How the contrast gain control modifies the frequency responses of cat retinal ganglion cells

Characterization of extracellular spike waveforms recorded in wallaby primary visual cortex

Extracellular recordings were made from 642 units in the primary visual cortex (V1) of a highly visual marsupial, the Tammar wallaby. The receptive field (RF) characteristics of the cells were objectively estimated using the non-linear input model (NIM), and these were correlated with spike shapes. We found that wallaby cortical units had 68% regular spiking (RS), 12% fast spiking (FS), 4% triphasic spiking (TS), 5% compound spiking (CS) and 11% positive spiking (PS). RS waveforms are most often associated with recordings from pyramidal or spiny stellate cell bodies, suggesting that recordings from these cell types dominate in the wallaby cortex. In wallaby, 70-80% of FS and RS cells had orientation selective RFs and had evenly distributed linear and nonlinear RFs. We found that 47% of wallaby PS units were non-orientation selective and they were dominated by linear RFs. Previous studies suggest that the PS units represent recordings from the axon terminals of non-orientation selective cells originating in the lateral geniculate nucleus (LGN). If this is also true in wallaby, as strongly suggested by their low response latencies and bursty spiking properties, the results suggest that significantly more neurons in wallaby LGN are already orientation selective. In wallaby, less than 10% of recorded spikes had triphasic (TS) or sluggish compound spiking (CS) waveforms. These units had a mixture of orientation selective and non-oriented properties, and their cellular origins remain difficult to classify.

Brain State-Dependent Modulation of Thalamic Visual Processing by Cortico-Thalamic Feedback

The behavioral state of a mammal impacts how the brain responds to visual stimuli as early as in the dorsolateral geniculate nucleus of the thalamus (dLGN), the primary relay of visual information to the cortex. A clear example of this is the markedly stronger response of dLGN neurons to higher temporal frequencies of the visual stimulus in alert as compared with quiescent animals. The dLGN receives strong feedback from the visual cortex, yet whether this feedback contributes to these state-dependent responses to visual stimuli is poorly understood. Here, we show that in male and female mice, silencing cortico-thalamic feedback profoundly reduces state-dependent differences in the response of dLGN neurons to visual stimuli. This holds true for dLGN responses to both temporal and spatial features of the visual stimulus. These results reveal that the state-dependent shift of the response to visual stimuli in an early stage of visual processing depends on cortico-thalamic feedback.SIGNIFICANCE STATEMENT Brain state affects even the earliest stages of sensory processing. A clear example of this phenomenon is the change in thalamic responses to visual stimuli depending on whether the animal's brain is in an alert or quiescent state. Despite the radical impact that brain state has on sensory processing, the underlying circuits are still poorly understood. Here, we show that both the temporal and spatial response properties of thalamic neurons to visual stimuli depend on the state of the animal and, crucially, that this state-dependent shift relies on the feedback projection from visual cortex to thalamus.

Contrast and Luminance Gain Control in the Macaque's Lateral Geniculate Nucleus

There is substantial variation in the mean and variance of light levels (luminance and contrast) in natural visual scenes. Retinal ganglion cells maintain their sensitivity despite this variation using two adaptive mechanisms, which control how responses depend on luminance and on contrast. However, the nature of each mechanism and their interactions downstream of the retina are unknown. We recorded neurons in the magnocellular and parvocellular layers of the lateral geniculate nucleus (LGN) in anesthetized adult male macaques and characterized how their responses adapt to changes in contrast and luminance. As contrast increases, neurons in the magnocellular layers maintain sensitivity to high temporal frequency stimuli but attenuate sensitivity to low-temporal frequency stimuli. Neurons in the parvocellular layers do not adapt to changes in contrast. As luminance increases, both magnocellular and parvocellular cells increase their sensitivity to high-temporal frequency stimuli. Adaptation to luminance is independent of adaptation to contrast, as previously reported for LGN neurons in the cat. Our results are similar to those previously reported for macaque retinal ganglion cells, suggesting that adaptation to luminance and contrast result from two independent mechanisms that are retinal in origin.

Cascaded normalizations for spatial integration in the primary visual cortex of primates

Spatial integration of visual information is an important function in the brain. However, neural computation for spatial integration in the visual cortex remains unclear. In this study, we recorded laminar responses in V1 of awake monkeys driven by visual stimuli with grating patches and annuli of different sizes. We find three important response properties related to spatial integration that are significantly different between input and output layers: neurons in output layers have stronger surround suppression, smaller receptive field (RF), and higher sensitivity to grating annuli partially covering their RFs. These interlaminar differences can be explained by a descriptive model composed of two global divisions (normalization) and a local subtraction. Our results suggest suppressions with cascaded normalizations (CNs) are essential for spatial integration and laminar processing in the visual cortex. Interestingly, the features of spatial integration in convolutional neural networks, especially in lower layers, are different from our findings in V1.

Detection and discrimination of achromatic contrast: A ganglion cell perspective

The magnocellular (MC) pathway in the primate has much higher achromatic contrast sensitivity than the parvocellular (PC) pathway, and is implicated in luminance contrast detection. But MC pathway responses tend to saturate at lower achromatic contrast than do PC pathway responses. It has been proposed that the PC pathway plays a major role in discriminating suprathreshold achromatic contrast, because the MC pathway is in saturation. This has been termed the pulsed-pedestal protocol. To test this hypothesis, responses of MC and PC pathway ganglion cells have been examined under suprathreshold conditions with stimulus configurations similar to those in psychophysical tests. For MC cells, response saturation was much less for flashed or moving edges than for sinusoidal modulation, and MC cell thresholds predicted for these stimuli were similar to psychophysical discrimination (and detection) data. Results suggest the protocol is not effective in segregating MC and PC function.

Stimulus Contrast Affects Spatial Integration in the Lateral Geniculate Nucleus of Macaque Monkeys

Gain-control mechanisms adjust neuronal responses to accommodate the wide range of stimulus conditions in the natural environment. Contrast gain control and extraclassical surround suppression are two manifestations of gain control that govern the responses of neurons in the early visual system. Understanding how these two forms of gain control interact has important implications for the detection and discrimination of stimuli across a range of contrast conditions. Here, we report that stimulus contrast affects spatial integration in the lateral geniculate nucleus of alert macaque monkeys (male and female), whereby neurons exhibit a reduction in the strength of extraclassical surround suppression and an expansion in the preferred stimulus size with low-contrast stimuli compared with high-contrast stimuli. Effects were greater for magnocellular neurons than for parvocellular neurons, indicating stream-specific interactions between stimulus contrast and stimulus size. Within the magnocellular pathway, contrast-dependent effects were comparable for ON-center and OFF-center neurons, despite ON neurons having larger receptive fields, less pronounced surround suppression, and more pronounced contrast gain control than OFF neurons. Together, these findings suggest that the parallel streams delivering visual information from retina to primary visual cortex, serve not only to broaden the range of signals delivered to cortex, but also to provide a substrate for differential interactions between stimulus contrast and stimulus size that may serve to improve stimulus detection and stimulus discrimination under pathway-specific lower and higher contrast conditions, respectively.SIGNIFICANCE STATEMENT Stimulus contrast is a salient feature of visual scenes. Here we examine the influence of stimulus contrast on spatial integration in the lateral geniculate nucleus (LGN). Our results demonstrate that increases in contrast generally increase extraclassical suppression and decrease the size of optimal stimuli, indicating a reduction in the extent of visual space from which LGN neurons integrate signals. Differences between magnocellular and parvocellular neurons are noteworthy and further demonstrate that the feedforward parallel pathways to cortex increase the range of information conveyed for downstream cortical processing, a range broadened by diversity in the ON and OFF pathways. These results have important implications for more complex visual processing that underly the detection and discrimination of stimuli under varying natural conditions.

Spatiotemporal Content of Saccade Transients

Humans use rapid gaze shifts, known as saccades, to explore visual scenes. These movements yield abrupt luminance changes on the retina, which elicit robust neural discharges at fixation onsets. Yet little is known about the spatial content of saccade transients. Here, we show that saccades redistribute spatial information within the temporal range of retinal sensitivity following two distinct regimes: saccade modulations counterbalance (whiten) the spectral density of natural scenes at low spatial frequencies and follow the external power distribution at higher frequencies. This redistribution is a consequence of saccade dynamics, particularly the speed/amplitude/duration relation known as the main sequence. It resembles the redistribution resulting from inter-saccadic eye drifts, revealing a continuum in the modulations given by different eye movements, with oculomotor transitions primarily acting by regulating the bandwidth of whitening. Our findings suggest important computational roles for saccade transients in the establishment of spatial representations and lead to testable predictions about their consequences for visual functions and encoding mechanisms.

Additive effect of contrast and velocity suggests the role of strong excitatory drive in suppression of visual gamma response

It is commonly acknowledged that gamma-band oscillations arise from interplay between neural excitation and inhibition; however, the neural mechanisms controlling the power of stimulus-induced gamma responses (GR) in the human brain remain poorly understood. A moderate increase in velocity of drifting gratings results in GR power enhancement, while increasing the velocity beyond some 'transition point' leads to GR power attenuation. We tested two alternative explanations for this nonlinear input-output dependency in the GR power. First, the GR power can be maximal at the preferable velocity/temporal frequency of motion-sensitive V1 neurons. This 'velocity tuning' hypothesis predicts that lowering contrast either will not affect the transition point or shift it to a lower velocity. Second, the GR power attenuation at high velocities of visual motion can be caused by changes in excitation/inhibition balance with increasing excitatory drive. Since contrast and velocity both add to excitatory drive, this 'excitatory drive' hypothesis predicts that the 'transition point' for low-contrast gratings would be reached at a higher velocity, as compared to high-contrast gratings. To test these alternatives, we recorded magnetoencephalography during presentation of low (50%) and high (100%) contrast gratings drifting at four velocities. We found that lowering contrast led to a highly reliable shift of the GR suppression transition point to higher velocities, thus supporting the excitatory drive hypothesis. No effects of contrast or velocity were found in the alpha-beta range. The results have implications for understanding the mechanisms of gamma oscillations and developing gamma-based biomarkers of disturbed excitation/inhibition balance in brain disorders.

Sparse identification of contrast gain control in the fruit fly photoreceptor and amacrine cell layer

The fruit fly's natural visual environment is often characterized by light intensities ranging across several orders of magnitude and by rapidly varying contrast across space and time. Fruit fly photoreceptors robustly transduce and, in conjunction with amacrine cells, process visual scenes and provide the resulting signal to downstream targets. Here, we model the first step of visual processing in the photoreceptor-amacrine cell layer. We propose a novel divisive normalization processor (DNP) for modeling the computation taking place in the photoreceptor-amacrine cell layer. The DNP explicitly models the photoreceptor feedforward and temporal feedback processing paths and the spatio-temporal feedback path of the amacrine cells. We then formally characterize the contrast gain control of the DNP and provide sparse identification algorithms that can efficiently identify each the feedforward and feedback DNP components. The algorithms presented here are the first demonstration of tractable and robust identification of the components of a divisive normalization processor. The sparse identification algorithms can be readily employed in experimental settings, and their effectiveness is demonstrated with several examples.

Temporal information loss in the macaque early visual system

Stimuli that modulate neuronal activity are not always detectable, indicating a loss of information between the modulated neurons and perception. To identify where in the macaque visual system information about periodic light modulations is lost, signal-to-noise ratios were compared across simulated cone photoreceptors, lateral geniculate nucleus (LGN) neurons, and perceptual judgements. Stimuli were drifting, threshold-contrast Gabor patterns on a photopic background. The sensitivity of LGN neurons, extrapolated to populations, was similar to the monkeys' at low temporal frequencies. At high temporal frequencies, LGN sensitivity exceeded the monkeys' and approached the upper bound set by cone photocurrents. These results confirm a loss of high-frequency information downstream of the LGN. However, this loss accounted for only about 5% of the total. Phototransduction accounted for essentially all of the rest. Together, these results show that low temporal frequency information is lost primarily between the cones and the LGN, whereas high-frequency information is lost primarily within the cones, with a small additional loss downstream of the LGN.

Slow Temporal Dynamics of Motion-Induced Brightness Shift Reveals Impact of Adaptation

Brightness of an object is determined by various factors including ambient illumination, surface reflectance of the object, and spatial and temporal relation between the object and its surrounding context. Recently, it has been demonstrated that the motion of an object alters its own and nearby object’s appearance such as brightness and color. This study aims to unveil mechanisms of the motion-induced brightness shift by measuring its temporal dynamics. We found that the motion-induced brightness shift occurred instantaneously with the motion onset when the motion was introduced abruptly. However, the brightness of a stationary object was altered gradually by a nearby moving object in about 2 s time window when the stationary dot was introduced abruptly. Two distinct temporal dynamics (slow vs. fast) of the motion-induced brightness shift demonstrate that both slow neural adaptation and fast neural normalization processes determine the brightness shift induced by the object’s motion.

The dynamic receptive fields of retinal ganglion cells

Retinal ganglion cells (RGCs) were one of the first classes of sensory neurons to be described in terms of a receptive field (RF). Over the last six decades, our understanding of the diversity of RGC types and the nuances of their response properties has grown exponentially. We will review the current understanding of RGC RFs mostly from studies in mammals, but including work from other vertebrates as well. We will argue for a new paradigm that embraces the fluidity of RGC RFs with an eye toward the neuroethology of vision. Specifically, we will focus on (1) different methods for measuring RGC RFs, (2) RF models, (3) feature selectivity and the distinction between fluid and stable RF properties, and (4) ideas about the future of understanding RGC RFs.

Neuronal adaptation to sound statistics in the inferior colliculus of behaving macaques does not reduce the effectiveness of the masking noise

The detectability of target sounds embedded within noisy backgrounds is affected by the regularities that summarize acoustic sceneries. Previous studies suggested that the dynamic range of neurons in the inferior colliculus (IC) of anesthetized guinea pigs shifts toward the mean sound pressure level in irregular acoustic environments. Yet, it is unclear how this neuronal adaptation processes may influence the effectiveness of sounds as a masker, both behaviorally and in terms of neuronal encoding. To answer this question, we measured the neural response of IC neurons while macaque monkeys performed a Go/No-Go tone detection task. Macaques detected a 50-ms tone that was either simultaneously gated with a burst of noise or embedded within a continuous noise background, whose levels were randomly sampled (every 50 ms) from a probability distribution. The mean of the distribution matched the level of the gated burst of noise. Psychometric and IC neurometric thresholds to tones did not differ between the two masking conditions. However, the neuronal firing rate versus level function was significantly affected by the temporal characteristics of the noise masker. Simultaneously gated noise caused higher baseline responses and greater dynamic range compression compared with noise distribution. The slopes of psychometric and neurometric functions were significantly shallower for higher variance distributions, suggesting that neuronal sensitivity might change with the variability of the sound. Our results suggest that the adaptive response of IC neurons to sound regularities does not affect the effectiveness of the noise-masking signal, which remains invariant to surrounding noise amplitudes. NEW & NOTEWORTHY Auditory neurons adapt to the statistics of sound levels in the acoustic scene. However, it is still unclear to what extent such adaptation influences the effectiveness of the stimulus as a masker. Our study represents the first attempt to investigate how the adaptation to the statistics of masking stimuli may be related to the effectiveness of masking, and to the single-unit encoding of the midbrain auditory neurons in behaving animals.

Vision During Saccadic Eye Movements

The perceptual consequences of eye movements are manifold: Each large saccade is accompanied by a drop of sensitivity to luminance-contrast, low-frequency stimuli, impacting both conscious vision and involuntary responses, including pupillary constrictions. They also produce transient distortions of space, time, and number, which cannot be attributed to the mere motion on the retinae. All these are signs that the visual system evokes active processes to predict and counteract the consequences of saccades. We propose that a key mechanism is the reorganization of spatiotemporal visual fields, which transiently increases the temporal and spatial uncertainty of visual representations just before and during saccades. On one hand, this accounts for the spatiotemporal distortions of visual perception; on the other hand, it implements a mechanism for fusing pre- and postsaccadic stimuli. This, together with the active suppression of motion signals, ensures the stability and continuity of our visual experience.

Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing

We developed Convis, a Python simulation toolbox for large scale neural populations which offers arbitrary receptive fields by 3D convolutions executed on a graphics card. The resulting software proves to be flexible and easily extensible in Python, while building on the PyTorch library (The Pytorch Project, 2017), which was previously used successfully in deep learning applications, for just-in-time optimization and compilation of the model onto CPU or GPU architectures. An alternative implementation based on Theano (Theano Development Team, 2016) is also available, although not fully supported. Through automatic differentiation, any parameter of a specified model can be optimized to approach a desired output which is a significant improvement over e.g., Monte Carlo or particle optimizations without gradients. We show that a number of models including even complex non-linearities such as contrast gain control and spiking mechanisms can be implemented easily. We show in this paper that we can in particular recreate the simulation results of a popular retina simulation software VirtualRetina (Wohrer and Kornprobst, 2009), with the added benefit of providing (1) arbitrary linear filters instead of the product of Gaussian and exponential filters and (2) optimization routines utilizing the gradients of the model. We demonstrate the utility of 3d convolution filters with a simple direction selective filter. Also we show that it is possible to optimize the input for a certain goal, rather than the parameters, which can aid the design of experiments as well as closed-loop online stimulus generation. Yet, Convis is more than a retina simulator. For instance it can also predict the response of V1 orientation selective cells. Convis is open source under the GPL-3.0 license and available from https://github.com/jahuth/convis/ with documentation at https://jahuth.github.io/convis/.

Diverse inhibitory and excitatory mechanisms shape temporal tuning in transient OFF α ganglion cells in the rabbit retina

KEY POINTS

Neurons combine excitatory and inhibitory signals to perform computations. In the retina, interactions between excitation and inhibition enable neurons to detect specific visual features. We describe how several excitatory and inhibitory mechanisms work together to allow transient OFF α ganglion cells in the rabbit retina to respond selectively to high temporal frequencies and thus detect faster image motion. The weightings of these different mechanisms change with the contrast and spatiotemporal properties of the visual input, and thereby support temporal tuning in α cells over a range of visual conditions. The results help us understand how ganglion cells selectively integrate excitatory and inhibitory signals to extract specific information from the visual input.

ABSTRACT

The 20 to 30 types of ganglion cell in the mammalian retina represent parallel signalling pathways that convey different information to the brain. α ganglion cells are selective for high temporal frequencies in visual inputs, which makes them particularly sensitive to rapid motion. Although α ganglion cells have been studied in several species, the synaptic basis for their selective temporal tuning remains unclear. Here, we analyse excitatory synaptic inputs to transient OFF α ganglion cells (t-OFF α GCs) in the rabbit retina. We show that convergence of excitatory and inhibitory synaptic inputs within the bipolar cell terminals presynaptic to the t-OFF α GCs shifts the temporal tuning to higher temporal frequencies. GABAergic inhibition suppresses the excitatory input at low frequencies, but potentiates it at high frequencies. Crossover glycinergic inhibition and sodium channel activity in the presynaptic bipolar cells also potentiate high frequency excitatory inputs. We found differences in the spatial and temporal properties, and contrast sensitivities of these mechanisms. These differences in stimulus selectivity allow these mechanisms to generate bandpass temporal tuning of t-OFF α GCs over a range of visual conditions.

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.

A novel mechanism of cone photoreceptor adaptation

An animal’s ability to survive depends on its sensory systems being able to adapt to a wide range of environmental conditions, by maximizing the information extracted and reducing the noise transmitted. The visual system does this by adapting to luminance and contrast. While luminance adaptation can begin at the retinal photoreceptors, contrast adaptation has been shown to start at later stages in the retina. Photoreceptors adapt to changes in luminance over multiple time scales ranging from tens of milliseconds to minutes, with the adaptive changes arising from processes within the phototransduction cascade. Here we show a new form of adaptation in cones that is independent of the phototransduction process. Rather, it is mediated by voltage-gated ion channels in the cone membrane and acts by changing the frequency response of cones such that their responses speed up as the membrane potential modulation depth increases and slow down as the membrane potential modulation depth decreases. This mechanism is effectively activated by high-contrast stimuli dominated by low frequencies such as natural stimuli. However, the more generally used Gaussian white noise stimuli were not effective since they did not modulate the cone membrane potential to the same extent. This new adaptive process had a time constant of less than a second. A critical component of the underlying mechanism is the hyperpolarization-activated current, I_h, as pharmacologically blocking it prevented the long- and mid- wavelength sensitive cone photoreceptors (L- and M-cones) from adapting. Consistent with this, short- wavelength sensitive cone photoreceptors (S-cones) did not show the adaptive response, and we found they also lacked a prominent I_h. The adaptive filtering mechanism identified here improves the information flow by removing higher-frequency noise during lower signal-to-noise ratio conditions, as occurs when contrast levels are low. Although this new adaptive mechanism can be driven by contrast, it is not a contrast adaptation mechanism in its strictest sense, as will be argued in the Discussion.

An animal’s ability to survive depends on its ability to adapt to a wide range of light conditions, by maximizing the information flow through the retina. Here, we show a new form of adaptation in cone photoreceptors that helps them optimize the information they transmit by adjusting their response kinetics to better match the visual conditions. The adaptive mechanism we describe is independent of the cone phototransduction process and is instead mediated by membrane processes in which the hyperpolarization-activated current, I_h, plays a critical role. Consistent with the critical role of this current, we also found that cones sensitive to short wavelengths lacked a prominent I_h current and did not show this new form of adaptation. As voltage-dependent processes underlie the adaptational mechanism, it is only apparent when the stimuli are able to sufficiently modulate the membrane potential of cones. This happens with natural stimuli, which are able to deliver high levels of “effective” contrast. However, even though this new adaptive mechanism can be driven by contrast, we argue in the Discussion that in its strictest sense it is not a contrast adaptation mechanism per se.

Motion, Flash, and Flicker: A Unified Spatiotemporal Model of Perceived Edge Sharpening

Blurred edges appear sharper in motion than when they are stationary. We proposed a model of this motion sharpening that invokes a local, nonlinear contrast transducer function (Hammett et al, 1998 Vision Research38 2099–2108). Response saturation in the transducer compresses or ‘clips’ the input spatial waveform, rendering the edges as sharper. To explain the increasing distortion of drifting edges at higher speeds, the degree of nonlinearity must increase with speed or temporal frequency. A dynamic contrast gain control before the transducer can account for both the speed dependence and approximate contrast invariance of motION sharpening (Hammett et al, 2003 Vision Research in press). We show here that this model also predicts perceived sharpening of briefly flashed and flickering edges, and we show that the model can account fairly well for experimental data from all three modes of presentation (motion, flash, and flicker). At moderate durations and lower temporal frequencies the gain control attenuates the input signal, thus protecting it from later compression by the transducer. The gain control is somewhat sluggish, and so it suffers both a slow onset, and loss of power at high temporal frequencies. Consequently, brief presentations and high temporal frequencies of drift and flicker are less protected from distortion, and show greater perceptual sharpening.

How inhibitory circuits in the thalamus serve vision

Inhibitory neurons dominate the intrinsic circuits in the visual thalamus. Interneurons in the lateral geniculate nucleus innervate relay cells and each other densely to provide powerful inhibition. The visual sector of the overlying thalamic reticular nucleus receives input from relay cells and supplies feedback inhibition to them in return. Together, these two inhibitory circuits influence all information transmitted from the retina to the primary visual cortex. By contrast, relay cells make few local connections. This review explores the role of thalamic inhibition from the dual perspectives of feature detection and information theory. For example, we describe how inhibition sharpens tuning for spatial and temporal features of the stimulus and how it might enhance image perception. We also discuss how inhibitory circuits help to reduce redundancy in signals sent downstream and, at the same time, are adapted to maximize the amount of information conveyed to the cortex.

Macaque retinal ganglion cell responses to visual patterns: harmonic composition, noise, and psychophysical detectability

The goal of these experiments was to test how well cell responses to visual patterns can be predicted from the sinewave tuning curve. Magnocellular (MC) and parvocellular (PC) ganglion cell responses to different spatial waveforms (sinewave, squarewave, and ramp waveforms) were measured across a range of spatial frequencies. Sinewave spatial tuning curves were fit with standard Gaussian models. From these fits, waveforms and spatial tuning of a cell's responses to the other waveforms were predicted for different harmonics by scaling in amplitude for the power in the waveform's Fourier expansion series over spatial frequency. Since higher spatial harmonics move at a higher temporal frequency, an additional scaling for each harmonic by the MC (bandpass) or PC (lowpass) temporal response was included, together with response phase. Finally, the model included a rectifying nonlinearity. This provided a largely satisfactory estimation of MC and PC cell responses to complex waveforms. As a consequence of their transient responses, MC responses to complex waveforms were found to have significantly more energy in higher spatial harmonic components than PC responses. Response variance (noise) was also quantified as a function of harmonic component. Noise increased to some degree for the higher harmonics. The data are relevant for psychophysical detection or discrimination of visual patterns, and we discuss the results in this context.

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.

Our sensory systems have to process stimuli under a wide range of environmental conditions. To cope with this challenge, the involved neurons adapt by adjusting their signal processing to the recently encountered intensity range. In the visual system, one finds, for example, that higher visual contrast leads to changes in how visual signals are temporally filtered, making signal processing faster and more band-pass-like at higher contrast. By analyzing signals from neurons in the retina of salamanders, we here found that these adaptation effects can be described by a fixed set of filters, independent of contrast, whose relative contributions change with contrast. Also, we found that different phenomena contribute to this adaptation. In particular, some cells change their relative sensitivity to light increments and light decrements, whereas other cells are influenced by a strong contrast-dependence of the exact timing of their responses. Our results show that contrast adaptation in the retina is not an entirely homogeneous phenomenon, and that models with multiple filters can help in characterizing sensory adaptation.

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components.

SIGNIFICANCE STATEMENT

Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales.

Hearing in noisy environments: noise invariance and contrast gain control

Contrast gain control has recently been identified as a fundamental property of the auditory system. Electrophysiological recordings in ferrets have shown that neurons continuously adjust their gain (their sensitivity to change in sound level) in response to the contrast of sounds that are heard. At the level of the auditory cortex, these gain changes partly compensate for changes in sound contrast. This means that sounds which are structurally similar, but have different contrasts, have similar neuronal representations in the auditory cortex. As a result, the cortical representation is relatively invariant to stimulus contrast and robust to the presence of noise in the stimulus. In the inferior colliculus (an important subcortical auditory structure), gain changes are less reliably compensatory, suggesting that contrast- and noise-invariant representations are constructed gradually as one ascends the auditory pathway. In addition to noise invariance, contrast gain control provides a variety of computational advantages over static neuronal representations; it makes efficient use of neuronal dynamic range, may contribute to redundancy-reducing, sparse codes for sound and allows for simpler decoding of population responses. The circuits underlying auditory contrast gain control are still under investigation. As in the visual system, these circuits may be modulated by factors other than stimulus contrast, forming a potential neural substrate for mediating the effects of attention as well as interactions between the senses.

Impairments in background and event-related alpha-band oscillatory activity in patients with schizophrenia

Studies show that patients with schizophrenia exhibit impaired responses to sensory stimuli, especially at the early stages of neural processing. In particular, patients' alpha-band (8-14 Hz) event-related desynchronization (ERD) and visual P1 event-related potential (ERP) component tend to be significantly reduced, with P1 ERP deficits greater for visual stimuli biased towards the magnocellular system. In healthy controls, studies show that pre-stimulus alpha (background alpha) plays a pivotal role in sensory processing and behavior, largely by shaping the neural responses to incoming stimuli. Here, we address whether patients' ERD and P1 deficits stem from impairments in pre-stimulus alpha mechanisms. To address this question we recorded electrophysiological activity in patients with schizophrenia and healthy controls while they engaged in a visual discrimination task with low, medium, and high contrast stimuli. The results revealed a significant decrease in patients' ERDs, which was largely driven by reductions in pre-stimulus alpha. These reductions were most prominent in right-hemispheric areas. We also observed a systematic relationship between pre-stimulus alpha and the P1 component across different contrast levels. However, this relationship was only observed in healthy controls. Taken together, these findings highlight a substantial anomaly in patients' amplitude-based alpha background activity over visual areas. The results provide further support that pre-stimulus alpha activity plays an active role in perception by modulating the neural responses to incoming sensory inputs, a mechanism that seems to be compromised in schizophrenia.

Retinal representation of the elementary visual signal

The propagation of visual signals from individual cone photoreceptors through parallel neural circuits was examined in the primate retina. Targeted stimulation of individual cones was combined with simultaneous recording from multiple retinal ganglion cells of identified types. The visual signal initiated by an individual cone produced strong responses with different kinetics in three of the four numerically dominant ganglion cell types. The magnitude and kinetics of light responses in each ganglion cell varied nonlinearly with stimulus strength but in a manner that was independent of the cone of origin after accounting for the overall input strength of each cone. Based on this property of independence, the receptive field profile of an individual ganglion cell could be well estimated from responses to stimulation of each cone individually. Together, these findings provide a quantitative account of how elementary visual inputs form the ganglion cell receptive field.

Blood oxygen level-dependent activation of the primary visual cortex predicts size adaptation illusion

In natural scenes, objects rarely occur in isolation but appear within a spatiotemporal context. Here, we show that the perceived size of a stimulus is significantly affected by the context of the scene: brief previous presentation of larger or smaller adapting stimuli at the same region of space changes the perceived size of a test stimulus, with larger adapting stimuli causing the test to appear smaller than veridical and vice versa. In a human fMRI study, we measured the blood oxygen level-dependent activation (BOLD) responses of the primary visual cortex (V1) to the contours of large-diameter stimuli and found that activation closely matched the perceptual rather than the retinal stimulus size: the activated area of V1 increased or decreased, depending on the size of the preceding stimulus. A model based on local inhibitory V1 mechanisms simulated the inward or outward shifts of the stimulus contours and hence the perceptual effects. Our findings suggest that area V1 is actively involved in reshaping our perception to match the short-term statistics of the visual scene.

Perceptual consequence of normalization revealed by a novel brightness induction

The human brain is renowned for its dynamic regulation of sensory inputs, which enables our brain to operate under an enormous range of physical energy with sensory neurons whose processing range is limited. Here we present a novel and strong brightness induction that reflects neural mechanisms underlying this dynamic regulation of sensory inputs. When physically identical, stationary and moving objects are viewed simultaneously, the stationary and moving objects appear largely different. Experiments reveal that normalization at multiple stages of visual processing provides a plausible account for the large shifts in perceptual experiences, observed in both the stationary and the moving objects. This novel brightness induction suggests that brightness of an object is influenced not only by variations in surrounding light (i.e. simultaneous contrast) but also by dynamically changing neural responses associated with stimulus motion.

Binaural gain modulation of spectrotemporal tuning in the interaural level difference-coding pathway

In the brainstem, the auditory system diverges into two pathways that process different sound localization cues, interaural time differences (ITDs) and level differences (ILDs). We investigated the site where ILD is detected in the auditory system of barn owls, the posterior part of the lateral lemniscus (LLDp). This structure is equivalent to the lateral superior olive in mammals. The LLDp is unique in that it is the first place of binaural convergence in the brainstem where monaural excitatory and inhibitory inputs converge. Using binaurally uncorrelated noise and a generalized linear model, we were able to estimate the spectrotemporal tuning of excitatory and inhibitory inputs to these cells. We show that the response of LLDp neurons is highly locked to the stimulus envelope. Our data demonstrate that spectrotemporally tuned, temporally delayed inhibition enhances the reliability of envelope locking by modulating the gain of LLDp neurons' responses. The dependence of gain modulation on ILD shown here constitutes a means for space-dependent coding of stimulus identity by the initial stages of the auditory pathway.

Local and global contrast adaptation in retinal ganglion cells

Retinal ganglion cells react to changes in visual contrast by adjusting their sensitivity and temporal filtering characteristics. This contrast adaptation has primarily been studied under spatially homogeneous stimulation. Yet, ganglion cell receptive fields are often characterized by spatial subfields, providing a substrate for nonlinear spatial processing. This raises the question whether contrast adaptation follows a similar subfield structure or whether it occurs globally over the receptive field even for local stimulation. We therefore recorded ganglion cell activity in isolated salamander retinas while locally changing visual contrast. Ganglion cells showed primarily global adaptation characteristics, with notable exceptions in certain aspects of temporal filtering. Surprisingly, some changes in filtering were most pronounced for locations where contrast did not change. This seemingly paradoxical effect can be explained by a simple computational model, which emphasizes the importance of local nonlinearities in the retina and suggests a reevaluation of previously reported local contrast adaptation.

Alert response to motion onset in the retina

Previous studies have shown that motion onset is very effective at capturing attention and is more salient than smooth motion. Here, we find that this salience ranking is present already in the firing rate of retinal ganglion cells. By stimulating the retina with a bar that appears, stays still, and then starts moving, we demonstrate that a subset of salamander retinal ganglion cells, fast OFF cells, responds significantly more strongly to motion onset than to smooth motion. We refer to this phenomenon as an alert response to motion onset. We develop a computational model that predicts the time-varying firing rate of ganglion cells responding to the appearance, onset, and smooth motion of a bar. This model, termed the adaptive cascade model, consists of a ganglion cell that receives input from a layer of bipolar cells, represented by individual rectified subunits. Additionally, both the bipolar and ganglion cells have separate contrast gain control mechanisms. This model captured the responses to our different motion stimuli over a wide range of contrasts, speeds, and locations. The alert response to motion onset, together with its computational model, introduces a new mechanism of sophisticated motion processing that occurs early in the visual system.

Features and functions of nonlinear spatial integration by retinal ganglion cells

Ganglion cells in the vertebrate retina integrate visual information over their receptive fields. They do so by pooling presynaptic excitatory inputs from typically many bipolar cells, which themselves collect inputs from several photoreceptors. In addition, inhibitory interactions mediated by horizontal cells and amacrine cells modulate the structure of the receptive field. In many models, this spatial integration is assumed to occur in a linear fashion. Yet, it has long been known that spatial integration by retinal ganglion cells also incurs nonlinear phenomena. Moreover, several recent examples have shown that nonlinear spatial integration is tightly connected to specific visual functions performed by different types of retinal ganglion cells. This work discusses these advances in understanding the role of nonlinear spatial integration and reviews recent efforts to quantitatively study the nature and mechanisms underlying spatial nonlinearities. These new insights point towards a critical role of nonlinearities within ganglion cell receptive fields for capturing responses of the cells to natural and behaviorally relevant visual stimuli. In the long run, nonlinear phenomena of spatial integration may also prove important for implementing the actual neural code of retinal neurons when designing visual prostheses for the eye.

Dynamic coding of temporal luminance variation

The range of variation in environmental stimuli is much larger than the visual system can represent. It is therefore sensible for the system to adjust its responses to the momentary input statistics of the environment, such as when our pupils contract to limit the light entering the eye. Previous evidence indicates that the visual system increasingly centers responses on the mean of the visual input and scales responses to its variation during adaptation. To what degree does adaptation to a stimulus varying in luminance over time result in such adjustment of responses? The first two experiments were designed to test whether sensitivity to changes in the amplitude and the mean of a 9.6° central patch varying sinusoidally in luminance at 0.6 Hz would increase or decrease with adaptation. This was also tested for a dynamic peripheral stimulus (random patches rotating on the screen) to test to what extent the effects uncovered in the first two experiments reflect retinotopic mechanisms. Sensitivity to changes in mean and amplitude of the temporal luminance variation increased sharply the longer the adaptation to the variation, both for the large patch and the peripheral patches. Adaptation to luminance variation leads to increased sensitivity to temporal luminance variation for both central and peripheral presentation, the latter result ruling retinotopic mechanisms out as sole explanations for the adaptation effects.

Dynamics of normalization underlying masking in human visual cortex

Stimulus visibility can be reduced by other stimuli that overlap the same region of visual space, a process known as masking. Here we studied the neural mechanisms of masking in humans using source-imaged steady state visual evoked potentials and frequency-domain analysis over a wide range of relative stimulus strengths of test and mask stimuli. Test and mask stimuli were tagged with distinct temporal frequencies and we quantified spectral response components associated with the individual stimuli (self terms) and responses due to interaction between stimuli (intermodulation terms). In early visual cortex, masking alters the self terms in a manner consistent with a reduction of input contrast. We also identify a novel signature of masking: a robust intermodulation term that peaks when the test and mask stimuli have equal contrast and disappears when they are widely different. We fit all of our data simultaneously with family of a divisive gain control models that differed only in their dynamics. Models with either very short or very long temporal integration constants for the gain pool performed worse than a model with an integration time of ∼30 ms. Finally, the absolute magnitudes of the response were controlled by the ratio of the stimulus contrasts, not their absolute values. This contrast-contrast invariance suggests that many neurons in early visual cortex code relative rather than absolute contrast. Together, these results provide a more complete description of masking within the normalization framework of contrast gain control and suggest that contrast normalization accomplishes multiple functional goals.

Perceptual measurement in schizophrenia: promising electrophysiology and neuroimaging paradigms from CNTRICS

The sixth meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) focused on selecting promising imaging paradigms for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of perception, the 2 constructs of interest were "gain control" and "visual integration." CNTRICS received 6 task nominations for imaging paradigms for gain control and 3 task nominations for integration. The breakout group for perception evaluated the degree to which each of these tasks met prespecified criteria. For gain control, the breakout group believed that one task (mismatch negativity) was already mature and was being incorporated into multisite clinical trials. The breakout group recommended that 1 visual task (steady-state visual evoked potentials to magnocellular- vs parvocellular-biased stimuli) and 2 auditory measures (an event-related potential (ERP) measure of corollary discharge and a functional magnetic resonance imaging (fMRI) version of prepulse inhibition of startle) be adapted for use in clinical trials in schizophrenia research. For visual integration, the breakout group recommended that fMRI and ERP versions of a contour integration test and an fMRI version of a coherent motion test be adapted for use in clinical trials. This manuscript describes the ways in which each of these tasks met the criteria used in the breakout group to evaluate and recommend tasks for further development.

Normalization as a canonical neural computation

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.

Stimulus-induced dissociation of neuronal firing rates and local field potential gamma power and its relationship to the resonance blood oxygen level-dependent signal in macaque primary visual cortex

The functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signal is regularly used to assign neuronal activity to cognitive function. Recent analyses have shown that the local field potential (LFP) gamma power is a better predictor of the fMRI BOLD signal than spiking activity. However, LFP gamma power and spiking activity are usually correlated, clouding the analysis of the neural basis of the BOLD signal. We show that changes in LFP gamma power and spiking activity in the primary visual cortex (V1) of the awake primate can be dissociated by using grating and plaid pattern stimuli, which differentially engage surround suppression and cross-orientation inhibition/facilitation within and between cortical columns. Grating presentation yielded substantial V1 LFP gamma frequency oscillations and significant multi-unit activity. Plaid pattern presentation significantly reduced the LFP gamma power while increasing population multi-unit activity. The fMRI BOLD activity followed the LFP gamma power changes, not the multi-unit activity. Inference of neuronal activity from the fMRI BOLD signal thus requires detailed a priori knowledge of how different stimuli or tasks activate the cortical network.

Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppression

Visual neurons can respond with extremely precise temporal patterning to visual stimuli that change on much slower time scales. Here, we investigate how the precise timing of cat thalamic spike trains-which can have timing as precise as 1 ms-is related to the stimulus, in the context of both artificial noise and natural visual stimuli. Using a nonlinear modeling framework applied to extracellular data, we demonstrate that the precise timing of thalamic spike trains can be explained by the interplay between an excitatory input and a delayed suppressive input that resembles inhibition, such that neuronal responses only occur in brief windows where excitation exceeds suppression. The resulting description of thalamic computation resembles earlier models of contrast adaptation, suggesting a more general role for mechanisms of contrast adaptation in visual processing. Thus, we describe a more complex computation underlying thalamic responses to artificial and natural stimuli that has implications for understanding how visual information is represented in the early stages of visual processing.

Contrast gain control abnormalities in idiopathic generalized epilepsy

OBJECTIVE

The origin of neural hyperexcitability underlying idiopathic generalized epilepsy (IGE) is not known. The objective of this study is to identify evidence of hyperexcitability in precisely measured visual evoked responses and to understand the nature of changes in excitation and inhibition that lead to altered responses in human patients with IGE.

METHODS

Steady-state visual-evoked potentials (VEPs) to contrast reversing gratings were recorded over a wide range of stimulus contrast. VEPs were analyzed at the pattern reversal rate using spectral analysis. Ten patients with IGE and 13 healthy subjects participated. All subjects had normal visual acuity and had no history of photic-induced seizures or photoparoxysmal electroencephalograph (EEG) activity.

RESULTS

At a group level, the amplitude of visual responses did not saturate at high stimulus contrast in patients, as it did in the control subjects. This reflects an abnormality in neuronal gain control. The VEPs did not have sufficient power to reliably distinguish patients from controls at an individual level. Parametric modeling using a standard gain control framework showed that the abnormality lay in reduced inhibition from neighboring neurons rather than increased excitatory response to the stimulus.

INTERPRETATION

Visual evoked responses reveal changes in a fundamental mechanism regulating neuronal sensitivity. These changes may give rise to hyperexcitability underlying generalized epilepsy.

Complex cell receptive fields: evidence for a hierarchical mechanism

Simple cells in the primary visual cortex have segregated ON and OFF subregions in their receptive fields, while complex cells have overlapping ON and OFF subregions. These two cell types form the extremes at each end of a continuum of receptive field types. Hubel and Wiesel in 1962 suggested a hierarchical scheme of processing whereby spatially offset simple cells drive complex cells. Simple and complex cells are often classified by their responses to moving sine wave gratings: simple cells have oscillatory responses while complex cells produce unmodulated responses. Here, using moving gratings as stimuli, we show that a significant number of cells that display low levels of response modulation at high contrasts demonstrate high levels of response modulation at low contrasts. Most often a drifting low contrast grating generates a large phasic response at the fundamental frequency of the grating (F(1)) and a smaller but significant phasic response that is approximately 180 deg out-of-phase with the F(1) component. We present several models capable of capturing the effects of stimulus contrast on complex cell responses. The model that best reproduces our experimental results is a variation of the classical hierarchical model. In our model several spatially offset simple cells provide input to a complex cell, with each simple cell exhibiting a different contrast response function. At low contrasts only one of these simple cells is sufficiently excited to reveal its receptive field properties. As contrast is increased additional spatially offset simple cells with higher contrast thresholds add their responses to the overall spiking activity.

Heterogeneous response dynamics in retinal ganglion cells: the interplay of predictive coding and adaptation

To make efficient use of their limited signaling capacity, sensory systems often use predictive coding. Predictive coding works by exploiting the statistical regularities of the environment--specifically, by filtering the sensory input to remove its predictable elements, thus enabling the neural signal to focus on what cannot be guessed. To do this, the neural filters must remove the environmental correlations. If predictive coding is to work well in multiple environments, sensory systems must adapt their filtering properties to fit each environment's statistics. Using the visual system as a model, we determine whether this happens. We compare retinal ganglion cell dynamics in two very different environments: white noise and natural. Because natural environments have more power than that of white noise at low temporal frequencies, predictive coding is expected to produce a suppression of low frequencies and an enhancement of high frequencies, compared with the behavior in a white-noise environment. We find that this holds, but only in part. First, predictive coding behavior is not uniform: most on cells manifest it, whereas off cells, on average, do not. Overlaid on this nonuniformity between cell classes is further nonuniformity within both cell classes. These findings indicate that functional considerations beyond predictive coding play an important role in shaping the dynamics of sensory adaptation. Moreover, the differences in behavior between on and off cell classes add to the growing evidence that these classes are not merely homogeneous mirror images of each other and suggest that their roles in visual processing are more complex than expected from the classic view.

The response dynamics of rabbit retinal ganglion cells to simulated blur

Retinal ganglion cells (RGCs) are highly sensitive to changes in contrast, which is crucial for the detection of edges in a visual scene. However, in the natural environment, edges do not just vary in contrast, but edges also vary in the degree of blur, which can be caused by distance from the plane of fixation, motion, and shadows. Hence, blur is as much a characteristic of an edge as luminance contrast, yet its effects on the responses of RGCs are largely unexplored.We examined the responses of rabbit RGCs to sharp edges varying by contrast and also to high-contrast edges varying by blur. The width of the blur profile ranged from 0.73 to 13.05 deg of visual angle. For most RGCs, blurring a high-contrast edge produced the same pattern of reduction of response strength and increase in latency as decreasing the contrast of a sharp edge. In support of this, we found a significant correlation between the amount of blur required to reduce the response by 50% and the size of the receptive fields, suggesting that blur may operate by reducing the range of luminance values within the receptive field. These RGCs cannot individually encode for blur, and blur could only be estimated by comparing the responses of populations of neurons with different receptive field sizes. However, some RGCs showed a different pattern of changes in latency and magnitude with changes in contrast and blur; these neurons could encode blur directly.We also tested whether the response of a RGC to a blurred edge was linear, that is, whether the response of a neuron to a sharp edge was equal to the response to a blurred edge plus the response to the missing spatial components that were the difference between a sharp and blurred edge. Brisk-sustained cells were more linear; however, brisk-transient cells exhibited both linear and nonlinear behavior.

The challenges natural images pose for visual adaptation

Advances in our understanding of natural image statistics and of gain control within the retinal circuitry are leading to new insights into the classic problem of retinal light adaptation. Here we review what we know about how rapid adaptation occurs during active exploration of the visual scene. Adaptational mechanisms must balance the competing demands of adapting quickly, locally, and reliably, and this balance must be maintained as lighting conditions change. Multiple adaptational mechanisms in different locations within the retina act in concert to accomplish this task, with lighting conditions dictating which mechanisms dominate.

Population coding under normalization

A common computation in visual cortex is the divisive normalization of responses by a pooled signal of the activity of cells within its neighborhood. From a geometrical point of view, normalization constraints the population response to high-contrast stimuli to lie on the surface of a high-dimensional sphere. Here we study the implications this constraint imposes on the representation of a circular variable, such as the orientation of a visual stimulus. New results are derived for the infinite dimensional case of a homogeneous populations of neurons with identical tuning curves but different orientation preferences. An important finding is that the ability of the population to discriminate between any two orientations depends exclusively on the Fourier amplitude spectrum of the orientation tuning curve. We also study the problem of encoding by a finite set of neurons. A central result is that, under normalization, optimal encoding can be achieved by a finite number of neurons with heterogeneous tuning curves. In other words, increasing the number of neurons in the population does not always allow for an improved population code. These results are used to estimate the number of neurons involved in the coding of orientation at one position in the visual field. If the cortex were to code orientation optimally, we find that a small number (∼4) of neurons should suffice.

Pattern motion selectivity of spiking outputs and local field potentials in macaque visual cortex

The dorsal pathway of the primate visual cortex is involved in the processing of motion signals that are useful for perception and behavior. Along this pathway, motion information is first measured by the primary visual cortex (V1), which sends specialized projections to extrastriate regions such as the middle temporal area (MT). Previous work with plaid stimuli has shown that most V1 neurons respond to the individual components of moving stimuli, whereas some MT neurons are capable of estimating the global motion of the pattern. In this work, we show that the majority of neurons in the medial superior temporal area (MST), which receives input from MT, have this pattern-selective property. Interestingly, the local field potentials (LFPs) measured simultaneously with the spikes often exhibit properties similar to that of the presumptive feedforward input to each area: in the high-gamma frequency band, the LFPs in MST are as component selective as the spiking outputs of MT, and MT LFPs have plaid responses that are similar to the spiking outputs of V1. In the lower LFP frequency bands (beta and low gamma), component selectivity is very common, and pattern selectivity is almost entirely absent in both MT and MST. Together, these results suggest a surprisingly strong link between the sensory tuning of cortical LFPs and afferent inputs, with important implications for the interpretation of imaging studies and for models of cortical function.

Development of contrast mechanisms in humans: a VEP study

PURPOSE

The visual system undergoes major developmental changes in infancy and continues to mature throughout childhood. This study was designed to investigate the developmental change in the contrast response function and the neural mechanisms that contribute to this change.

METHODS

Participants were 29 infants from 15 to 28 weeks of age, two children, one adolescent, and nine adults. Visual evoked potentials were elicited by horizontal square-wave gratings contrast-reversed at 7.5 Hz. Spatial frequencies of 0.75 and 1.5 cpd were used, and contrast was swept in seven octave steps from 1 to 64% with an initial step at 0%. There were 10 runs of each condition (8.5 s each). Fourier analysis was used to derive amplitude and phase of the dominant (second harmonic) frequency component in the response, which were then plotted vs. contrast. The empirical contrast response functions were fitted using a nonlinear model, which generates estimates of shunting inhibition, conductance, and the integrative time constant in the system.

RESULTS

Typically, in comparison to older observers, contrast response functions in infants are relatively linear with increases in contrast, and they exhibit little if any contrast gain control (amplitude compression and phase advance with increasing contrast). Time constants in infants are longer than in adults, and infants demonstrate less decrease in time constant values with increasing contrast than do adults.

CONCLUSIONS

These results are consistent with greater shunting inhibition in the visual cortex of older observers.

Inter-ocular contrast normalization in human visual cortex

The brain combines visual information from the two eyes and forms a coherent percept, even when inputs to the eyes are different. However, it is not clear how inputs from the two eyes are combined in visual cortex. We measured fMRI responses to single gratings presented monocularly, or pairs of gratings presented monocularly or dichoptically with several combinations of contrasts. Gratings had either the same orientation or orthogonal orientations (i.e., plaids). Observers performed a demanding task at fixation to minimize top-down modulation of the stimulus-evoked responses. Dichoptic presentation of compatible gratings (same orientation) evoked greater activity than monocular presentation of a single grating only when contrast was low (<10%). A model that assumes linear summation of activity from each eye failed to explain binocular responses at 10% contrast or higher. However, a model with binocular contrast normalization, such that activity from each eye reduced the gain for the other eye, fitted the results very well. Dichoptic presentation of orthogonal gratings evoked greater activity than monocular presentation of a single grating for all contrasts. However, activity evoked by dichoptic plaids was equal to that evoked by monocular plaids. Introducing an onset asynchrony (stimulating one eye 500 ms before the other, which under attentive vision results in flash suppression) had no impact on the results; the responses to dichoptic and monocular plaids were again equal. We conclude that when attention is diverted, inter-ocular suppression in V1 can be explained by a normalization model in which the mutual suppression between orthogonal orientations does not depend on the eye of origin, nor on the onset times, and cross-orientation suppression is weaker than inter-ocular (same orientation) suppression.