Visual Interactions Conform to Pattern Decorrelation in Multiple Cortical Areas

Neural responses to visual stimuli are strongest in the classical receptive field, but they are also modulated by stimuli in a much wider region. In the primary visual cortex, physiological data and models suggest that such contextual modulation is mediated by recurrent interactions between cortical areas. Outside the primary visual cortex, imaging data has shown qualitatively similar interactions. However, whether the mechanisms underlying these effects are similar in different areas has remained unclear. Here, we found that the blood oxygenation level dependent (BOLD) signal spreads over considerable cortical distances in the primary visual cortex, further than the classical receptive field. This indicates that the synaptic activity induced by a given stimulus occurs in a surprisingly extensive network. Correspondingly, we found suppressive and facilitative interactions far from the maximum retinotopic response. Next, we characterized the relationship between contextual modulation and correlation between two spatial activation patterns. Regardless of the functional area or retinotopic eccentricity, higher correlation between the center and surround response patterns was associated with stronger suppressive interaction. In individual voxels, suppressive interaction was predominant when the center and surround stimuli produced BOLD signals with the same sign. Facilitative interaction dominated in the voxels with opposite BOLD signal signs. Our data was in unison with recently published cortical decorrelation model, and was validated against alternative models, separately in different eccentricities and functional areas. Our study provides evidence that spatial interactions among neural populations involve decorrelation of macroscopic neural activation patterns, and suggests that the basic design of the cerebral cortex houses a robust decorrelation mechanism for afferent synaptic input.     

Contextual modulation of V1 receptive fields depends on their spatial symmetry

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

Coding of natural scenes in primary visual cortex

Natural scene coding in ferret visual cortex was investigated using a new technique for multi-site recording of neuronal activity from the cortical surface. Surface recordings accurately reflected radially aligned layer 2/3 activity. At individual sites, evoked activity to natural scenes was weakly correlated with the local image contrast structure falling within the cells' classical receptive field. However, a population code, derived from activity integrated across cortical sites having retinotopically overlapping receptive fields, correlated strongly with the local image contrast structure. Cell responses demonstrated high lifetime sparseness, population sparseness, and high dispersal values, implying efficient neural coding in terms of information processing. These results indicate that while cells at an individual cortical site do not provide a reliable estimate of the local contrast structure in natural scenes, cell activity integrated across distributed cortical sites is closely related to this structure in the form of a sparse and dispersed code.     

A Normalization Model of Attentional Modulation of Single Unit Responses

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

Spectral Characteristics of Phase Sensitivity and Discharge Rate of Neurons in the Ascending Tectofugal Visual System

Drifting gratings can modulate the activity of visual neurons at the temporal frequency of the stimulus. In order to characterize the temporal frequency modulation in the cat’s ascending tectofugal visual system, we recorded the activity of single neurons in the superior colliculus, the suprageniculate nucleus, and the anterior ectosylvian cortex during visual stimulation with drifting sine-wave gratings. In response to such stimuli, neurons in each structure showed an increase in firing rate and/or oscillatory modulated firing at the temporal frequency of the stimulus (phase sensitivity). To obtain a more complete characterization of the neural responses in spatiotemporal frequency domain, we analyzed the mean firing rate and the strength of the oscillatory modulations measured by the standardized Fourier component of the response at the temporal frequency of the stimulus. We show that the spatiotemporal stimulus parameters that elicit maximal oscillations often differ from those that elicit a maximal discharge rate. Furthermore, the temporal modulation and discharge-rate spectral receptive fields often do not overlap, suggesting that the detection range for visual stimuli provided jointly by modulated and unmodulated response components is larger than the range provided by a one response component.     

Characteristics of inhibition in receptive fields of the cat visual cortex

Unit responses of neurons of zone 17 in the cat striate cortex to stripes of different widths were studied. Changes in the number of spikes during different time intervals (cuts) from the beginning of the response were analyzed in relation to stimulus area. Comparison of the results with those obtained by the study of receptive fields of the lateral geniculate body showed a significant difference in the dynamics of inhibition between cortical and geniculate receptive fields. Similar results were obtained when cortical unit responses to simultaneous and consecutive appearance of two stripes in the receptive field, one in the excitatory zone and the other at the inhibitory periphery, were studied. Evidence of the longer duration of cortical inhibition also was obtained by the same technique. When both stripes were placed in the excitatory center of the field another feature of cortical inhibition was revealed: its dependence on the order of stimulus application. If the order of stimulus application coincided with the optimal direction of movement of the stripe for the given field, the unit response to the next stimulus was strongly facilitated by the action of the stimulus applied previously. Application of stimuli in the opposite order invoked inhibition. The sensitivity of inhibition to the order of stimulus application was observed in the center of the field; it diminished toward the periphery, where application of the stimuli in any order evokes inhibition of the response.Medical Academy, Sofia, Bulgaria, I. P. Pavlov Institute of Physiology, Academy of Sciences of the USSR, Leningrad. Translated from Neirofiziologiya, Vol. 9, No. 4, pp. 339–346, July–August, 1977.     

Attention modulates contextual influences in the primary visual cortex of alert monkeys

The response properties of cells in the primary visual cortex (V1) were measured while the animals directed their attention either to the position of the neuron's receptive field (RF), to a position away from the RF (focal attention), or to four locations in the visual field (distributed attention). Over the population, varying attentional state had no significant effect on the response to an isolated stimulus within the RF but had a large influence on the facilitatory effects of contextual lines. We propose that the attentional modulation of contextual effects represents a gating of long range horizontal connections within area V1 by feedback connections to V1 and that this gating provides a mechanism for shaping responses under attention to stimulus configuration.     

Attentional modulation strength in cortical area MT depends on stimulus contrast

The attentional modulation of sensory information processing in the visual system is the result of top-down influences, which can cause a multiplicative modulation of the firing rate of sensory neurons in extrastriate visual cortex, an effect reminiscent of the bottom-up effect of changes in stimulus contrast. This similarity could simply reflect the multiplicity of both effects. But, here we show that in direction-selective neurons in monkey visual cortical area MT, stimulus and attentional effects share a nonlinearity. These neurons show higher response gain for both contrast and attentional changes for intermediate contrast stimuli and smaller gain for low- and high-contrast stimuli. This finding suggests a close relationship between the neural encoding of stimulus contrast and the modulating effect of the behavioral relevance of stimuli.     

Retinotopic maps, spatial tuning, and locations of human visual areas in surface coordinates characterized with multifocal and blocked FMRI designs

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies.     

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

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

Covariation between Spike and LFP Modulations Revealed with Focal and Asynchronous Stimulation of Receptive Field Surround in Monkey Primary Visual Cortex

A focal visual stimulus outside the classical receptive field (RF) of a V1 neuron does not evoke a spike response by itself, and yet evokes robust changes in the local field potential (LFP). This subthreshold LFP provides a unique opportunity to investigate how changes induced by surround stimulation leads to modulation of spike activity. In the current study, two identical Gabor stimuli were sequentially presented with a variable stimulus onset asynchrony (SOA) ranging from 0 to 100 ms: the first (S1) outside the RF and the second (S2) over the RF of primary visual cortex neurons, while trained monkeys performed a fixation task. This focal and asynchronous stimulation of the RF surround enabled us to analyze the modulation of S2-evoked spike activity and covariation between spike and LFP modulation across SOA. In this condition, the modulation of S2-evoked spike response was dominantly facilitative and was correlated with the change in LFP amplitude, which was pronounced for the cells recorded in the upper cortical layers. The time course of covariation between the SOA-dependent spike modulation and LFP amplitude suggested that the subthreshold LFP evoked by the S1 can predict the magnitude of upcoming spike modulation.     

A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields

Sparse coding algorithms trained on natural images can accurately predict the features that excite visual cortical neurons, but it is not known whether such codes can be learned using biologically realistic plasticity rules. We have developed a biophysically motivated spiking network, relying solely on synaptically local information, that can predict the full diversity of V1 simple cell receptive field shapes when trained on natural images. This represents the first demonstration that sparse coding principles, operating within the constraints imposed by cortical architecture, can successfully reproduce these receptive fields. We further prove, mathematically, that sparseness and decorrelation are the key ingredients that allow for synaptically local plasticity rules to optimize a cooperative, linear generative image model formed by the neural representation. Finally, we discuss several interesting emergent properties of our network, with the intent of bridging the gap between theoretical and experimental studies of visual cortex.     

Modulation of V1 Spike Response by Temporal Interval of Spatiotemporal Stimulus Sequence

The spike activity of single neurons of the primary visual cortex (V1) becomes more selective and reliable in response to wide-field natural scenes compared to smaller stimuli confined to the classical receptive field (RF). However, it is largely unknown what aspects of natural scenes increase the selectivity of V1 neurons. One hypothesis is that modulation by surround interaction is highly sensitive to small changes in spatiotemporal aspects of RF surround. Such a fine-tuned modulation would enable single neurons to hold information about spatiotemporal sequences of oriented stimuli, which extends the role of V1 neurons as a simple spatiotemporal filter confined to the RF. In the current study, we examined the hypothesis in the V1 of awake behaving monkeys, by testing whether the spike response of single V1 neurons is modulated by temporal interval of spatiotemporal stimulus sequence encompassing inside and outside the RF. We used two identical Gabor stimuli that were sequentially presented with a variable stimulus onset asynchrony (SOA): the preceding one (S1) outside the RF and the following one (S2) in the RF. This stimulus configuration enabled us to examine the spatiotemporal selectivity of response modulation from a focal surround region. Although S1 alone did not evoke spike responses, visual response to S2 was modulated for SOA in the range of tens of milliseconds. These results suggest that V1 neurons participate in processing spatiotemporal sequences of oriented stimuli extending outside the RF.     

The local and non-local components of the local field potential in awake primate visual cortex

The Local Field Potential (LFP) is the analog signal recorded from a microelectrode inserted into cortex, typically in the frequency band of approximately 1 to 200 Hz. Here visual stimuli were flashed on in the receptive fields of primary visual cortical neurons in awake behaving macaques, and both isolated single units (neurons) and the LFP signal were recorded from the same unipolar microelectrode. The fall-off of single unit activity as a visual stimulus was moved from near the center to near the edge of the receptive field paralleled the fall-off of the stimulus-locked (evoked) LFP response. This suggests that the evoked LFP strongly reflects local neuronal activity. However, the evoked LFP could be significant even when the visual stimulus was completely outside the receptive field and the single unit response had fallen to zero, although this phenomenon was variable. Some of the non-local components of the LFP may be related to the slow distributed, or non-retinotopic, LFP signal previously observed in anesthetized animals. The induced (not time-locked to stimulus onset) component of the LFP showed significant increases only for stimuli within the receptive field of the single units. While the LFP primarily reflects local neuronal activity, it can also reflect neuronal activity at more distant sites, although these non-local components are typically more variable, slower, and weaker than the local components.     

A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields

Computational models of primary visual cortex have demonstrated that principles of efficient coding and neuronal sparseness can explain the emergence of neurones with localised oriented receptive fields. Yet, existing models have failed to predict the diverse shapes of receptive fields that occur in nature. The existing models used a particular "soft" form of sparseness that limits average neuronal activity. Here we study models of efficient coding in a broader context by comparing soft and "bard" forms of neuronal sparseness. As a result of our analyses, we propose a novel network model for visual cortex. The model forms efficient visual representations in which the number of active neurones, rather than mean neuronal activity, is limited. This form of hard sparseness also economises cortical resources like synaptic memory and metabolic energy. Furthermore, our model accurately predicts the distribution of receptive field shapes found in the primary visual cortex of cat and monkey.     

A specialized area in limbic cortex for fast analysis of peripheral vision

In primates, prostriata is a small area located between the primary visual cortex (V1) and the hippocampal formation. Prostriata sends connections to multisensory and high-order association areas in the temporal, parietal, cingulate, orbitofrontal, and frontopolar cortices. It is characterized by a relatively simple histological organization, alluding to an early origin in mammalian evolution. Here we show that prostriata neurons in marmoset monkeys exhibit a unique combination of response properties, suggesting a new pathway for rapid distribution of visual information in parallel with the traditionally recognized dorsal and ventral streams. Whereas the location and known connections of prostriata suggest a high-level association area, its response properties are unexpectedly simple, resembling those found in early stages of the visual processing: neurons have robust, nonadapting responses to simple stimuli, with latencies comparable to those found in V1, and are broadly tuned to stimulus orientation and spatiotemporal frequency. However, their receptive fields are enormous and form a unique topographic map that emphasizes the far periphery of the visual field. These results suggest a specialized circuit through which stimuli in peripheral vision can bypass the elaborate hierarchy of extrastriate visual areas and rapidly elicit coordinated motor and cognitive responses across multiple brain systems.     

Adaptation to stimulus contrast and correlations during natural visual stimulation

In this study, we characterize the adaptation of neurons in the cat lateral geniculate nucleus to changes in stimulus contrast and correlations. By comparing responses to high- and low-contrast natural scene movie and white noise stimuli, we show that an increase in contrast or correlations results in receptive fields with faster temporal dynamics and stronger antagonistic surrounds, as well as decreases in gain and selectivity. We also observe contrast- and correlation-induced changes in the reliability and sparseness of neural responses. We find that reliability is determined primarily by processing in the receptive field (the effective contrast of the stimulus), while sparseness is determined by the interactions between several functional properties. These results reveal a number of adaptive phenomena and suggest that adaptation to stimulus contrast and correlations may play an important role in visual coding in a dynamic natural environment.     

Traveling Waves and the Processing of Weakly Tuned Inputs in a Cortical Network Module

Recent studies have shown that local cortical feedback can havean important effect on the response of neurons in primary visualcortex to the orientation of visual stimuli. In this work, westudy the role of the cortical feedback in shaping thespatiotemporal patterns of activity in cortex. Two questionsare addressed: one, what are the limitations on the ability ofcortical neurons to lock their activity to rotatingoriented stimuli within a single receptive field? Two, can thelocal architecture of visual cortex lead to the generation ofspontaneous traveling pulses of activity? We study theseissues analytically by a population-dynamic model of ahypercolumn in visual cortex. The order parameter thatdescribes the macroscopic behavior of the network is thetime-dependent population vector of the network. We firststudy the network dynamics under the influence of a weakly tunedinput that slowly rotates within the receptive field. We showthat if the cortical interactions have strong spatialmodulation, the network generates a sharply tuned activityprofile that propagates across the hypercolumn in a path thatis completely locked to the stimulus rotation. The resultantrotating population vector maintains a constant angular lagrelative to the stimulus, the magnitude of which grows with thestimulus rotation frequency. Beyond a critical frequency thepopulation vector does not lock to the stimulus but executes aquasi-periodic motion with an average frequency that is smallerthan that of the stimulus. In the second part we consider thestable intrinsic state of the cortex under the influence of isotropic stimulation. We show that if the local inhibitoryfeedback is sufficiently strong, the network does not settleinto a stationary state but develops spontaneous travelingpulses of activity. Unlike recent models of wave propagation incortical networks, the connectivity pattern in our model isspatially symmetric, hence the direction of propagation ofthese waves is arbitrary. The interaction of these waves withan external-oriented stimulus is studied. It is shown that thesystem can lock to a weakly tuned rotating stimulus if thestimulus frequency is close to the frequency of the intrinsic wave.     

Neuronal selectivity,population sparseness,and ergodicity in the inferior temporal visual cortex

The sparseness of the encoding of stimuli by single neurons and by populations of neurons is fundamental to understanding the efficiency and capacity of representations in the brain, and was addressed as follows. The selectivity and sparseness of firing to visual stimuli of single neurons in the primate inferior temporal visual cortex were measured to a set of 20 visual stimuli including objects and faces in macaques performing a visual fixation task. Neurons were analysed with significantly different responses to the stimuli. The firing rate distribution of 36% of the neurons was exponential. Twenty-nine percent of the neurons had too few low rates to be fitted by an exponential distribution, and were fitted by a gamma distribution. Interestingly, the raw firing rate distribution taken across all neurons fitted an exponential distribution very closely. The sparseness a ^s or selectivity of the representation of the set of 20 stimuli provided by each of these neurons (which takes a maximal value of 1.0) had an average across all neurons of 0.77, indicating a rather distributed representation. The sparseness of the representation of a given stimulus by the whole population of neurons, the population sparseness a ^p, also had an average value of 0.77. The similarity of the average single neuron selectivity a ^s and population sparseness for any one stimulus taken at any one time a ^p shows that the representation is weakly ergodic. For this to occur, the different neurons must have uncorrelated tuning profiles to the set of stimuli.