Thresholds and latencies of retinal ganglion cell responses in cats to local stimulation of various parts of their receptive field

Depending on their responses to separate stimulation of the center and periphery of the receptive field, all ganglion cells of the cat retina can be subdivided into two types: ON-center (OFF-periphery) and OFF-center (ON-periphery). By all the parameters studied these ON- and OFF-systems were symmetrical. This apparently reflects, first, the equality of informativeness of illumination and darkening of individual areas of the visual field and, second, adaptation in order to widen the dynamic range of the visual channel of information transmission. Thresholds of unit responses to stimulation of the periphery and center of their receptive fields were identical. The latent periods of the unit responses were much longer in the first case than in the second. This is regarded as providing the functional basis for discrimination between "central" and "peripheral" unit responses by higher structures.Institute of Control Problems, Academy of Sciences of the USSR. Translated from Neirofiziologiya, Vol. 3, No. 6, pp. 644–649, November–December, 1971.     

A neural network model for the emergence of grating cells

A correlation-based learning (CBL) neural network model is proposed, which simulates the emergence of grating cells as well as some of their response characteristics to periodic pattern stimuli. These cells, found in areas V1 and V2 of the visual cortex of monkeys, respond vigorously and exclusively to bar gratings of a preferred orientation and periodicity. Their non-linear behaviour differentiates grating cells from other orientation-selective cells, which show linear spatial frequency filtering. Received: 9 June 1997 / Accepted in revised form: 9 February 1998     

A model of direction-selective “simple” cells in the visual cortex based on inhibition asymmetry

Direction selectivity is a prominent feature of single units in the central visual pathway of cat and monkey. Various mechanisms have been proposed for the generation of this property. Experimental evidence suggests that intracortical inhibition is a major factor contributing to direction selectivity.We have developed a one-dimensional computer model for direction selective simple cells in the visual cortex under two basic assumptions: 1) Inhibition is exerted upon a cortical cell by neighboring cells from either side within a retinotopic array, 2) The relative strength of inhibition from both neighbors can be varied, interneurons always having larger time constants than the simple cells. Summation in the model is linear, but is followed by an essential non-linearity. ON- and/or OFF-center cells of the sustained type (X-cells) are used as an input to the simple cells.The computer simulation demonstrates that various subtypes of direction-selective simple cells in area 17, as described by Schiller et al. (1976), can be generated by different amounts of inhibition asymmertry, different delays and by different spatial arrangements of the input. Only one type of input (ON or OFF) is required to generate direction selectivity, but a greater variety of cell subtypes is created by combining both. Length-summation, contributing to orientation selectivity, was not considered in this one-dimensional model.     

Simulation of visual cortex development under lid-suture conditions: enhancement of response specificity by a reverse-Hebb rule in the absence of spatially patterned input

In this report, I show that a reverse-Hebb synaptic modification rule leads to the enhancement of response specificity of simulated visual cortex neurons in the absence of spatial patterning of the afferent activity. Although it is clear that receptive fields in the visual cortex can be modified by experience, many studies have shown a substantial increase of response specificity in cats deprived of pattern vision by lid suture, leading some to conclude that receptive field properties are essentially hard-wired. The hard-wired vs. experience-dependent controversy can be resolved by assuming that while Hebb-type plasticity is responsible for developmental synaptic changes, the organization of presynaptic activity which exists under conditions of visual deprivation is sufficient to drive the neurons towards greater specificity (Linsker 1986a–c; Miller 1989, 1992; Miller et al. 1989). As a reverse-Hebb rule enhances response specificity by balancing the push-pull system of ON- and OFF-center afferents, the sufficient condition is that the activity of ON- and OFF-center retinal ganglion cells be negatively correlated, a condition which will be met by diffuse illumination as seen through sutured eyelids. Unlike the models of Linsker and Miller and colleagues, which are based on a standard-Hebb rule, the model presented here does not require the presence of a Mexican hat spatial patterning of the afferent correlations, which has not been observed experimentally.     

An intracellular study of space and time representation in primary visual cortical receptive fields

In contrast with previous knowledge based on extracellular recordings, the recent development of intracellular techniques in vivo (sharp electrode or ‘blind patch’) ideally allows experimenters to analyze and dissect the contribution of feedforward and lateral connectivity in the functional expression of a synaptic ‘integration field’. We will present recent data which demonstrate that the visual receptive field of cortical neurons described at the level of subthreshold synaptic events extends over much larger regions of the visual field than previously thought, and that the capacity of cells to amplify subthreshold responses depends on the immediate past history of their membrane potential. Our data suggest that visual cortical receptive fields should not be considered as a fixed entity but more as a dynamic field of integration and association. Two types of dynamics can be argued for: 1) the spatial structure of the minimal discharge field (defined by suprathreshold activation of the cell) can be profoundly reorganized at least during development and most probably during selective phases of learning under the control of activity-dependent mechanisms. Adaptive changes in visual responses are thought to reflect long-lasting potentiation and/or depression of synaptic efficacies conveying ON- and OFF-center information; and 2) during sensory processing, reconfiguration of synaptic weights may be achieved on a much faster time-scale and linke to non-linear properties of the postsynaptic membrane as well as that of recruited networks. Association of information available in the central part of the receptive field (RF) and of input coming from the reputedly ‘unresponsive’ regions surrounding it, or arising simultaneously from different parts of the visual field, might be suppressive in certain cases and capable of boosting hidden responses in other cases, depending on the global stimulus configuration.     

Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model

We have built a phenomenological spiking model of the cat early visual system comprising the retina, the Lateral Geniculate Nucleus (LGN) and V1’s layer 4, and established four main results (1) When exposed to videos that reproduce with high fidelity what a cat experiences under natural conditions, adjacent Retinal Ganglion Cells (RGCs) have spike-time correlations at a short timescale (~30 ms), despite neuronal noise and possible jitter accumulation. (2) In accordance with recent experimental findings, the LGN filters out some noise. It thus increases the spike reliability and temporal precision, the sparsity, and, importantly, further decreases down to ~15 ms adjacent cells’ correlation timescale. (3) Downstream simple cells in V1’s layer 4, if equipped with Spike Timing-Dependent Plasticity (STDP), may detect these fine-scale cross-correlations, and thus connect principally to ON- and OFF-centre cells with Receptive Fields (RF) aligned in the visual space, and thereby become orientation selective, in accordance with Hubel and Wiesel (Journal of Physiology 160:106–154, 1962) classic model. Up to this point we dealt with continuous vision, and there was no absolute time reference such as a stimulus onset, yet information was encoded and decoded in the relative spike times. (4) We then simulated saccades to a static image and benchmarked relative spike time coding and time-to-first spike coding w.r.t. to saccade landing in the context of orientation representation. In both the retina and the LGN, relative spike times are more precise, less affected by pre-landing history and global contrast than absolute ones, and lead to robust contrast invariant orientation representations in V1.     

Pooling strategies in V1 can account for the functional and structural diversity across species

Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high selectivity in simple cells to low selectivity in complex cells. Various computational models have suggested a possible link between the presence of phase invariant cells and the existence of orientation maps in higher mammals’ V1. These models, however, do not explain the emergence of complex cells in animals that do not show orientation maps. In this study, we build a theoretical model based on a convolutional network called Sparse Deep Predictive Coding (SDPC) and show that a single computational mechanism, pooling, allows the SDPC model to account for the emergence in V1 of complex cells with or without that of orientation maps, as observed in distinct species of mammals. In particular, we observed that pooling in the feature space is directly related to the orientation map formation while pooling in the retinotopic space is responsible for the emergence of a complex cells population. Introducing different forms of pooling in a predictive model of early visual processing as implemented in SDPC can therefore be viewed as a theoretical framework that explains the diversity of structural and functional phenomena observed in V1.     

Corticofugal feedback can reduce the visual latency of responses to antagonistic stimuli

 A biophysically realistical model of the primary visual pathway is designed, including feedback connections from the visual cortex to the lateral geniculate nucleus (LGN) – the so-called corticofugal pathway. The model comprises up to 10 000 retina and LGN cells divided into the ON and the OFF pathway according to their contrast response characteristics. An additional 6000 cortical simple cells are modeled. Apart from the direct excitatory afferent pathway we include strong mutual inhibition between the ON and the OFF subsystems. In addition, we propose a novel type of paradoxical corticofugal connection pattern which links ON dominated cortical simple cells to OFF-center LGN cells and vice versa. In accordance with physiological findings these connections are weakly excitatory and do not interfere with the steady-state responses to constant illumination, because during the steady-state inhibition arising from the active pathway effectively silences the nonstimulated pathway. At the moment of a contrast reversal the effect of the paradoxical connection pattern comes into play and the depolarization of the previously silent channel is accelerated, leading to a latency reduction of up to 4 ms using moderate synaptic weights. With increased weights reductions of more than 10 ms can be achieved. We introduce different synaptic characteristics for the feedback (AMPA, NMDA, AMPA+NMDA) and show that the strongest latency reduction is obtained for a combination of the membrane channels (i.e., AMPA+NMDA). The effect of the proposed paradoxical connection pattern is self-regulating; because the levels of inhibition and paradoxical excitation are always driven by the same inputs (strong inhibition is counterbalanced by a stronger paradoxical excitation and vice versa). In addition, the latency reduction for a contrast inversion which ends at a small absolute contrast level (small contrast step) is stronger than the reduction for an inversion with large final contrast (large contrast step). This leads to a more pronounced reduction in the reaction times for weak stimuli. Thus, reaction time differences for different contrast steps are smoothed out. Received: 22 January 1996/Accepted in revised form: 20 May 1996     

Binding by temporal structure in multiple feature domains of an oscillatory neuronal network

An important step in visual processing is the segregation of objects in a visual scene from one another and from the embedding background. According to current theories of visual neuroscience, the different features of a particular object are represented by cells which are spatially distributed across multiple visual areas in the brain. The segregation of an object therefore requires the unique identification and integration of the pertaining cells which have to be “bound” into one assembly coding for the object in question. Several authors have suggested that such a binding of cells could be achieved by the selective synchronization of temporally structured responses of the neurons activated by features of the same stimulus. This concept has recently gained support by the observation of stimulus-dependent oscillatory activity in the visual system of the cat, pigeon and monkey. Furthermore, experimental evidence has been found for the formation and segregation of synchronously active cell assemblies representing different stimuli in the visual field. In this study, we investigate temporally structured activity in networks with single and multiple feature domains. As a first step, we examine the formation and segregation of cell assemblies by synchronizing and desynchronizing connections within a single feature module. We then demonstrate that distributed assemblies can be appropriately bound in a network comprising three modules selective for stimulus disparity, orientation and colour, respectively. In this context, we address the principal problem of segregating assemblies representing spatially overlapping stimuli in a distributed architecture. Using synchronizing as well as desynchronizing mechanisms, our simulations demonstrate that the binding problem can be solved by temporally correlated responses of cells which are distributed across multiple feature modules. Received: 25 March 1993/Accepted in revised form: 8 September 1993     

Recurrent V1–V2 interaction in early visual boundary processing

A majority of cortical areas are connected via feedforward and feedback fiber projections. In feedforward pathways we mainly observe stages of feature detection and integration. The computational role of the descending pathways at different stages of processing remains mainly unknown. Based on empirical findings we suggest that the top-down feedback pathways subserve a context-dependent gain control mechanism. We propose a new computational model for recurrent contour processing in which normalized activities of orientation selective contrast cells are fed forward to the next processing stage. There, the arrangement of input activation is matched against local patterns of contour shape. The resulting activities are subsequently fed back to the previous stage to locally enhance those initial measurements that are consistent with the top-down generated responses. In all, we suggest a computational theory for recurrent processing in the visual cortex in which the significance of local measurements is evaluated on the basis of a broader visual context that is represented in terms of contour code patterns. The model serves as a framework to link physiological with perceptual data gathered in psychophysical experiments. It handles a variety of perceptual phenomena, such as the local grouping of fragmented shape outline, texture surround and density effects, and the interpolation of illusory contours. Received: 28 October 1998 / Accepted in revised form: 19 March 1999     

A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model

Simple cells in primary visual cortex are believed to extract local contour information from a visual scene. The 2D Gabor function (GF) model has gained particular popularity as a computational model of a simple cell. However, it short-cuts the LGN, it cannot reproduce a number of properties of real simple cells, and its effectiveness in contour detection tasks has never been compared with the effectiveness of alternative models. We propose a computational model that uses as afferent inputs the responses of model LGN cells with center–surround receptive fields (RFs) and we refer to it as a Combination of Receptive Fields (CORF) model. We use shifted gratings as test stimuli and simulated reverse correlation to explore the nature of the proposed model. We study its behavior regarding the effect of contrast on its response and orientation bandwidth as well as the effect of an orthogonal mask on the response to an optimally oriented stimulus. We also evaluate and compare the performances of the CORF and GF models regarding contour detection, using two public data sets of images of natural scenes with associated contour ground truths. The RF map of the proposed CORF model, determined with simulated reverse correlation, can be divided in elongated excitatory and inhibitory regions typical of simple cells. The modulated response to shifted gratings that this model shows is also characteristic of a simple cell. Furthermore, the CORF model exhibits cross orientation suppression, contrast invariant orientation tuning and response saturation. These properties are observed in real simple cells, but are not possessed by the GF model. The proposed CORF model outperforms the GF model in contour detection with high statistical confidence (RuG data set: p < 10⁻⁴, and Berkeley data set: p < 10⁻⁴). The proposed CORF model is more realistic than the GF model and is more effective in contour detection, which is assumed to be the primary biological role of simple cells.     

A model of activity-dependent anatomical inhibitory plasticity applied to the mammalian auditory system

We construct a model of activity-dependent, anatomical inhibitory plasticity. We apply the model to the mammalian auditory system. Specifically, we model the activity-dependent topographic refinement of inhibitory projections in the auditory brain stem, and we construct an anatomically abstract model of binaural band formation in the primary auditory cortex involving the segregation of different populations of inhibitory and excitatory afferents. Issues raised and predictions made include the nature of interactions between excitatory and inhibitory afferents innervating the same population of target cells, and the possibility that pharmacological manipulations of the developing primary auditory cortex might induce a shift in the periodicity of binaural bands. Any model of inhibitory plasticity must confront the issue of postulating mechanisms underlying such plasticity. In order to attempt to understand, at least theoretically, what the mechanisms underlying inhibitory plasticity might be, we propose the existence of a new class of neurotrophic factors that promote neurite outgrowth from and mediate competitive interactions between inhibitory afferents. We suppose that such factors are up-regulated by hyperpolarisation and down-regulated by depolarisation. Furthermore, we suppose that their activity-dependent release from target cells depends on Cl⁻ influx. Such factors are therefore assumed to be the physiological inverse of such factors as nerve growth factor and brain-derived neurotrophic factor, which are up-regulated by depolarisation and down-regulated by hyperpolarisation, with their activity-dependent release depending on Na⁺, and not Ca²⁺, influx. Received: 16 December 1997 / Accepted in revised form: 3 April 1998     

The influence of cortical feature maps on the encoding of the orientation of a short line

The inhomogeneous distribution of the receptive fields of cortical neurons influences the cortical representation of the orientation of short lines seen in visual images. We construct a model of the response of populations of neurons in the human primary visual cortex by combining realistic response properties of individual neurons and cortical maps of orientation and location preferences. The encoding error, which characterizes the difference between the parameters of a visual stimulus and their cortical representation, is calculated using Fisher information as the square root of the variance of a statistically efficient estimator. The error of encoding orientation varies considerably with the location and orientation of the short line stimulus as modulated by the underlying orientation preference map. The average encoding error depends only weakly on the structure of the orientation preference map and is much smaller than the human error of estimating orientation measured psychophysically. From this comparison we conclude that the actual mechanism of orientation perception does not make efficient use of all the information available in the neuronal responses and that it is the decoding of visual information from neuronal responses that limits psychophysical performance. Action Editor: Terrence Sejnowski     

Endogenous elicitor-like effects of alginate on physiological activities of plant cells

 The effects of alginate on the physiological activities of plant cells were studied. Addition of alginate oligomer (AO) to the suspension culture of Catharanthus roseus L. or Wasabia japonica cells promoted the production of antibiotic enzymes such as 5′-phosphodiesterase or chitinase respectively. Ajmalicine (a secondary metabolite) production by C. roseus CP3 cells was also promoted when AO was added to the suspension culture. On the basis of these results, we assumed that alginate is an elicitor-like substance. We therefore compared the effect of AO on C. roseus L. and W. japonica cells with those of chitosan oligomer (CO) and oligo-galacturonic acid (OGA), which are well known as an exogenous elicitor and endogenous elicitor respectively. The effects of various concentrations of AO, OGA, and CO on the physiological activities, membrane permeability and protoplast formation of C. roseus L. or W. japonica cells were investigated. AO and OGA showed similar physiological effects, which were quite different from those of CO. Since alginate appeared to have similar effects to galacturonic acid, we concluded that alginate acts as an endogenous elicitor. Both alginate and galacturonic acid are uronic acids, and we considered their structural similarity. The effects of esterification of the carboxylic groups of alginate by propylene oxide were also studied. The greater the degree of esterification, the less the secretion of 5′-phosphodiesterase. Hence we assumed that carboxylic groups have an important role in the initiation of the elicitation reaction in plant cells, as shown in the case of galacturonic acid. Received: 18 January 1999 / Received revision: 2 April 1999 / Accepted: 1 May 1999     

Combined Hebbian development of geniculocortical and lateral connectivity in a model of primary visual cortex

We present a network model of visual map development in layer 4 of primary visual cortex. Our model comprises excitatory and inhibitory spiking neurons. The input to the network consists of correlated spike trains to mimick the activity of neurons in the lateral geniculate nucleus (LGN). An activity-driven Hebbian learning mechanism governs the development of both the network's lateral connectivity and feedforward projections from LGN to cortex. Plasticity of inhibitory synapses has been included into the model so as to control overall cortical activity. Even without feedforward input, Hebbian modification of the excitatory lateral connections can lead to the development of an intracortical orientation map. We have found that such an intracortical map can guide the development of feedforward connections from LGN to cortical simple cells so that the structure of the final feedforward orientation map is predetermined by the intracortical map. In a scenario in which left- and right-eye geniculocortical inputs develop sequentially one after the other, the resulting maps are therefore very similar, provided the intracortical connectivity remains unaltered. This may explain the outcome of so-called reverse lid-suture experiments, where animals are reared so that both eyes never receive input at the same time, but the orientation maps measured separately for the two eyes are nevertheless nearly identical. Received: 20 December 1999 / Accepted in revised form: 9 June 2000     

Motor-maps, navigation and implicit space representation in the hippocampus

Multiple sensory-motor maps located in the brainstem and the cortex are involved in spatial orientation. Guiding movements of eyes, head, neck and arms they provide an approximately linear relation between target distance and motor response. This involves especially the superior colliculus in the brainstem and the parietal cortex. There, the natural frame of reference follows from the retinal representation of the environment. A model of navigation is presented that is based on the modulation of activity in those sensory-motor maps. The actual mechanism chosen was gain-field modulation, a process of multimodal integration that has been demonstrated in the parietal cortex and superior colliculus, and was implemented as attraction to visual cues (colour). Dependent on the metric of the sensory-motor map, the relative attraction to these cues implemented as gain field modulation and their position define a fixed point attractor on the plane for locomotive behaviour. The actual implementation used Kohonen-networks in a variant of reinforcement learning that are well suited to generate such topographically organized sensory-motor maps with roughly linear visuo-motor response characteristics. In the following, it was investigated how such an implicit coding of target positions by gain-field parameters might be represented in the hippocampus formation and under what conditions a direction-invariant space representation can arise from such retinotopic representations of multiple cues. Information about the orientation in the plane—as could be provided by head direction cells—appeared to be necessary for unambiguous space representation in our model in agreement with physiological experiments. With this information, Gauss-shaped “place-cells” could be generated, however, the representation of the spatial environment was repetitive and clustered and single cells were always tuned to the gain-field parameters as well     

Horizontal organization of orientation-sensitive cells in primate visual cortex

In the visual cortex of the monkey the horizontal organization of the preferred orientations of orientation-selective cells follows two opposing rules:(1) neighbors tend to have similar orientation preferences, and(2) many different orientations are observed in a local region. We have described a classification for orientation maps based on the types of topological singularities and the spacing of these singularities relative to the cytochrome oxidase blobs. Using the orientation drift rate as a measure we have compared simulated orientation maps to published records of horizontal electrode recordings.     

Visual Receptive Field Properties of Neurons in the Mouse Lateral Geniculate Nucleus

The lateral geniculate nucleus (LGN) is increasingly regarded as a “smart-gating” operator for processing visual information. Therefore, characterizing the response properties of LGN neurons will enable us to better understand how neurons encode and transfer visual signals. Efforts have been devoted to study its anatomical and functional features, and recent advances have highlighted the existence in rodents of complex features such as direction/orientation selectivity. However, unlike well-researched higher-order mammals such as primates, the full array of response characteristics vis-à-vis its morphological features have remained relatively unexplored in the mouse LGN. To address the issue, we recorded from mouse LGN neurons using multisite-electrode-arrays (MEAs) and analysed their discharge patterns in relation to their location under a series of visual stimulation paradigms. Several response properties paralleled results from earlier studies in the field and these include centre-surround organization, size of receptive field, spontaneous firing rate and linearity of spatial summation. However, our results also revealed “high-pass” and “low-pass” features in the temporal frequency tuning of some cells, and greater average contrast gain than reported by earlier studies. In addition, a small proportion of cells had direction/orientation selectivity. Both “high-pass” and “low-pass” cells, as well as direction and orientation selective cells, were found only in small numbers, supporting the notion that these properties emerge in the cortex. ON- and OFF-cells showed distinct contrast sensitivity and temporal frequency tuning properties, suggesting parallel projections from the retina. Incorporating a novel histological technique, we created a 3-D LGN volume model explicitly capturing the morphological features of mouse LGN and localising individual cells into anterior/middle/posterior LGN. Based on this categorization, we show that the ON/OFF, DS/OS and linear response properties are not regionally restricted. Our study confirms earlier findings of spatial pattern selectivity in the LGN, and builds on it to demonstrate that relatively elaborate features are computed early in the visual pathway.     

Online learning and stimulus-driven responses of neurons in visual cortex

In understanding how visual scene is processed in visual cortex, it has been an intriguing problem for theoretical and experimental neuroscientists to examine the relationship between visual stimuli and the induced responses of visual cortex. In particular, it is less explored whether and how the collective responses of visual neurons are patterned to reflect the geometrical regularities. In this paper, through a computation model and statistical analysis, we show that the orientation preference maps induced from correlated visual stimuli exhibit geometrical regularities similar as observed in natural images.     

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

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