Receptive field properties of near neighbor orientation selective neurons in the visual cortex: a modeling study

The primary visual cortex is organized into clusters of cells having similar receptive fields (RFs). A purely feedforward model has been shown to produce realistic simple cell receptive fields. The modeled cells capture a wide range of receptive field properties of orientation selective cortical cells. We have analyzed the responses of 78 nearby cell pairs to study which RF properties are clustered. Orientation preference shows strongest clustering. Orientation tuning width (hwhh) and tuning height (spikes/sec) at the preferred orientation are not as tightly clustered. Spatial frequency is also not as tightly clustered and RF phase has the least clustering. Clustering property of orientation preference, orientation tuning height and width depend on the location of cells in the orientation map. No such location dependence is observed for spatial frequency and RF phase. Our results agree well with experimental data.     

A functional model of the wiring of the simple cells of visual cortex

A computer model of the simple cells in the mammalian visual cortex was constructed. The model cells received inputs from a great number of isopolar centre/surround cells assumed to be located in the lateral geniculate nucleus (LGN). The distribution of input to the model simple cells was either inhibitory/excitatory or inhibitory/excitatory/inhibitory. Such arrangements produced receptive fields containing four or five consecutively antagonistic subfields. Responses produced by the model cells to different types of stimuli (periodical as well as nonperiodical) were obtained and compared to responses of living cells reported from various laboratories under comparable stimulus conditions. In all the situations tested, the responses of the model cells corresponded qualitatively very well to those of living cells. It was seen that the same wiring mechanism was able to account for orientation selectivity, spatial frequency filtering, various phase relationships between stimulus and response, subfield orientational selectivity, and slight end-inhibition. Furthermore, the receptive fields of the model simple cells closely resemble Gabor functions.     

猫外膝体神经元非寻常的方位调谐特性——Ⅰ、在正常猫的研究

在九只成年猫上用玻璃电极记录了单个外膝体神经元对不同方位的移动正弦光栅刺激的反应共详细测定了４００个细胞的方位调谐特性。少数外膝体神经元具有非寻常的方位调谐特性,包括：具蝴蝶状调谐曲线的方位调谐特性;双调谐的方位调谐特性和最优方位随刺激光栅空间频率的改变而变化的方位调谐特性。这些细胞非寻常的方位调谐特性往往伴随着非寻常的空间频率调谐特性。空们的方位调谐特性和空间频率调谐特性都不能用Ｓｏｏｄａｋ等提     

Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex

In the primate visual pathway, orientation tuning of neurons is first observed in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientation tuned, but some V1 neurons are quite selective. Two main classes of theoretical models have been offered to explain orientation selectivity: feedforward models, in which inputs from spatially aligned LGN cells are summed together by one cortical neuron; and feedback models, in which an initial weak orientation bias due to convergent LGN input is sharpened and amplified by intracortical feedback. Recent data on the dynamics of orientation tuning, obtained by a cross-correlation technique, may help to distinguish between these classes of models. To test this possibility, we simulated the measurement of orientation tuning dynamics on various receptive field models, including a simple Hubel-Wiesel type feedforward model: a linear spatiotemporal filter followed by an integrate-and-fire spike generator. The computational study reveals that simple feedforward models may account for some aspects of the experimental data but fail to explain many salient features of orientation tuning dynamics in V1 cells. A simple feedback model of interacting cells is also considered. This model is successful in explaining the appearance of Mexican-hat orientation profiles, but other features of the data continue to be unexplained.     

Independent component filters of natural images compared with simple cells in primary visual cortex.

Properties of the receptive fields of simple cells in macaque cortex were compared with properties of independent component filters generated by independent component analysis (ICA) on a large set of natural images. Histograms of spatial frequency bandwidth, orientation tuning bandwidth, aspect ratio and length of the receptive fields match well. This indicates that simple cells are well tuned to the expected statistics of natural stimuli. There is no match, however, in calculated and measured distributions for the peak of the spatial frequency response: the filters produced by ICA do not vary their spatial scale as much as simple cells do, but are fixed to scales close to the finest ones allowed by the sampling lattice. Possible ways to resolve this discrepancy are discussed.     

A multi-stage model for fundamental functional properties in primary visual cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (～4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.     

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons'' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception.     

Orientation selectivity of visual cortical neurons at different stimulus intensities in cats

Orientation selectivity of 24 neurons in area 17 of the visual cortex at different intensities of test bars of light, flashing against a constant light background in the center of the receptive field, was investigated in acute experiments on immobilized cats. Five neurons were invariant in orientation tuning to stimulus intensity (contrast): Although the magnitude of the response and acuteness of orientation selectivity were modified, preferential orientation was unchanged. More than half of the cells studied (13) were classed as noninvariant, for their preferential orientation was significantly shifted by 22–90° with a change in contrast. Small shifts of the peak of orientation selectivity, not statistically significant, were observed for the other neurons. Invariant neurons, unlike noninvariant, were characterized by preferential horizontal and vertical orientation, a lower frequency of spontaneous and evoked discharges, and the more frequent presence of receptive fields of simple type. The mechanisms of the change of orientation selectivity during contrast variation and also the different use of the two types of cells in orientation detection operations are discussed.     

Neuronal selectivity and local map structure in visual cortex

The organization of primary visual cortex (V1) into functional maps makes individual cells operate in a variety of contexts. For instance, some neurons lie in regions of fairly homogeneous orientation preference (iso-orientation domains), while others lie in regions with a variety of preferences (e.g., pinwheel centers). We asked whether this diversity in local map structure correlates with the degree of selectivity of spike responses. We used a combination of imaging and electrophysiology to reveal that neurons in regions of homogeneous orientation preference have much sharper tuning. Moreover, in both monkeys and cats, a common principle links the structure of the orientation map, on the spatial scale of dendritic integration, to the degree of selectivity of individual cells. We conclude that neural computation is not invariant across the cortical surface. This finding must factor into future theories of receptive field wiring and map development.     

Orientation and spatiotemporal tuning of cells in the primary visual cortex of an Australian marsupial,the wallaby<Emphasis Type="Italic"> Macropus eugenii</Emphasis>

The metatherians (marsupials) have been separated from eutherians (placentals) for approximately 135 million years. It might, therefore, be expected that significant independent evolution of the visual system has occurred. The present paper describes for the first time the orientation, direction and spatiotemporal tuning of neurons in the primary visual cortex of an Australian marsupial, the wallaby Macropus eugenii. The stimuli consisted of spatial sinusoidal gratings presented within apertures covering the classical receptive fields of the cells. The neurons can be classified as those with clear ON and OFF zones and those with less well-defined receptive field structures. Seventy-percent of the total cells encountered were strongly orientation selective (tuning functions at half height were less than 45 degrees ). The preferred orientations were evenly distributed throughout 360 degrees for cells with uniform receptive fields but biased towards the vertical and horizontal for cells with clear ON-OFF zones. Many neurons gave directional responses but only a small percentage of them (4%) showed motion opponent properties (i.e. they were excited by motion in one direction and actively inhibited by motion in the opposite direction). The median peak temporal tuning for cells with clear ON-OFF zones and those without were 3 Hz and 6 Hz, respectively. The most common peak spatial frequency tuning for the two groups were 2 cycles per degree and 0.5 cycles per degree, respectively. Spatiotemporal tuning was not always the same for preferred and antipreferred direction motion. In general, the physiology of the wallaby cortex was similar to well studied eutherian mammals suggesting either convergent evolution or a highly conserved architecture that stems from a common therian ancestor.     

A cooperation and competition based simple cell receptive field model and study of feed-forward linear and nonlinear contributions to orientation selectivity

We present a model for development of orientation selectivity in layer IV simple cells. Receptive field (RF) development in the model, is determined by diffusive cooperation and resource limited competition guided axonal growth and retraction in geniculocortical pathway. The simulated cortical RFs resemble experimental RFs. The receptive field model is incorporated in a three-layer visual pathway model consisting of retina, LGN and cortex. We have studied the effect of activity dependent synaptic scaling on orientation tuning of cortical cells. The mean value of hwhh (half width at half the height of maximum response) in simulated cortical cells is 58° when we consider only the linear excitatory contribution from LGN. We observe a mean improvement of 22.8° in tuning response due to the non-linear spiking mechanisms that include effects of threshold voltage and synaptic scaling factor.     

Development of spatiotemporal receptive fields of simple cells: I. Model formulation

A model for the development of spatiotemporal receptive fields of simple cells in the visual cortex is proposed. The model is based on the 1990 hypothesis of Saul and Humphrey that the convergence of four types of input onto a cortical cell, viz. non-lagged ON and OFF inputs and lagged ON and OFF inputs, underlies the spatial and temporal structure of the receptive fields. It therefore explains both orientation and direction selectivity of simple cells. The response properties of the four types of input are described by the product of linear spatial and temporal response functions. Extending the 1994 model of one of the authors (K.D. Miller), we describe the development of spatiotemporal receptive fields as a Hebbian learning process taking into account not only spatial but also temporal correlations between the different inputs. We derive the correlation functions that drive the development both for the period before and after eye-opening and demonstrate how the joint development of orientation and direction selectivity can be understood in the framework of correlation-based learning. Our investigation is split into two parts that are presented in two papers. In the first, the model for the response properties and for the development of direction-selective receptive fields is presented. In the second paper we present simulation results that are compared with experimental data, and also provide a first analysis of our model. Received: 18 June 1997 / Accepted: 16 September 1997     

A Push-Pull CORF Model of a Simple Cell with Antiphase Inhibition Improves SNR and Contour Detection

We propose a computational model of a simple cell with push-pull inhibition, a property that is observed in many real simple cells. It is based on an existing model called Combination of Receptive Fields or CORF for brevity. A CORF model uses as afferent inputs the responses of model LGN cells with appropriately aligned center-surround receptive fields, and combines their output with a weighted geometric mean. The output of the proposed model simple cell with push-pull inhibition, which we call push-pull CORF, is computed as the response of a CORF model cell that is selective for a stimulus with preferred orientation and preferred contrast minus a fraction of the response of a CORF model cell that responds to the same stimulus but of opposite contrast. We demonstrate that the proposed push-pull CORF model improves signal-to-noise ratio (SNR) and achieves further properties that are observed in real simple cells, namely separability of spatial frequency and orientation as well as contrast-dependent changes in spatial frequency tuning. We also demonstrate the effectiveness of the proposed push-pull CORF model in contour detection, which is believed to be the primary biological role of simple cells. We use the RuG (40 images) and Berkeley (500 images) benchmark data sets of images with natural scenes and show that the proposed model outperforms, with very high statistical significance, the basic CORF model without inhibition, Gabor-based models with isotropic surround inhibition, and the Canny edge detector. The push-pull CORF model that we propose is a contribution to a better understanding of how visual information is processed in the brain as it provides the ability to reproduce a wider range of properties exhibited by real simple cells. As a result of push-pull inhibition a CORF model exhibits an improved SNR, which is the reason for a more effective contour detection.     

Response histogram shapes and tuning curves: The predicted responses of several cortical cell types to drifting gratings stimuli

The responses to visual stimuli of simple cortical cells show linear spatial summation within and between their receptive field subunits. Complex cortical cells do not show this linearity. We analyzed the simulated responses to drifting sinusoidal grating stimuli of simple and of several types of complex cells. The complex cells, whose responses are seen to be half-wave rectified before pooling, have receptive fields consisting of two or more DOG (difference-of-Gaussians) shaped subunits. In both cases of stimulation by contrast-reversal gratings or drifting gratings, the cells' response as a function of spatial frequency is affected by the subunit distances 2 and the stimulation frequency . Furthermore, an increased number of subunits (a larger receptive field) yields a narrower peak tuning curve with decreased modulation depth for many of the spatial frequencies. The average and the peak response tuning curves are compared for the different receptive field types.     

猫V1区不同外周整合细胞的经典感受野属性研究

以家猫为动物模型,采用细胞外记录的方法,测试了82个初级视皮层细胞的方位和方向调谐以及感受野大小.基于细胞的面积整合特性,区分出52个外周抑制型细胞和30个外周无抑制型细胞.所有被测细胞均存在强的方位选择性,而外周无抑制型细胞比抑制型细胞有更强的方位选择性.两类细胞的方向选择性没有显著性差异.外周抑制型细胞比外周无抑制型细胞有着更大的动作电位发放率.采用两种不同方法测量两类细胞的感受野范围,却产生了不同的结果:用最小反应区测量发现抑制型细胞的经典感受野更大,而用面积整合曲线测量时外周无抑制型细胞的感受野更大.     

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

In order to probe into the self-organizing emergence of simple cell orientation selectivity, we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells. However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.     

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

In order to probe into the self-organizing emergence of simple cell orientation selectivity, we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells. However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.     

Spatial structure of complex cell receptive fields measured with natural images

Neuronal receptive fields (RFs) play crucial roles in visual processing. While the linear RFs of early neurons have been well studied, RFs of cortical complex cells are nonlinear and therefore difficult to characterize, especially in the context of natural stimuli. In this study, we used a nonlinear technique to compute the RFs of complex cells from their responses to natural images. We found that each RF is well described by a small number of subunits, which are oriented, localized, and bandpass. These subunits contribute to neuronal responses in a contrast-dependent, polarity-invariant manner, and they can largely predict the orientation and spatial frequency tuning of the cell. Although the RF structures measured with natural images were similar to those measured with random stimuli, natural images were more effective for driving complex cells, thus facilitating rapid identification of the subunits. The subunit RF model provides a useful basis for understanding cortical processing of natural stimuli.     

Double orientation tuning of cat visual cortical neurons

Orientation tuning of 148 primary visual cortical neurons was studied in acute experiments on unanesthetized, curarized cats by analysis of their spike responses to flashes in a receptive field of a bar of light of optimal size. Orientation tuning of 88 neurons (59%) was found to be bimodal: Besides the principal preferred orientation there was a second, making an angle with the first. The second tuning maximum in some cases (64%) was exhibited only with a change in stimulus intensity or background brightness. Analysis of orientation tuning by the time-slice method, i.e., on the basis of individual cuts of the spike trace, showed double tuning to be present in 69% of cases only at certain moments after the beginning of stimulation. The results of analysis of the model showed that the double orientation tuning effect may be the result of the specific configuration of the receptive field, the use of a stimulus longer than the receptive field, the presence of a series of alternating excitatory and inhibitory zones in the receptive field, and also of end inhibitory zones on the narrow ends of the field. The unequal change in zones of the receptive fields in time explains the appearance of double orientation tuning in individual fragments of the spike trace. The functional role of double, "cross-wise" tuning in some primary visual cortical neurons and their role in the detection of the features of visual patterns are discussed.