µM bicuculline + 50 µM TPMPA increased GC receptive field center radii by a mean value of 19%, and shifted the GC RF centers by a mean distance of 53.7 µm. Glycinergic neurons in the mouse retina are narrow-field amacrine cells that have been shown to mediate ON-OFF crossover inhibitory synapses within the RGs’ RF center, therefore they may increase the size and shift the location of GC RF center by synergistic addition to bipolar cell inputs to GCs. GABAergic neurons are wide-field amacrine cells and horizontal cells that are known to mediate antagonistic surround responses of GCs, and thus they decrease the GCs’ RF center size. Our results suggest that a major global function of glycinergic and GABAergic interneurons in the mammalian retina is to provide the flexibility for adjusting the size and location of GCs’ RF centers. The apparent shifts of GC RF centers suggest that the synergistic addition by GlyACs and the surround inhibition by GABAergic interneurons are not spatially symmetrical within GC RFs.

Adaptation to Binocular Anticorrelation Results in Increased Neural Excitability.

Throughout the brain, information from individual sources converges onto higher order neurons. For example, information from the two eyes first converges in binocular neurons in area V1. Some neurons are tuned to similarities between sources of information, which makes intuitive sense in a system striving to match multiple sensory signals to a single external cause-that is, establish causal inference. However, there are also neurons that are tuned to dissimilar information. In particular, some binocular neurons respond maximally to a dark feature in one eye and a light feature in the other. Despite compelling neurophysiological and behavioral evidence supporting the existence of these neurons [Katyal, S., Vergeer, M., He, S., He, B., & Engel, S. A. Conflict-sensitive neurons gate interocular suppression in human visual cortex. Scientific Reports, 8, 1239, 2018; Kingdom, F. A. A., Jennings, B. J., & Georgeson, M. A. Adaptation to interocular difference. Journal of Vision, 18, 9, 2018; Janssen, P., Vogels, R., Liu, Y., & Orban, G. A. At least at the level of inferior temporal cortex, the stereo correspondence problem is solved. Neuron, 37, 693-701, 2003; Tsao, D. Y., Conway, B. R., & Livingstone, M. S. Receptive fields of disparity-tuned simple cells in macaque V1. Neuron, 38, 103-114, 2003; Cumming, B. G., & Parker, A. J. Responses of primary visual cortical neurons to binocular disparity without depth perception. Nature, 389, 280-283, 1997], their function has remained opaque. To determine how neural mechanisms tuned to dissimilarities support perception, here we use electroencephalography to measure human observers' steady-state visually evoked potentials in response to change in depth after prolonged viewing of anticorrelated and correlated random-dot stereograms (RDS). We find that adaptation to anticorrelated RDS results in larger steady-state visually evoked potentials, whereas adaptation to correlated RDS has no effect. These results are consistent with recent theoretical work suggesting "what not" neurons play a suppressive role in supporting stereopsis [Goncalves, N. R., & Welchman, A. E. "What not" detectors help the brain see in depth. Current Biology, 27, 1403-1412, 2017]; that is, selective adaptation of neurons tuned to binocular mismatches reduces suppression resulting in increased neural excitability.

Inhibitory components of retinal bipolar cell receptive fields are differentially modulated by dopamine D1 receptors.

During adaptation to an increase in environmental luminance, retinal signaling adjustments are mediated by the neuromodulator dopamine. Retinal dopamine is released with light and can affect center-surround receptive fields, the coupling state between neurons, and inhibitory pathways through inhibitory receptors and neurotransmitter release. While the inhibitory receptive field surround of bipolar cells becomes narrower and weaker during light adaptation, it is unknown how dopamine affects bipolar cell surrounds. If dopamine and light have similar effects, it would suggest that dopamine could be a mechanism for light-adapted changes. We tested the hypothesis that dopamine D1 receptor activation is sufficient to elicit the magnitude of light-adapted reductions in inhibitory bipolar cell surrounds. Surrounds were measured from OFF bipolar cells in dark-adapted mouse retinas while stimulating D1 receptors, which are located on bipolar, horizontal, and inhibitory amacrine cells. The D1 agonist SKF-38393 narrowed and weakened OFF bipolar cell inhibitory receptive fields but not to the same extent as with light adaptation. However, the receptive field surround reductions differed between the glycinergic and GABAergic components of the receptive field. GABAergic inhibitory strength was reduced only at the edges of the surround, while glycinergic inhibitory strength was reduced across the whole receptive field. These results expand the role of retinal dopamine to include modulation of bipolar cell receptive field surrounds. Additionally, our results suggest that D1 receptor pathways may be a mechanism for the light-adapted weakening of glycinergic surround inputs and the furthest wide-field GABAergic inputs to bipolar cells. However, remaining differences between light-adapted and D1 receptor-activated inhibition demonstrate that non-D1 receptor mechanisms are necessary to elicit the full effect of light adaptation on inhibitory surrounds.

Face Representations via Tensorfaces of Various Complexities.

Neurons selective for faces exist in humans and monkeys. However, characteristics of face cell receptive fields are poorly understood. In this theoretical study, we explore the effects of complexity, defined as algorithmic information (Kolmogorov complexity) and logical depth, on possible ways that face cells may be organized. We use tensor decompositions to decompose faces into a set of components, called tensorfaces, and their associated weights, which can be interpreted as model face cells and their firing rates. These tensorfaces form a high-dimensional representation space in which each tensorface forms an axis of the space. A distinctive feature of the decomposition algorithm is the ability to specify tensorface complexity. We found that low-complexity tensorfaces have blob-like appearances crudely approximating faces, while high-complexity tensorfaces appear clearly face-like. Low-complexity tensorfaces require a larger population to reach a criterion face reconstruction error than medium- or high-complexity tensorfaces, and thus are inefficient by that criterion. Low-complexity tensorfaces, however, generalize better when representing statistically novel faces, which are faces falling beyond the distribution of face description parameters found in the tensorface training set. The degree to which face representations are parts based or global forms a continuum as a function of tensorface complexity, with low and medium tensorfaces being more parts based. Given the computational load imposed in creating high-complexity face cells (in the form of algorithmic information and logical depth) and in the absence of a compelling advantage to using high-complexity cells, we suggest face representations consist of a mixture of low- and medium-complexity face cells.

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

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.

The Relationship Between the Photopic Negative Response and Retinal Ganglion Cell Topography.

To assess the topographic relationship between the photopic negative response (PhNR) and retinal ganglion cell distribution in healthy individuals. Data was recorded from 16 healthy participants. The amplitude of PhNRs obtained in response to focal long duration (250 ms) and brief flash (5 ms), red (660 nm) on blue (469 nm) stimuli of increasing size (5° - full field) were measured. The number of retinal ganglion cell receptive fields (RGCf) in each stimulus area was established from the literature and regression analysis used to determine the relationships between: PhNR amplitude and number of RGCfs stimulated, PhNR density and the RGCf density and response per RGCf as a function of eccentricity. The overall amplitude of the PhNR increased with stimulus size and the response density declined from ∼0.1 μV/deg in the macular region to ∼0.003 μV/deg approximately 45° from the fovea. Contrary to expectations, the relationship between the PhNR and number of RGCf was nonlinear, the response from more eccentric neurons being about three times greater than those in the macular region. Although the amplitude of the PhNR broadly maps on to the topographic distribution of RGCf the increase in PhNR amplitude with increasing eccentricity is only partly explained by RGCf numbers. Increases in the PhNR amplitude may be due to topographic variations in the contributions from other non-RGC neurons, as well as eccentricity-related morphologic and physiologic differences in RGCs.

Bicistronic Construct for Optogenetic Prosthesis of Ganglion Cell Receptive Field of Degenerative Retina.

To perform optogenetic prosthetics of the retinal ganglion cell receptive field, a bicistronic genetic construct carrying the genes encoding the excitatory (channelrhodopsin-2) and inhibitory (Guillardia thetaanion channelrhodopsin GtACR2) rhodopsins was created. A characteristic feature of this construct was the combination of these two genes with a mutant IRES insertion between them, which ensures the exact ratio of expression levels of the first and second genes in each transfected cell. Illumination of the central part of the neuron with light with a wavelength of 470 nm induced the action potential generation in the cell. Stimulation of the peripheral neuronal region with light induced the inhibition of action potential generation. Thus, using optogenetics methods, we simulated the ON-OFF interaction in the retinal ganglion cell receptive field. Theoretically, this construct can be used for optogenetic prosthetics of degenerative retina in the case of its delivery to the ganglion cells with lentiviral vectors.

Automatic skin lesion segmentation by coupling deep fully convolutional networks and shallow network with textons.

Segmentation of skin lesions is an important step in computer-aided diagnosis of melanoma; it is also a very challenging task due to fuzzy lesion boundaries and heterogeneous lesion textures. We present a fully automatic method for skin lesion segmentation based on deep fully convolutional networks (FCNs). We investigate a shallow encoding network to model clinically valuable prior knowledge, in which spatial filters simulating simple cell receptive fields function in the primary visual cortex (V1) is considered. An effective fusing strategy using skip connections and convolution operators is then leveraged to couple prior knowledge encoded via shallow network with hierarchical data-driven features learned from the FCNs for detailed segmentation of the skin lesions. To our best knowledge, this is the first time the domain-specific hand craft features have been built into a deep network trained in an end-to-end manner for skin lesion segmentation. The method has been evaluated on both ISBI 2016 and ISBI 2017 skin lesion challenge datasets. We provide comparative evidence to demonstrate that our newly designed network can gain accuracy for lesion segmentation by coupling the prior knowledge encoded by the shallow network with the deep FCNs. Our method is robust without the need for data augmentation or comprehensive parameter tuning, and the experimental results show great promise of the method with effective model generalization compared to other state-of-the-art-methods.

Toward a Biologically Plausible Model of LGN-V1 Pathways Based on Efficient Coding.

Increasing evidence supports the hypothesis that the visual system employs a sparse code to represent visual stimuli, where information is encoded in an efficient way by a small population of cells that respond to sensory input at a given time. This includes simple cells in primary visual cortex (V1), which are defined by their linear spatial integration of visual stimuli. Various models of sparse coding have been proposed to explain physiological phenomena observed in simple cells. However, these models have usually made the simplifying assumption that inputs to simple cells already incorporate linear spatial summation. This overlooks the fact that these inputs are known to have strong non-linearities such the separation of ON and OFF pathways, or separation of excitatory and inhibitory neurons. Consequently these models ignore a range of important experimental phenomena that are related to the emergence of linear spatial summation from non-linear inputs, such as segregation of ON and OFF sub-regions of simple cell receptive fields, the push-pull effect of excitation and inhibition, and phase-reversed cortico-thalamic feedback. Here, we demonstrate that a two-layer model of the visual pathway from the lateral geniculate nucleus to V1 that incorporates these biological constraints on the neural circuits and is based on sparse coding can account for the emergence of these experimental phenomena, diverse shapes of receptive fields and contrast invariance of orientation tuning of simple cells when the model is trained on natural images. The model suggests that sparse coding can be implemented by the V1 simple cells using neural circuits with a simple biologically plausible architecture.

Biologically inspired computational modeling of motion based on middle temporal area

Abstract This paper describes a bio-inspired algorithm for motion computation based on V1 (Primary Visual Cortex) andMT (Middle Temporal Area) cells. The behavior of neurons in V1 and MT areas contain significant information to understand the perception of motion. From a computational perspective, the neurons are treated as two dimensional filters to represent the receptive fields of simple cells that compose the complex cells. A modified elaborated Reichardt detector, adding an output exponent before the last stage followed by a re-entry stage of modulating feedback from MT, (reciprocal connections of V1 and MT) in a hierarchical framework, is proposed. The endstopped units, where the receptive fields of cells are surrounded by suppressive regions, are modeled as a divisive operation. MT cells play an important role for integrating and interpreting inputs from earlier-level (V1).We fit a normalization and a pooling to find the most active neurons for motion detection. All steps employed are physiologically inspired processing schemes and need some degree of simplification and abstraction. The results suggest that our proposed algorithm can achieve better performance than recent state-of-the-art bio-inspired approaches for real world images.

Spatial summation across the visual field in strabismic and anisometropic amblyopia

Ricco’s area (the largest area of visual space in which stimulus area and intensity are inversely proportional at threshold) has previously been hypothesised to be a result of centre/surround antagonism in retinal ganglion cell receptive fields, but recent evidence suggests a sizeable cortical contribution. Here, Ricco’s area was measured in amblyopia, a condition in which retinal receptive fields are normal, to better understand its physiological basis. Spatial summation functions were determined at 12 visual field locations in both eyes of 14 amblyopic adults and 15 normal-sighted controls. Ricco’s area was significantly larger in amblyopic eyes than in fellow non-amblyopic eyes. Compared to the size of Ricco’s area in control eyes, Ricco’s area measured significantly larger in amblyopic eyes. Additionally, Ricco’s area in the fellow, non-amblyopic eye of amblyopic participants measured significantly smaller than in control eyes. Compared to controls, Ricco’s area was larger in amblyopic eyes and smaller in fellow non-amblyopic eyes. Amblyopia type, binocularity, and inter-ocular difference in visual acuity were significantly associated with inter-ocular differences in Ricco’s area in amblyopes. The physiological basis for Ricco’s area is unlikely to be confined to the retina, but more likely representative of spatial summation at multiple sites along the visual pathway.

Eliminating Glutamatergic Input onto Horizontal Cells Changes the Dynamic Range and Receptive Field Organization of Mouse Retinal Ganglion Cells.

In the mammalian retina, horizontal cells receive glutamatergic inputs from many rod and cone photoreceptors and return feedback signals to them, thereby changing photoreceptor glutamate release in a light-dependent manner. Horizontal cells also provide feedforward signals to bipolar cells. It is unclear, however, how horizontal cell signals also affect the temporal, spatial, and contrast tuning in retinal output neurons, the ganglion cells. To study this, we generated a genetically modified mouse line in which we eliminated the light dependency of feedback by deleting glutamate receptors from mouse horizontal cells. This genetic modification allowed us to investigate the impact of horizontal cells on ganglion cell signaling independent of the actual mode of feedback in the outer retina and without pharmacological manipulation of signal transmission. In control and genetically modified mice (both sexes), we recorded the light responses of transient OFF-α retinal ganglion cells in the intact retina. Excitatory postsynaptic currents (EPSCs) were reduced and the cells were tuned to lower temporal frequencies and higher contrasts, presumably because photoreceptor output was attenuated. Moreover, receptive fields of recorded cells showed a significantly altered surround structure. Our data thus suggest that horizontal cells are responsible for adjusting the dynamic range of retinal ganglion cells and, together with amacrine cells, contribute to the center/surround organization of ganglion cell receptive fields in the mouse.SIGNIFICANCE STATEMENT Horizontal cells represent a major neuronal class in the mammalian retina and provide lateral feedback and feedforward signals to photoreceptors and bipolar cells, respectively. The mode of signal transmission remains controversial and, moreover, the contribution of horizontal cells to visual processing is still elusive. To address the question of how horizontal cells affect retinal output signals, we recorded the light responses of transient OFF-α retinal ganglion cells in a newly generated mouse line. In this mouse line, horizontal cell signals were no longer modulated by light. With light response recordings, we show that horizontal cells increase the dynamic range of retinal ganglion cells for contrast and temporal changes and contribute to the center/surround organization of their receptive fields.

Visual resolution and cone spacing in the nasal and inferior retina.

To determine the retinal eccentricity at which cones are no longer an observable substitute for ganglion cells on nasal and inferior parafoveal visual acuity. Visual acuities were measured on 12 healthy volunteers, under dynamic adaptive optic aberrations correction (crx1™) in white light, from 0° to 6°, every two degrees, along the nasal and inferior retinal meridians. Cone spacing was measured on images of the retina acquired using an adaptive optic flood illumination retina camera (rtx1™) at the same eccentricity, except at 0°. Cone spacing increased by around 0.13min of arc per degree of eccentricity and a difference of 7% between both meridians was observed (higher cone spacing in the inferior retinal meridian). Visual resolution was higher in the nasal retinal meridian (difference of around 28% or 0.15 logMAR at 6°). Cone spacing can predict minimum angle of resolution (MAR) at 2° in both semi retinal meridians. In the inferior retinal meridian, MAR measurements are fairly well predicted by Watson's 50% mathematical model based on the midget retinal ganglion cell density. Along the nasal retinal meridian, the measured MAR lies between Watson's 50% and 100% models. At 2° of eccentricity, cone density accurately predicts visual resolution in both the nasal and inferior retina, supporting the idea that only 50% of the foveal midget retinal ganglion cells determine VA. The 50% model can also predict VA in the inferior retinal meridian at 4° and 6° of eccentricity. However, the 50% model underestimated visual acuity in the nasal retinal meridian at 4° and 6° of eccentricity consistent with the partially overlapping ON and OFF midget retinal ganglion cell receptive fields.

Pannexin 1 Is Critically Involved in Feedback from Horizontal Cells to Cones.

Retinal horizontal cells (HCs) feed back negatively to cone photoreceptors and in that way generate the center/surround organization of bipolar cell receptive fields. The mechanism by which HCs inhibit photoreceptors is a matter of debate. General consensus exists that horizontal cell activity leads to the modulation of the cone Ca-current. This modulation has two components, one fast and the other slow. Several mechanisms for this modulation have been proposed: a fast ephaptic mechanism, and a slow pH mediated mechanism. Here we test the hypothesis that the slow negative feedback signal from HCs to cones is mediated by Panx1 channels expressed at the tips of the dendrites of horizontal cell. We generated zebrafish lacking Panx1 and found that the slow component of the feedback signal was strongly reduced in the mutants showing that Panx1 channels are a fundamental part of the negative feedback pathway from HCs to cones.

Inhibition in Simple Cell Receptive Fields Is Broad and OFF-Subregion Biased.

Inhibition in thalamorecipient layer 4 simple cells of primary visual cortex is believed to play important roles in establishing visual response properties and integrating visual inputs across their receptive fields (RFs). Simple cell RFs are characterized by nonoverlapping, spatially restricted subregions in which visual stimuli can either increase or decrease the firing rate of the cell, depending on contrast. Inhibition is believed to be triggered exclusively from visual stimulation of individual RF subregions. However, this view is at odds with the known anatomy of layer 4 interneurons in visual cortex and differs from recent findings in mouse visual cortex. Here we show with in vivo intracellular recordings in cats that while excitation is restricted to RF subregions, inhibition spans the width of simple cell RFs. Consequently, excitatory stimuli within a subregion concomitantly drive excitation and inhibition. Furthermore, we found that the distribution of inhibition across the RF is stronger toward OFF subregions. This inhibitory OFF-subregion bias has a functional consequence on spatial integration of inputs across the RF. A model based on the known anatomy of layer 4 demonstrates that the known proportion and connectivity of inhibitory neurons in layer 4 of primary visual cortex is sufficient to explain broad inhibition with an OFF-subregion bias while generating a variety of phase relations, including antiphase, between excitation and inhibition in response to drifting gratings.SIGNIFICANCE STATEMENT The wiring of excitatory and inhibitory neurons in cortical circuits is key to determining the response properties in sensory cortex. In the visual cortex, the first cells that receive visual input are simple cells in layer 4. The underlying circuitry responsible for the response properties of simple cells is not yet known. In this study, we challenge a long-held view concerning the pattern of inhibitory input and provide results that agree with current known anatomy. We show here that inhibition is evoked broadly across the receptive fields of simple cells, and we identify a surprising bias in inhibition within the receptive field. Our findings represent a step toward a unified view of inhibition across different species and sensory systems.

Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells.

Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell's signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell's receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types.NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types.

Dopamine Regulation of GABAA Receptors Contributes to Light/Dark Modulation of the ON-Cone Bipolar Cell Receptive Field Surround in the Retina

Cone bipolar cells are interneurons that receive synaptic input from cone photoreceptor cells and provide the output of the first synaptic layer of the retina. These cells exhibit center-surround receptive fields, a prototype of lateral inhibition between neighboring sensory cells in which stimulation of the receptive field center excites the cell whereas stimulation of the surrounding region laterally inhibits the cell. This fundamental sensory coding mechanism facilitates spatial discrimination and detection of stimulus edges. However, although it is well established that the receptive field surround is strongest when ambient or background illumination is most intense, e.g., at midday, and that the surround is minimal following maintained darkness, the synaptic mechanisms that produce and modulate the surround have not been resolved. Using electrical recording of bipolar cells under experimental conditions in which the cells exhibited surround light responses, and light and electron microscopic immunocytochemistry, we show in the rabbit retina that bright-light-induced activation of dopamine D1 receptors located on ON-center cone bipolar cell dendrites increases the expression and activity of GABAA receptors on the dendrites of the cells and that surround light responses depend on endogenous GABAA receptor activation. We also show that maintained darkness and D1 receptor blockade following maintained illumination and D1 receptor activation result in minimal GABAA receptor expression and activity and greatly diminished surrounds. Modulation of the D1/GABAA receptor signaling pathway of ON-cBC dendrites by the ambient light level facilitates detection of spatial details on bright days and large dim objects on moonless nights.

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

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.

Inhibition decorrelates visual feature representations in the inner retina.

SUMMARYThe retina extracts visual features for transmission to the brain. Different types of bipolar cell split the photoreceptor input into parallel channels and provide the excitatory drive for downstream visual circuits. Anatomically and genetically, mouse bipolar cell types have been described at great detail, but a similarly deep understanding of their functional diversity is lacking. By imaging light-driven glutamate release from more than 13,000 bipolar cell axon terminals in the intact retina, we here show that bipolar cell functional diversity is generated by the interplay of dendritic excitatory inputs and axonal inhibitory inputs. The resultant centre and surround components of bipolar cell receptive fields interact to decorrelate bipolar cell output in the spatial and temporal domain. Our findings highlight the importance of inhibitory circuits in generating functionally diverse excitatory pathways and suggest that decorrelation of parallel visual pathways begins already at the second synapse of the mouse visual system.