Local correlation-based circuitry can account for responses to multi-grating stimuli in a model of cat V1

Response sub-additivity and variability quenching in visual cortex

Sub-additivity and variability are ubiquitous response motifs in the primary visual cortex (V1). Response sub-additivity enables the construction of useful interpretations of the visual environment, whereas response variability indicates the factors that limit the precision with which the brain can do this. There is increasing evidence that experimental manipulations that elicit response sub-additivity often also quench response variability. Here, we provide an overview of these phenomena and suggest that they may have common origins. We discuss empirical findings and recent model-based insights into the functional operations, computational objectives and circuit mechanisms underlying V1 activity. These different modelling approaches all predict that response sub-additivity and variability quenching often co-occur. The phenomenology of these two response motifs, as well as many of the insights obtained about them in V1, generalize to other cortical areas. Thus, the connection between response sub-additivity and variability quenching may be a canonical motif across the cortex.

Development of Cross-Orientation Suppression and Size Tuning and the Role of Experience

Many sensory neural circuits exhibit response normalization, which occurs when the response of a neuron to a combination of multiple stimuli is less than the sum of the responses to the individual stimuli presented alone. In the visual cortex, normalization takes the forms of cross-orientation suppression and surround suppression. At the onset of visual experience, visual circuits are partially developed and exhibit some mature features such as orientation selectivity, but it is unknown whether cross-orientation suppression is present at the onset of visual experience or requires visual experience for its emergence. We characterized the development of normalization and its dependence on visual experience in female ferrets. Visual experience was varied across the following three conditions: typical rearing, dark rearing, and dark rearing with daily exposure to simple sinusoidal gratings (14-16 h total). Cross-orientation suppression and surround suppression were noted in the earliest observations, and did not vary considerably with experience. We also observed evidence of continued maturation of receptive field properties in the second month of visual experience: substantial length summation was observed only in the oldest animals (postnatal day 90); evoked firing rates were greatly increased in older animals; and direction selectivity required experience, but declined slightly in older animals. These results constrain the space of possible circuit implementations of these features.SIGNIFICANCE STATEMENT The development of the brain depends on both nature-factors that are independent of the experience of an individual animal-and nurture-factors that depend on experience. While orientation selectivity, one of the major response properties of neurons in visual cortex, is already present at the onset of visual experience, it is unknown whether response properties that depend on interactions among multiple stimuli develop without experience. We find that the properties of cross-orientation suppression and surround suppression are present at eye opening, and do not depend on visual experience. Our results are consistent with the idea that a majority of the basic properties of sensory neurons in primary visual cortex are derived independent of the experience of an individual animal.

Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1

Neurons in the primary visual cortex are known for responding vigorously but with high variability to classical stimuli such as drifting bars or gratings. By contrast, natural scenes are encoded more efficiently by sparse and temporal precise spiking responses. We used a conductance-based model of the visual system in higher mammals to investigate how two specific features of the thalamo-cortical pathway, namely push-pull receptive field organization and fast synaptic depression, can contribute to this contextual reshaping of V1 responses. By comparing cortical dynamics evoked respectively by natural vs. artificial stimuli in a comprehensive parametric space analysis, we demonstrate that the reliability and sparseness of the spiking responses during natural vision is not a mere consequence of the increased bandwidth in the sensory input spectrum. Rather, it results from the combined impacts of fast synaptic depression and push-pull inhibition, the later acting for natural scenes as a form of “effective” feed-forward inhibition as demonstrated in other sensory systems. Thus, the combination of feedforward-like inhibition with fast thalamo-cortical synaptic depression by simple cells receiving a direct structured input from thalamus composes a generic computational mechanism for generating a sparse and reliable encoding of natural sensory events.

Canonical computations of cerebral cortex

The idea that there is a fundamental cortical circuit that performs canonical computations remains compelling though far from proven. Here we review evidence for two canonical operations within sensory cortical areas: a feedforward computation of selectivity; and a recurrent computation of gain in which, given sufficiently strong external input, perhaps from multiple sources, intracortical input largely, but not completely, cancels this external input. This operation leads to many characteristic cortical nonlinearities in integrating multiple stimuli. The cortical computation must combine such local processing with hierarchical processing across areas. We point to important changes in moving from sensory cortex to motor and frontal cortex and the possibility of substantial differences between cortex in rodents vs. species with columnar organization of selectivity.

The effects of short-term synaptic depression at thalamocortical synapses on orientation tuning in cat V1

We examine the effects of short-term synaptic depression on the orientation tuning of the LGN input to simple cells in cat primary visual cortex (V1). The total LGN input has an untuned component as well as a tuned component, both of which grow with stimulus contrast. The untuned component is not visible in the firing rate responses of the simple cells. The suppression of the contribution of the untuned input component to firing rate responses is key to establishing orientation selectivity and its invariance with stimulus contrast. It has been argued that synaptic depression of LGN inputs could contribute to the selective suppression of the untuned component and thus contribute to the tuning observed in simple cells. We examine this using a model fit to the depression observed at thalamocortical synapses in-vivo, and compare this to an earlier model fit based on in-vitro observations. We examine the tuning of both the conductance and the firing rate induced in simple cells by the net LGN input. We find that depression causes minimal suppression of the untuned component. The primary effect of depression is to cause the contrast response curve to saturate at lower contrasts without differentially affecting the tuned vs. untuned components. This effect is slightly weaker for in-vivo vs. in-vitro parameters. Thus, synaptic depression of LGN inputs does not appreciably contribute to the orientation tuning of V1 simple cells.

Analysis of the stabilized supralinear network

We study a rate-model neural network composed of excitatory and inhibitory neurons in which neuronal input-output functions are power laws with a power greater than 1, as observed in primary visual cortex. This supralinear input-output function leads to supralinear summation of network responses to multiple inputs for weak inputs. We show that for stronger inputs, which would drive the excitatory subnetwork to instability, the network will dynamically stabilize provided feedback inhibition is sufficiently strong. For a wide range of network and stimulus parameters, this dynamic stabilization yields a transition from supralinear to sublinear summation of network responses to multiple inputs. We compare this to the dynamic stabilization in the balanced network, which yields only linear behavior. We more exhaustively analyze the two-dimensional case of one excitatory and one inhibitory population. We show that in this case, dynamic stabilization will occur whenever the determinant of the weight matrix is positive and the inhibitory time constant is sufficiently small, and analyze the conditions for supersaturation, or decrease of firing rates with increasing stimulus contrast (which represents increasing input firing rates). In work to be presented elsewhere, we have found that this transition from supralinear to sublinear summation can explain a wide variety of nonlinearities in cerebral cortical processing.

Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

Short-term synaptic depression (STD) is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network and increasing during silent states. Here, we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, we studied how trains of synaptic potentials had lesser decay during periods of activity (UP states) than during silent periods (DOWN states), providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.

Feedforward origins of response variability underlying contrast invariant orientation tuning in cat visual cortex

Contrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.

Spatial attention in area V4 is mediated by circuits in primary visual cortex

The ability to covertly select visual stimuli in our environment based on their behavioral relevance is an important skill. Stimulus selection has been studied experimentally, at the single neuron as well as at the population level, by recording from the visual cortex of subjects performing attention-demanding tasks, but studies at the local circuit level are lacking. We conducted simulations of a primary visual cortex (V1) model to provide insight into the local circuit computation underlying stimulus selection in V4. Two small oriented rectangular bars were placed at different locations in the 4 by 4 degree visual field represented by the V1 model, such that they activated different V1 neurons but such that they were both inside the classical receptive field (CRF) of the same V4 neuron. The biased competition framework [Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193-222] makes predictions for the response of V4 neurons and the modulation thereof by spatial and feature attention. In our simulation of the V1 network, we obtained results consistent with these predictions for V4 when the model had long-range excitatory projections targeting inhibitory neurons and when spatial attention was mediated by a spatially restricted projection that either inhibited the inhibitory neurons or excited the excitatory neurons. Although it is not clear whether attention effects measured in V4 neurons are generated mostly by local circuits within V4, our simulations suggest that spatial attention at a resolution less than the size of the CRF of a V4 neuron is inherited from upstream areas like V1 and relies on circuits mediating surround suppression at the single neuron level. Furthermore, the model displayed global oscillations in the alpha frequency range (around 10 Hz), whose coherence was highest in the absence of visual stimulation, which is consistent with electroencephalograms recorded in humans. By contrast, when a stimulus was presented the alpha oscillation sped up and became less coherent, whereas at the single column level (40-480 cells) transient beta/gamma oscillations were observed with a frequency between 25 and 50 Hz.

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids

The visual response of a cell in the primary visual cortex (V1) to a drifting grating stimulus at the cell's preferred orientation decreases when a second, perpendicular, grating is superimposed. This effect is called masking. To understand the nonlinear masking effect, we model the response of Macaque V1 simple cells in layer 4Calpha to input from magnocellular Lateral Geniculate Nucleus (LGN) cells. The cortical model network is a coarse-grained reduction of an integrate-and-fire network with excitation from LGN input and inhibition from other cortical neurons. The input is modeled as a sum of LGN cell responses. Each LGN cell is modeled as the convolution of a spatio-temporal filter with the visual stimulus, normalized by a retinal contrast gain control, and followed by rectification representing the LGN spike threshold. In our model, the experimentally observed masking arises at the level of LGN input to the cortex. The cortical network effectively induces a dynamic threshold that forces the test grating to have high contrast before it can overcome the masking provided by the perpendicular grating. The subcortical nonlinearities and the cortical network together account for the masking effect.

In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices

In order to better understand the synaptic nature of the integration process operated by cortical neurons during sensory processing, it is necessary to devise quantitative methods which allow one to infer the level of conductance change evoked by the sensory stimulation and, consequently, the dynamics of the balance between excitation and inhibition. Such detailed measurements are required to characterize the static versus dynamic nature of the non-linear interactions triggered at the single cell level by sensory stimulus. This paper primarily reviews experimental data from our laboratory based on direct conductance measurements during whole-cell patch clamp recordings in two experimental preparations: (1) in vitro, during electrical stimulation in the visual cortex of the rat and (2) in vivo, during visual stimulation, in the primary visual cortex of the anaesthetized cat. Both studies demonstrate that shunting inhibition is expressed as well in vivo as in vitro. Our in vivo data reveals that a high level of diversity is observed in the degree of interaction (from linear to non-linear) and in the temporal interplay (from push-pull to synchronous) between stimulus-driven excitation (E) and inhibition (I). A detailed analysis of the E/I balance during evoked spike activity further shows that the firing strength results from a simultaneous decrease of evoked inhibition and increase of excitation. Secondary, the paper overviews the various computational methods used in the literature to assess conductance dynamics, measured in current clamp as well as in voltage clamp in different neocortical areas and species, and discuss the consistency of their estimations.

Origins of cross-orientation suppression in the visual cortex

The response of a neuron in striate cortex to an optimally oriented stimulus is suppressed by a superimposed orthogonal stimulus. The neural mechanism underlying this cross-orientation suppression (COS) may arise from intracortical or subcortical processes or from both. Recent studies of the temporal frequency and adaptation properties of COS suggest that depression at thalamo-cortical synapses may be the principal mechanism. To examine the possible role of synaptic depression in relation to COS, we measured the recovery time course of COS. We find it too rapid to be explained by synaptic depression. We also studied potential subcortical processes by measuring single cell contrast response functions for a population of LGN neurons. In general, contrast saturation is a consistent property of LGN neurons. Combined with rectifying nonlinearities in the LGN and spike threshold nonlinearities in visual cortex, contrast saturation in the LGN can account for most of the COS that is observed in the visual cortex.

Dynamics of suppression in macaque primary visual cortex

The response of a neuron in primary visual cortex (V1) to an optimal stimulus in its classical receptive field (CRF) can be reduced by the presence of an orthogonal mask, a phenomenon known as cross-orientation suppression. The presence of a parallel stimulus outside the CRF can have a similar effect, in this case known as surround suppression. We used a novel stimulus to probe the time course of cross-orientation suppression and found that it is very fast, starting even before the response to optimal excitatory stimuli. However, it occurs with some delay after the offset response, considered to be a measure of the earliest excitatory signals that reach the CRF. We also examined the time course of response to a stimulus presented outside the CRF and found that cross-orientation suppression begins substantially earlier than surround suppression measured in the same cells. Together, these findings suggest that cross-orientation suppression is attributable to either direct feedforward signal paths to V1 neurons or a circuit involving fast local interneurons within V1. Feedback from higher cortical areas is implicated in surround suppression, but our results make this an implausible mechanism for cross-orientation suppression. We conclude that suppression from inside and outside the CRF occur through different mechanisms.

Mechanisms underlying cross-orientation suppression in cat visual cortex

In simple cells of the cat primary visual cortex, null-oriented stimuli, which by themselves evoke no response, can completely suppress the spiking response to optimally oriented stimuli. This cross-orientation suppression has been interpreted as evidence for cross-orientation inhibition: synaptic inhibition among cortical cells with different preferred orientations. In intracellular recordings from simple cells, however, we found that cross-oriented stimuli suppressed, rather than enhanced, synaptic inhibition and, at the same time, suppressed synaptic excitation. Much of the suppression of excitation could be accounted for by the behavior of geniculate relay cells: contrast saturation and rectification in relay cell responses, when applied to a linear feed-forward model, predicted cross-orientation suppression of the modulation (F1) component of excitation evoked in simple cells. In addition, we found that the suppression of the spike output of simple cells was almost twice the suppression of their synaptic inputs. Thus, cross-orientation suppression, like orientation selectivity, is strongly amplified by threshold.

Short-term depression in thalamocortical synapses of cat primary visual cortex

Neurons in primary visual cortex exhibit several nonlinearities in their responses to visual stimuli, including response decrements to repeated stimuli, contrast-dependent phase advance, contrast saturation, and cross-orientation suppression. Thalamocortical synaptic depression has been implicated in these phenomena but has not been examined directly in visual cortex in vivo. We assessed depression of visual thalamocortical synapses in vivo using 20-100 Hz trains of electrical stimuli delivered to the LGN. Cortical cells receiving direct input from the LGN, identified by short latency and low jitter of LGN-evoked PSPs, showed moderate reductions in PSP amplitude during the fastest trains. Cells receiving indirect input from the thalamus via other cortical excitatory neurons show a marked reduction in PSP amplitude during a train, which could be explained either by synaptic depression in corticocortical synapses or by an inhibition-mediated suppression of the firing of their afferents. Reducing spontaneous activity in the LGN (by retinal blockade) unmasked additional depression at the thalamocortical synapse but only for the first stimulus in the train. That is, the first PSP was increased in amplitude relative to the unblocked condition, but subsequent responses were essentially unchanged. Thus, the synapses are maintained at significant levels of depression by spontaneous activity. These findings constrain the role that thalamocortical depression can play in shaping cortical responses to visual stimuli.

A nonlinear model of the behavior of simple cells in visual cortex

Despite their structured receptive fields (RFs) and the strong linear components in their responses, most simple cells in mammalian visual cortex exhibit nonlinear behaviors. Besides the contrast-response function, nonlinearities are evident in various types of failure at superposition tasks, in the disagreement between direction indices computed from drifting and counterphase flickering gratings, in various forms of response suppression (including end- and side-stopping, spatial-frequency-specific inhibition and cross-orientation inhibition), in the advance of phase with increasing contrast, and in phase-insensitive and frequency-doubled responses to counterphase flickering gratings. These behaviors suggest that nonlinearities are involved in the operation of simple cells, but current models fail to explain them. A quantitative model is presented here that purports to describe basic and common principles of operation for all visual cortical cells. Simple cells are described as receiving afferents from multiple subunits that differ in their individual RFs and temporal impulse responses (TIRs). Subunits are independent and perform a spatial integration across their RFs followed by halfwave rectification and temporal convolution with their TIRs. This parallel operation yields a set of temporal functions representing each subunit's contribution to the membrane potential of the host cell, whose final form is given by the weighted sum of all subunits' contributions. By varying the number of subunits and their particular characteristics, different instances of the model are obtained each of which displays a different set of behaviors. Extensive simulation results are presented that illustrate how all of the reported nonlinear behaviors of simple cells arise from these multi-subunit organizations.

Different roles for simple-cell and complex-cell inhibition in V1

Previously, we proposed a model of the circuitry underlying simple-cell responses in cat primary visual cortex (V1) layer 4. We argued that the ordered arrangement of lateral geniculate nucleus inputs to a simple cell must be supplemented by a component of feedforward inhibition that is untuned for orientation and responds to high temporal frequencies to explain the sharp contrast-invariant orientation tuning and low-pass temporal frequency tuning of simple cells. The temporal tuning also requires a significant NMDA component in geniculocortical synapses. Recent experiments have revealed cat V1 layer 4 inhibitory neurons with two distinct types of receptive fields (RFs): complex RFs with mixed ON/OFF responses lacking in orientation tuning, and simple RFs with normal, sharp-orientation tuning (although, some respond to all orientations). We show that complex inhibitory neurons can provide the inhibition needed to explain simple-cell response properties. Given this complex cell inhibition, antiphase or "push-pull" inhibition from tuned simple inhibitory neurons acts to sharpen spatial frequency tuning, lower responses to low temporal frequency stimuli, and increase the stability of cortical activity.

The effect of moving textures on the responses of cells in the cat's dorsal lateral geniculate nucleus

Neurons in the dorsal lateral geniculate nucleus (dLGN) of the anaesthetized cat were activated with test stimuli (flashing spots, counterphased gratings and moving bars) in the presence of a moving background texture. Moving texture alone produced mild excitation, as a result of stimulation of the receptive field centre. Fast moving coarse textures were more effective than fine slow moving textures. The predominant effect of texture motion, however, was to reduce the response to all test stimuli displayed in the receptive field centre. The effects were similar for X- and Y-like cells. In the case of flashed spots, the sustained response was more strongly suppressed than the transient response. The direction of motion of the texture and differences in the relative motion of bar and texture had no influence on the degree of suppression. These observations are similar to effects seen on cat retinal ganglion cells, and are probably a form of gain control. Such suppressive effects are transmitted to the cortex and are likely to be evoked by large gratings, textures and by natural stimuli, all of which activate extensive regions of the receptive field surround.

A synaptic explanation of suppression in visual cortex

The responses of neurons in the primary visual cortex (V1) are suppressed by mask stimuli that do not elicit responses if presented alone. This suppression is widely believed to be mediated by intracortical inhibition. As an alternative, we propose that it can be explained by thalamocortical synaptic depression. This explanation correctly predicts that suppression is monocular, immune to cortical adaptation, and occurs for mask stimuli that elicit responses in the thalamus but not in the cortex. Depression also explains other phenomena previously ascribed to intracortical inhibition. It explains why responses saturate at high stimulus contrast, whereas selectivity for orientation and spatial frequency is invariant with contrast. It explains why transient responses to flashed stimuli are nonlinear, whereas spatial summation is primarily linear. These results suggest that the very first synapses into the cortex, and not the cortical network, may account for important response properties of V1 neurons.

Suppression without inhibition in visual cortex

Neurons in primary visual cortex (V1) are thought to receive inhibition from other V1 neurons selective for a variety of orientations. Evidence for this inhibition is commonly found in cross-orientation suppression: responses of a V1 neuron to optimally oriented bars are suppressed by superimposed mask bars of different orientation. We show, however, that suppression is unlikely to result from intracortical inhibition. First, suppression can be obtained with masks drifting too rapidly to elicit much of a response in cortex. Second, suppression is immune to hyperpolarization (through visual adaptation) of cortical neurons responding to the mask. Signals mediating suppression might originate in thalamus, rather than in cortex. Thalamic neurons exhibit some suppression; additional suppression might arise from depression at thalamocortical synapses. The mechanisms of suppression are subcortical and possibly include the very first synapse into cortex.

Rapid adaptation to internal states as a coding strategy in visual cortex?

Adaptation is a prominent feature of biological neuronal systems. A common interpretation of adaptation in terms of function is that it provides flexibility for a neuronal system to perform well under varying external conditions, for example by adjusting the input/output relation of a sensory system with reference to the ensemble of stimuli the organism currently perceives. This interpretation, however, only applies if the time-scale of adaptation is slower than the time-scale at which the environment changes. Experimentally it is observed, however, that adaptation can be very rapid. Spike-frequency adaptation of cortical neurons, for example, occurs on a time-scale of approximately 100 ms. Here we show that those rapid adaptation processes can also be understood within the framework of information theory. We start with the hypothesis that neuronal codes are designed to optimize the information a neuronal representation conveys about an input stimulus for any increasing time window beginning with stimulus onset, and we show that this implies a rapid adaptation of the neuronal code on the time-scale of stimulus presentation. Adaptation, however, does not occur because the state of the environment changes. Rather it is a reaction to changes of the organisms own internal state, e.g. the level of noise in the neuronal representation. We apply this approach to a model of an orientation hypercolumn in the primary visual cortex, and predict that inter-columnar interactions should adapt on the time-scale of a typical fixation period ( approximately 300 ms).

Opponent inhibition: a developmental model of layer 4 of the neocortical circuit

We model the development of the functional circuit of layer 4 (the input-recipient layer) of cat primary visual cortex. The observed thalamocortical and intracortical circuitry codevelop under Hebb-like synaptic plasticity. Hebbian development yields opponent inhibition: inhibition evoked by stimuli anticorrelated with those that excite a cell. Strong opponent inhibition enables recognition of stimulus orientation in a manner invariant to stimulus contrast. These principles may apply to cortex more generally: Hebb-like plasticity can guide layer 4 of any piece of cortex to create opposition between anticorrelated stimulus pairs, and this enables recognition of specific stimulus patterns in a manner invariant to stimulus magnitude. Properties that are invariant across a cortical column are predicted to be those shared by opponent stimulus pairs; this contrasts with the common idea that a column represents cells with similar response properties.