Spectral characteristics of stimuli and responses in a complex receptive field]

Responses of a complex receptive field of visual cortex of the cat are determined by the energy of stimuli in the band pass of equivalent space frequency characteristic of the receptive field. This is a proof that the complex receptive fields are spatial frequency band pass filters.     

Sensory and behavioral properties of neurons in posterior parietal cortex of the awake, trained monkey.

Neurons in posterior parietal cortex of the awake, trained monkey respond to passive visual and/or somatosensory stimuli. In general, the receptive fields of these cells are large and nonspecific. When these neurons are studied during visually guided hand movements and eye movements, most of their activity can be accounted for by passive sensory stimulation. However, for some visual cells, the response to a stimulus is enhanced when it is to be the target for a saccadic eye movement. This enhancement is selective for eye movements into the visual receptive field since it does not occur with eye movements to other parts of the visual field. Cells that discharge in association with a visual fixation task have foveal receptive fields and respond to the spots of light used as fixation targets. Cells discharging selectively in association with different directions of tracking eye movements have directionally selective responses to moving visual stimuli. Every cell in our sample discharging in association with movement could be driven by passive sensory stimuli. We conclude that the activity of neurons in posterior parietal cortex is dependent on and indicative of external stimuli but not predictive of movement.     

Seeing beyond the receptive field in primary visual cortex

Recent studies on the response properties of neurons in primary visual cortex emphasize the dynamics and the complexities of facilitatory and suppressive interactions between the receptive field center and surrounding areas of visual space. These observations raise new questions about the circuitry responsible for receptive field surround effects and their contribution to visual perception.     

Perisaccadic Remapping and Rescaling of Visual Responses in Macaque Superior Colliculus

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

Neurons with visual receptive fields independent of eye position in the caudal section of the ventral bank of cat cruciate slucus

Neurons responding to tactile and visual stimulation were found in the caudal section of the cruciate slucus ventral bank in awake cats. Tactile receptive fields were located on the face, mainly around the mouth. Visual stimuli evoked a response when presented close to the tactile receptive field. It was found that the visual responses of these bimodal neurons located in layer VI of the cortex display spatial consistency. The position of these visual receptive fields remained constant through saccadic eye movements, while still linked to the tactile receptive field.Institute for Research into Information Transmission, Academy of Sciences of the USSR, Moscow. Translated from Neifofiziologiya, Vol. 18, No. 6, pp. 800–805, November–December, 1986.     

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.     

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.     

Inhibitory zones of receptive fields of the lateral geniculate body and visual cortex of the cat

Unit responses to moving strips were investigated. The organization of the inhibitory zones in the receptive fields of the lateral geniculate body and visual cortex of the cat was compared. The response in the receptive field of the lateral geniculate body was inhibited only during simultaneous stimulation of the excitatory and inhibitory zones of the field. Stimulation of the inhibitory zone in the receptive field of the visual cortex was effective for a long time (several hundreds of milliseconds) after stimulation of the excitatory zone. The inhibitory zones of the simple and complex receptive fields of the visual cortex differed significantly. An increase in the width of the strip above the optimal size reduced the inhibitory effect in the complex fields. This was not observed in the simple receptive fields. The functional and structural models of the receptive field of the visual cortex are discussed.I. P. Pavlov Institute of Physiology, Academy of Sciences of the USSR, Leningrad. Translated from Neirofiziologiya, Vol. 5, No. 2, pp. 201–209, March–April, 1973.     

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.     

Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images

The sparse coding hypothesis has enjoyed much success in predicting response properties of simple cells in primary visual cortex (V1) based solely on the statistics of natural scenes. In typical sparse coding models, model neuron activities and receptive fields are optimized to accurately represent input stimuli using the least amount of neural activity. As these networks develop to represent a given class of stimulus, the receptive fields are refined so that they capture the most important stimulus features. Intuitively, this is expected to result in sparser network activity over time. Recent experiments, however, show that stimulus-evoked activity in ferret V1 becomes less sparse during development, presenting an apparent challenge to the sparse coding hypothesis. Here we demonstrate that some sparse coding models, such as those employing homeostatic mechanisms on neural firing rates, can exhibit decreasing sparseness during learning, while still achieving good agreement with mature V1 receptive field shapes and a reasonably sparse mature network state. We conclude that observed developmental trends do not rule out sparseness as a principle of neural coding per se: a mature network can perform sparse coding even if sparseness decreases somewhat during development. To make comparisons between model and physiological receptive fields, we introduce a new nonparametric method for comparing receptive field shapes using image registration techniques.     

Functional characteristics of visual cortical neurons during local photic stimulation of their receptive fields in cats

A group of functional characteristics of 103 neurons in visual cortical area 17 was investigated in acute experiments on curarized, light-adapted cats during a change in various parameters of the local photic stimuli. The average threshold sensitivity of the neuron population was 32 dB (0.052 nit), the sharpness of orientation tuning was 37°, the critical summation time was 57 msec, and the reactivity recovery time 190 msec. Photic sensitivity was lower during light adaptation than during dark adaptation, orientation selectivity of the neurons was increased, temporal summation was lengthened, and the time required by the neuron to recovery from after-inhibition was shortened. Several properties of the cortical neurons depended on the accentricity of their receptive fields: Cells with centrally localized receptive fields on average had lower thresholds and shorter summation time and they recovered their reactivity more quickly; their activity was of a higher frequency and they more often generated short phasic discharges than neurons with receptive fields in the peripheral part of the visual field. The mechanisms responsible for changes in the properties of neurons in the central and peripheral visual channels during dark and light adaptation are discussed. The presence of several inhibitory subsystems in the cortex regulating unit activity in the primary visual projection area is postulated.     

Spontaneous retinal activity mediates development of ocular dominance columns and binocular receptive fields in v1

The mechanisms that give rise to ocular dominance columns (ODCs) during development are controversial. Early experiments indicated a key role for retinal activity in ODC formation. However, later studies showed that in those early experiments, the retinal activity perturbation was initiated after ODCs had already formed. Moreover, recent studies concluded that early eye removals do not impact ODC segregation. Here we blocked spontaneous retinal activity during the very early stages of ODC development. This permanently disrupted the anatomical organization of ODCs and led to a dramatic increase in receptive field size for binocular cells in primary visual cortex. Our data suggest that early spontaneous retinal activity conveys crucial information about whether thalamocortical axons represent one or the other eye and that this activity mediates binocular competition important for shaping receptive fields in primary visual cortex.     

Receptive fields of auditory cortical neurons in the cat

Receptive fields of auditory cortical neurons were studied by electrical stimulation of nerve fibers in different parts of the cochlea in cats anesthetized with pentobarbital. The dimensions of the receptive fields were shown to depend on the topographic arrangement of the neuron in the auditory cortex. The more caudad the neuron on the cortical projection of the cochlea in the primary auditory cortex, the more extensive its receptive field. The receptive fields were narrowest in the basal turn of the cochlea and were symmetrical with respect to their center. It is suggested that the region of finest discrimination of acoustic stimuli in cats is located in the basal region of the cochlea, i.e., in that part of its receptor system which has the narrowest receptive field and is represented by significantly more (than the middle and apical regions of the cochlea) nerve cells in the primary auditory cortex [1].A. A. Bogomolets Institute of Physiology, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Neirofiziologiya, Vol. 13, No. 5, pp. 467–473, September–October, 1981.     

Color sensitivity in the receptive fields of neurons of the squirrel visual cortex

Color-opponent properties in neurons of the primary visual cortex were investigated in the squirrel. All neurons responded to the presentation of both black and white visual stimuli and of colored stimuli — mainly to blue and green. In 65% of test neurons a response only occurred when blue and green stimuli were applied while the remaining cells partially responded to red. Neurons were divided into groups according to how they responded to the presentation of stimuli composed of black and white: whether nonselective, directionally selective, or orientationally selective (simple or complex). No color-opponent properties were found in any of these groups at receptive field level. The whole or parts of the receptive field responded similarly to the presentation of white, blue, or green stimuli of the same shape. The way in which the receptive fields were divided into on- and off-regions and between directional and orientational selectivity does not depend on the color of the visual stimuli. Findings are discussed with regard to the presence of opponent-color cells in squirrel retina and lateral geniculate body.A. N. Severtsov Institute of Evolutionary Morphology and Animal Ecology, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 17, No. 6, pp. 764–770, November–December, 1985.     

Receptive field dynamics of neurons in the cat visual cortex and lateral geniculate body

Spike responses of single neurons in the primary visual cortex and lateral geniculate body to random presentation of local photic stimuli in different parts of the receptive field of the cell were studied in acute experiments on curarized cats. Series of maps of receptive fields with time interval of 20 msec obtained by computer enabled the dynamics of the excitatory and inhibitory zones of the field to be assessed during development of on- and off-responses to flashes. Receptive fields of all cortical and lateral geniculate body neurons tested were found to undergo regular dynamic reorganization both after the beginning and after the end of action of the photic stimulus. During the latent period of the response no receptive field was found in the part of the visual field tested, but later a small zone of weak responses appeared only in the center of the field. Gradually (most commonly toward 60–100 msec after application of the stimulus) the zone of the responses widened to its limit, after which the recorded field began to shrink, ending with complete disappearance or disintegration into separate fragments. If two bursts of spikes were generated in response to stimulation, during the second burst the receptive field of the neuron changed in the same way. The effects described were clearly exhibited if the level of background illumination, the intensity of the test bars, their contrast with the background, duration, angles subtended, and orientation were varied, although the rate and degree of reorganization of the receptive field in this case changed significantly. The functional importance of the effect for coding of information about the features of a signal by visual cortical neurons is discussed.Institute of Higher Nervous Activity and Neurophysiology, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 14, No. 6, pp. 622–630, November–December, 1982.     

Orientation-selective neurons in the squirrel visual cortex

The organization of receptive fields of neurons sensitive to orientation of visual stimuli was investigated in the squirrel visual cortex. Neurons with mutually inhibitory on- and off-areas of the receptive field, with partially and completely overlapping excitatory and inhibitory mechanisms, were distinguished. Neurons of the second group are most typical. They exhibit orientation selectivity within the excitatory area of the receptive field because, if the stimulus widens in the zero direction, perpendicular to the preferred direction, lateral inhibition is much stronger than if it widens in the preferred direction. Additional inhibitory areas (outside the excitatory area) potentiate this inhibition and increase selectivity. It is suggested that there is no strict separation of simple (with separate excitatory and inhibitory mechanisms in the receptive field) and complex (with overlapping of these mechanisms) neurons in the squirrel visual cortex.A. N. Severtsov Institute of Evolutionary Morphology and Ecology of Animals, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 11, No. 6, pp. 540–549, November–December, 1979.     

The visual cortical association field: A Gestalt concept or a psychophysiological entity?

The receptive field of a visual neurone is classically defined as the region of space (or retina) where a visual stimulus evokes a change in its firing activity. Intracellular recordings in cat area 17 show that the visually evoked synaptic integration field extends over a much larger area than that established on the basis of spike activity. Synaptic depolarizing (dominant excitation) responses decrease in strength for stimuli that are flashed at increasing distances away from the centre of the discharge field, while their onset latency increases. A detailed spatio-temporal analysis of these electrophysiological data shows that subthreshold synaptic responses observed in the 'silent' surround of cortical receptive fields result from the intracortical spread of activation waves carried by slowly conducting horizontal axons within primary visual cortex. They also predict that a perceptual facilitation may occur when feedforward activation produced by the motion signal in the retina travels in phase in the primary visual cortex with the visually induced spread of horizontal activation. A psychophysical correlate has been obtained in humans, showing that apparent motion produced by a sequence of co-linear Gabor patches, known to preferentially activate V1 orientation selective cells, are perceived by human observers as much faster than non co-linear sequences of the same physical speed.     

Inhibitory components in the neuronal response of the lateral suprasylvian cortical area in the cat

Inhibitory components in the response evoked by presentation of mobile visual stimuli in neurons belonging to the lateral suprasylvian area of the cerebral cortex were investigated in cats. It was demonstrated by comparing poststimulus histograms of neuronal response to movement in two opposite directions that the location of discharge centers within the receptive fields changed in relation to movement direction. No spatial area giving rise to the inhibitory component of response could be found in any of the neurons with monotone stationary structure of their receptive fields. Findings from experiments involving techniques of stimulating a test area of the receptive field separately indicated that inhibitory components of response in neurons of the lateral suprasylvian area with monotone organization of the receptive field could represent inhibitory after-response following the neuronal excitation produced by the visual stimulus traveling across this field.L. A. Orbeli Institute of Physiology, Academy of Sciences of the Armenian SSR, Erevan. Translated from Neirofiziologiya, Vol. 19, No. 3, pp. 299–308, May–June, 1987.     

Computational model for perception of objects and motions

Perception of objects and motions in the visual scene is one of the basic problems in the visual system. There exist 'What' and 'Where' pathways in the superior visual cortex, starting from the simple cells in the primary visual cortex. The former is able to perceive objects such as forms, color, and texture, and the latter perceives 'where', for example, velocity and direction of spatial movement of objects. This paper explores brain-like computational architectures of visual information processing. We propose a visual perceptual model and computational mechanism for training the perceptual model. The compu- tational model is a three-layer network. The first layer is the input layer which is used to receive the stimuli from natural environments. The second layer is designed for representing the internal neural information. The connections between the first layer and the second layer, called the receptive fields of neurons, are self-adaptively learned based on principle of sparse neural representation. To this end, we introduce Kullback-Leibler divergence as the measure of independence between neural responses and derive the learning algorithm based on minimizing the cost function. The proposed algorithm is applied to train the basis functions, namely receptive fields, which are localized, oriented, and bandpassed. The resultant receptive fields of neurons in the second layer have the characteristics resembling that of simple cells in the primary visual cortex. Based on these basis functions, we further construct the third layer for perception of what and where in the superior visual cortex. The proposed model is able to perceive objects and their motions with a high accuracy and strong robustness against additive noise. Computer simulation results in the final section show the feasibility of the proposed perceptual model and high efficiency of the learning algorithm.     

Computational model for perception of objects and motions

Perception of objects and motions in the visual scene is one of the basic problems in the visual system. There exist ‘What’ and ‘Where’ pathways in the superior visual cortex, starting from the simple cells in the primary visual cortex. The former is able to perceive objects such as forms, color, and texture, and the latter perceives ‘where’, for example, velocity and direction of spatial movement of objects. This paper explores brain-like computational architectures of visual information processing. We propose a visual perceptual model and computational mechanism for training the perceptual model. The computational model is a three-layer network. The first layer is the input layer which is used to receive the stimuli from natural environments. The second layer is designed for representing the internal neural information. The connections between the first layer and the second layer, called the receptive fields of neurons, are self-adaptively learned based on principle of sparse neural representation. To this end, we introduce Kullback-Leibler divergence as the measure of independence between neural responses and derive the learning algorithm based on minimizing the cost function. The proposed algorithm is applied to train the basis functions, namely receptive fields, which are localized, oriented, and bandpassed. The resultant receptive fields of neurons in the second layer have the characteristics resembling that of simple cells in the primary visual cortex. Based on these basis functions, we further construct the third layer for perception of what and where in the superior visual cortex. The proposed model is able to perceive objects and their motions with a high accuracy and strong robustness against additive noise. Computer simulation results in the final section show the feasibility of the proposed perceptual model and high efficiency of the learning algorithm.