Transformation of Stimulus Correlations by the Retina

Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure; these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible.     

Prediction of orientation selectivity from receptive field architecture in simple cells of cat visual cortex

From the intracellularly recorded responses to small, rapidly flashed spots, we have quantitatively mapped the receptive fields of simple cells in the cat visual cortex. We then applied these maps to a feedforward model of orientation selectivity. Both the preferred orientation and the width of orientation tuning of the responses to oriented stimuli were well predicted by the model. Where tested, the tuning curve was well predicted at different spatial frequencies. The model was also successful in predicting certain features of the spatial frequency selectivity of the cells. It did not successfully predict the amplitude of the responses to drifting gratings. Our results show that the spatial organization of the receptive field can account for a large fraction of the orientation selectivity of simple cells.     

Extended difference-of-Gaussians model incorporating cortical feedback for relay cells in the lateral geniculate nucleus of cat

A striking feature of the organization of the early visual pathway is the significant feedback from primary visual cortex to cells in the dorsal lateral geniculate nucleus (LGN). Despite numerous experimental and modeling studies, the functional role for this feedback remains elusive. We present a new firing-rate-based model for LGN relay cells in cat, explicitly accounting for thalamocortical loop effects. The established DOG model, here assumed to account for the spatial aspects of the feedforward processing of visual stimuli, is extended to incorporate the influence of thalamocortical loops including a full set of orientation-selective cortical cell populations. Assuming a phase-reversed push-pull arrangement of ON and OFF cortical feedback as seen experimentally, this extended DOG (eDOG) model exhibits linear firing properties despite non-linear firing characteristics of the corticothalamic cells. The spatiotemporal receptive field of the eDOG model has a simple algebraic structure in Fourier space, while the real-space receptive field, as well as responses to visual stimuli, are found by evaluation of an integral. As an example application we use the eDOG model to study effects of cortical feedback on responses to flashing circular spots and patch-grating stimuli and find that the eDOG model can qualitatively account for experimental findings.     

Excitability cycles and rhythmic responses of visual cortical neurons to diffuse and punctiform light stimuli

The responses of the rabbit's visual cortical neurons to paired and rhythmic punctiform stimulation of their receptive fields were compared with responses to diffuse photic stimuli and the electric stimulation of the optic nerve. Diffuse photic and electric stimuli evoke a short-lasting initial activation of a neuron, followed by an inhibitory phase, during which the response to repetitive stimulation is suppressed. By contrast, localized stimulation of the neuron's receptive field with a spot of light produces an intensive and longer-lasting activation which is not followed by profound inhibition. Fusion of the responses to paired and rhythmic localized stimuli is therefore possible when the intervals between stimuli are brief enough. Rhythmic stimulation is capable of evoking sustained activation of a neuron during the entire duration of light flicker. During stimulation of a single point of the receptive field such prolonged activation can take place only within a limited range of stimulation frequencies (up to 15/sec), while higher frequencies evoke responses to the onset and offset of sequences of light flashes only. If, however, rhythmic stimuli alternate between the various points of a receptive field, prolonged neuronal activation is observed with any frequency of stimulation.A. N. Severtsov Institute of Evolutionary Morphology and Ecology of Animals, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 3, No. 3, pp. 252–259, May–June, 1971.     

Functional mechanisms shaping lateral geniculate responses to artificial and natural stimuli

Functional models of the early visual system should predict responses not only to simple artificial stimuli but also to sequences of complex natural scenes. An ideal testbed for such models is the lateral geniculate nucleus (LGN). Mechanisms shaping LGN responses include the linear receptive field and two fast adaptation processes, sensitive to luminance and contrast. We propose a compact functional model for these mechanisms that operates on sequences of arbitrary images. With the same parameters that fit the firing rate responses to simple stimuli, it predicts the bulk of the firing rate responses to complex stimuli, including natural scenes. Further improvements could result by adding a spiking mechanism, possibly one capable of bursts, but not by adding mechanisms of slow adaptation. We conclude that up to the LGN the responses to natural scenes can be largely explained through insights gained with simple artificial stimuli.     

Local non-linear interactions in the visual cortex may reflect global decorrelation

The classical receptive field in the primary visual cortex have been successfully explained by sparse activation of relatively independent units, whose tuning properties reflect the statistical dependencies in the natural environment. Robust surround modulation, emerging from stimulation beyond the classical receptive field, has been associated with increase of lifetime sparseness in the V1, but the system-wide modulation of response strength have currently no theoretical explanation. We measured fMRI responses from human visual cortex and quantified the contextual modulation with a decorrelation coefficient (d), derived from a subtractive normalization model. All active cortical areas demonstrated local non-linear summation of responses, which were in line with hypothesis of global decorrelation of voxels responses. In addition, we found sensitivity to surrounding stimulus structure across the ventral stream, and large-scale sensitivity to the number of simultaneous objects. Response sparseness across voxel population increased consistently with larger stimuli. These data suggest that contextual modulation for a stimulus event reflect optimization of the code and perhaps increase in energy efficiency throughout the ventral stream hierarchy. Our model provides a novel prediction that average suppression of response amplitude for simultaneous stimuli across the cortical network is a monotonic function of similarity of response strengths in the network when the stimuli are presented alone.     

Effects of ES52, an enkephalinase inhibitor, on responses of ventrobasal thalamic neurons in rat

The effects of ES52, a highly potent derivative of Thiorphan, an inhibitor of enkephalinase, at doses of 5 and 10 mg/kg IV were studied on the responses to cutaneous stimuli of 18 “nociceptive” (N), 10 “convergent” (NNn) and 4 “non-nociceptive” (Nn) neurons recorded in the ventrobasal (VB) complex of the rat. The responses of neurons exclusively driven by noxious mechanical and thermal stimuli (N neurons) were depressed by 56% by ES52 15 min after the injection of 5 or 10 mg/kg IV. This depressive effect was reversed by naloxone for half the neurons. For the ten neurons driven by both noxious and non-noxious stimuli (convergent NNn neurons), the responses to noxious heat were decreased by 42% at 15 min. By contrast, there was a marked enlargement of their receptive fields to light tactile stimuli, which was not naloxone-reversible. The receptive fields of neurons exclusively driven by non-noxious stimuli (Nn neurons) were also greatly expanded by ES52. These results show that ES52 can depress the responses of VB thalamic neurons to noxious stimuli; the effects on receptive field size underlines the complexity of the endogenous opiate systems.     

Perisaccadic Remapping and Rescaling of Visual Responses in Macaque Superior Colliculus

Visual neurons have spatial receptive fields that encode the positions of objects relative to the fovea. Because foveate animals execute frequent saccadic eye movements, this position information is constantly changing, even though the visual world is generally stationary. Interestingly, visual receptive fields in many brain regions have been found to exhibit changes in strength, size, or position around the time of each saccade, and these changes have often been suggested to be involved in the maintenance of perceptual stability. Crucial to the circuitry underlying perisaccadic changes in visual receptive fields is the superior colliculus (SC), a brainstem structure responsible for integrating visual and oculomotor signals. In this work we have studied the time-course of receptive field changes in the SC. We find that the distribution of the latencies of SC responses to stimuli placed outside the fixation receptive field is bimodal: The first mode is comprised of early responses that are temporally locked to the onset of the visual probe stimulus and stronger for probes placed closer to the classical receptive field. We suggest that such responses are therefore consistent with a perisaccadic rescaling, or enhancement, of weak visual responses within a fixed spatial receptive field. The second mode is more similar to the remapping that has been reported in the cortex, as responses are time-locked to saccade onset and stronger for stimuli placed in the postsaccadic receptive field location. We suggest that these two temporal phases of spatial updating may represent different sources of input to the SC.     

A Normalization Model of Attentional Modulation of Single Unit Responses

Although many studies have shown that attention to a stimulus can enhance the responses of individual cortical sensory neurons, little is known about how attention accomplishes this change in response. Here, we propose that attention-based changes in neuronal responses depend on the same response normalization mechanism that adjusts sensory responses whenever multiple stimuli are present. We have implemented a model of attention that assumes that attention works only through this normalization mechanism, and show that it can replicate key effects of attention. The model successfully explains how attention changes the gain of responses to individual stimuli and also why modulation by attention is more robust and not a simple gain change when multiple stimuli are present inside a neuron''s receptive field. Additionally, the model accounts well for physiological data that measure separately attentional modulation and sensory normalization of the responses of individual neurons in area MT in visual cortex. The proposal that attention works through a normalization mechanism sheds new light a broad range of observations on how attention alters the representation of sensory information in cerebral cortex.     

Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration

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 encoding models. 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 particular when stimulated with contrast-reversing gratings. We here study the influence of spatial nonlinearities in the encoding of natural images by ganglion cells, using multielectrode-array recordings from isolated salamander and mouse retinas. We assess how responses to natural 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. We show that taking not only the weighted average of light intensity inside the receptive field into account but also its variance over space can partly account for nonlinear integration and substantially improve response predictions of responses to novel images. For salamander ganglion cells, we find that response predictions for cell classes with large receptive fields profit most from including spatial contrast information. Finally, we demonstrate how this model framework can be used to assess the spatial scale of nonlinear integration. Our results underscore that nonlinear spatial stimulus integration translates to stimulation with 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.     

On the mechanisms underlying appearance of responses to movement,directional sensitivity and velocity tuning of the cat's striate cortical neurons

The responses to moving and stationary stimuli of 27 cat's striate cortical units were studied. Two stationary light bars located in different parts of the receptive field were used. The order of presentation and the time-interval between the stimuli varied; so, the presentation of a pair of stationary stimuli was an analogue of a moving stimulus.It was shown that responses occurred in neurons previously unresponsive to stationary stimuli when two stationary stimuli were presented successively in certain order. In the direction-sensitive units an asymmetry of the temporal course of the inhibitory processes was observed. The inhibitory zone located on the side of the preferred direction of movement was characterized by an early inhibitory phase followed by a phase of disinhibition and by a second inhibitory phase. For the inhibitory zone located on the side of the null direction no disinhibitory phase was demonstrated.The significance of the spatial and temporal characteristics of the receptive field for the appearance of responses to movement, the directional sensitivity and the velocity tuning in striate neurons is discussed.     

Modeling of the vertebrate visual system. II. Application to the turtle cone retina

The model of the vertebrate cone retina was adapted to the turtle retina with its red cone- and L-channel-dominances. The model consists of an ordering of four spatial organizations of unit hexagons, weighted inputs for all cones in the receptive fields, and linear polarization factors based on data from literature on turtle retina. Data generated by the model for spatial and chromatic patterns of receptive fields, intensity-response curves, dynamic ranges for cones, horizontal and bipolar cells proved remarkably consistent with literature. The model also generates observed phenomena such as near-field enhancement of cones due to stray light effects and electrical coupling of like-cones and far-field decrease in responses due to negative feedback from L-type horizontal cells to cones. Annular stimuli were shown to be more effective than spot stimuli for horizontal cells. The formal approach of the model demonstrates factors which play roles in various observed phenomena and all aspects of model can be displayed and tested both qualitatively and quantitatively.     

Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles

Analysis of sensory neurons'' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron''s receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron''s receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.     

Dynamic characteristics of the receptive field of L-cells for monochromatic lights

We applied the Wiener theory to analyse receptive field responses of L-cells in the carp and studied some dynamic properties of the receptive field of L-cells for monochromatic light stimuli. The L-cells were stimulated by each monochromatic light modulated in white-noise fashion. They responded almost linearly to all the monochromatic light stimuli. The impulse responses of the L-cells became larger in amplitude and faster in latency, peak response time, and repolarising phase as a spot of monochromatic light was enlarged. The L-cells seem to respond like a lowpass filter and the cutoff frequency of their gain characteristics increases with the enlargement of the monochromatic light spot. The relation between shift of cutoff frequency and spot diameter was monotonic increasing for each monochromatic light.     

A functional model of the wiring of the simple cells of visual cortex

A computer model of the simple cells in the mammalian visual cortex was constructed. The model cells received inputs from a great number of isopolar centre/surround cells assumed to be located in the lateral geniculate nucleus (LGN). The distribution of input to the model simple cells was either inhibitory/excitatory or inhibitory/excitatory/inhibitory. Such arrangements produced receptive fields containing four or five consecutively antagonistic subfields. Responses produced by the model cells to different types of stimuli (periodical as well as nonperiodical) were obtained and compared to responses of living cells reported from various laboratories under comparable stimulus conditions. In all the situations tested, the responses of the model cells corresponded qualitatively very well to those of living cells. It was seen that the same wiring mechanism was able to account for orientation selectivity, spatial frequency filtering, various phase relationships between stimulus and response, subfield orientational selectivity, and slight end-inhibition. Furthermore, the receptive fields of the model simple cells closely resemble Gabor functions.     

Biased competition through variations in amplitude of <Emphasis Type="Italic">γ</Emphasis>-oscillations

Experiments in visual cortex have shown that the firing rate of a neuron in response to the simultaneous presentation of a preferred and non-preferred stimulus within the receptive field is intermediate between that for the two stimuli alone (stimulus competition). Attention directed to one of the stimuli drives the response towards the response induced by the attended stimulus alone (selective attention). This study shows that a simple feedforward model with fixed synaptic conductance values can reproduce these two phenomena using synchronization in the gamma-frequency range to increase the effective synaptic gain for the responses to the attended stimulus. The performance of the model is robust to changes in the parameter values. The model predicts that the phase locking between presynaptic input and output spikes increases with attention.     

Using low-level filters to encode spatial displacements of visual stimuli

Directional responses to visual stimuli were analysed with the aid of a minimal computational model. The model is based upon arrays of motion sensors whose receptive fields are modified versions of those (difference-of-Gaussians) used to describe mechanisms in popular spatial vision models. In the model antagonistic influences on each motion sensor were assumed to: (1) arise from spatially non-aligned areas of the retina; and (2) to follow different time courses. Implications of the model were explored with simulations, and parallel psychophysical data were collected. Visual behaviours chosen for relatively detailed analysis were judgments of the temporal order of onset of two spatially displaced stimuli and motion aftereffects generated with discontinuously moving, sine-wave gratings.     

Contextual modulation of V1 receptive fields depends on their spatial symmetry

The apparent receptive field characteristics of sensory neurons depend on the statistics of the stimulus ensemble—a nonlinear phenomenon often called contextual modulation. Since visual cortical receptive fields determined from simple stimuli typically do not predict responses to complex stimuli, understanding contextual modulation is crucial to understanding responses to natural scenes. To analyze contextual modulation, we examined how apparent receptive fields differ for two stimulus ensembles that are matched in first- and second-order statistics, but differ in their feature content: one ensemble is enriched in elongated contours. To identify systematic trends across the neural population, we used a multidimensional scaling method, the Procrustes transformation. We found that contextual modulation of receptive field components increases with their spatial extent. More surprisingly, we also found that odd-symmetric components change systematically, but even-symmetric components do not. This symmetry dependence suggests that contextual modulation is driven by oriented On/Off dyads, i.e., modulation of the strength of intracortically-generated signals. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.