Dependence of Visual Cell Properties on Intracortical Synapses Among Hypercolumns: Analysis by a Computer Model

The role of intracortical synapses in affecting the property of visual cells is investigated by means of an original mathematical model of cortical circuitry in V1. The model represents a compromise between computational simplicity and physiological reliability. The model incorporates four different inputs into a cortical cell: thalamic input from the lateral geniculate nucleus, according to an even Gabor function; short-range inhibition confined within the hypercolumn; a long-range excitation, which emphasizes the properties of the input; and a long-range inhibition. In the model we assume that all cells receive a similar thalamic input, which differs simply according to its position in the retina and orientation preference. Simulations were performed, with different parameter values, to assess the main characteristics of cell response (i.e., the width and locations of subregions in the receptive field (RF), orientation tuning curve, and response to drifting and counterphase gratings) as a function of the strength and extension of intracortical excitatory synapses. Results suggest that, if intracortical excitation is confined within the hypercolumn, the cells exhibit the same properties as simple cells, both with regards to the width and shape of the RF, orientation tuning curve, and response to drifting and counterphase gratings. By contrast, if excitatory synapses extend beyond the hypercolumn with sufficient strength, the cells exhibit the typical characteristics of complex cells. A progressive shift from complex to simple cells can be realized with a monotonic variation in parameters. Simulations are also performed with a hierarchical model, to suggest possible experiments able to discriminate the present recurrent mechanism from the classical hierarchical one. Results support the assumptions of previous simpler models (Chance et al., 1999) and may help to understand and assess the role of intracortical synapses in rigorous quantitative terms.     

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.     

Joint coding of visual input and eye/head position in V1 of freely moving mice

1. Download : Download high-res image (166KB)
2. Download : Download full-size image

     

Computational models of spatial updating in peri-saccadic perception

Perceptual phenomena that occur around the time of a saccade, such as peri-saccadic mislocalization or saccadic suppression of displacement, have often been linked to mechanisms of spatial stability. These phenomena are usually regarded as errors in processes of trans-saccadic spatial transformations and they provide important tools to study these processes. However, a true understanding of the underlying brain processes that participate in the preparation for a saccade and in the transfer of information across it requires a closer, more quantitative approach that links different perceptual phenomena with each other and with the functional requirements of ensuring spatial stability. We review a number of computational models of peri-saccadic spatial perception that provide steps in that direction. Although most models are concerned with only specific phenomena, some generalization and interconnection between them can be obtained from a comparison. Our analysis shows how different perceptual effects can coherently be brought together and linked back to neuronal mechanisms on the way to explaining vision across saccades.     

Separation of Spatio-Temporal Receptive Fields into Sums of Gaussian Components

Visual cortical simple cells have been experimentally shown to reveal non-trivial spatio-temporal orientation tuning functions comprising different phases of specifically tuned enhanced and suppressed activity. A recently developed analytical method based on nonlinear neural field models suggests that such space-time responses should be approximately separable into a sum of temporally amplitude modulated Gaussian spatial components. In the present work, we investigate this possibility by means of numerical fits of sums of Gaussians to response functions observed in experiments and computer simulations. Because the theory relates each single component to a particular connectivity kernel between the underlying cell classes shaping the response, the relative contribution of feedforward and cortex-intrinsical excitatory and inhibitory feedback mechanisms to single cell tuning can be approached and quantified in experimental data.     

Is slowness a learning principle of the visual cortex?

Slow feature analysis is an algorithm for extracting slowly varying features from a quickly varying signal. It has been shown in network simulations on one-dimensional stimuli that visual invariances to shift and other transformations can be learned in an unsupervised fashion based on slow feature analysis. More recently, we have shown that slow feature analysis applied to image sequences generated from natural images using a range of spatial transformations results in units that share many properties with complex and hypercomplex cells of the primary visual cortex. We find cells responsive to Gabor stimuli with phase invariance, sharpened or widened orientation or frequency tuning, secondary response lobes, end-stopping, and cells selective for direction of motion. These results indicate that slowness may be an important principle of self-organization in the visual cortex.     

A Nonlinear Model of the Behavior of Simple Cells in Visual Cortex

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

Receptive Fields of Visually Sensitive Neurons of the Extrastriate Associative Area 21b of the Cat Cerebral Cortex

Organization of the receptive fields (RFs) of neurons of the extrastriate associative region 21b of the cerebral cortex was studied in cats. Most neurons under study (63%) were “monocular,” while 37% of the cells were “binocular” units. Among 178 neurons examined in detail, heterogeneous RF functional organization was typical of about 76% of the units; point-to-point testing of the entire RF area by stationary stimuli resulted in the generation of various types of responses (on, off, or on-off). The rest of the neurons (24%) generated homogeneous responses. The dimension, form, and functional organization of RFs of the neurons under study depended to a certain extent on the parameters of visual stimuli used for the measurements. Examination of the influence of the visual space, which surrounded the RF, on responses of the neurons evoked by stimulation of the RF per se showed that darkening of the visual space adjacent to the RF inhibited neuronal responses to moving stimuli; in some cases the responses were totally suppressed. Analysis of spatial overlapping of the RF sequentially recorded in the course of each insertion of the electrode showed that the density of distribution of the overlapping RF areas of neighboring neurons with the RF of the examined neuron is irregular, and that the RF is of a mosaic nature. We hypothesize that the visual space surrounding the RF plays a significant role in the formation of responses of visually sensitive neurons to presentation of moving stimuli. Neirofiziologiya/Neurophysiology, Vol. 37, No. 3, pp. 223–234, May–June, 2005.     

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.     

Learning-induced dynamic receptive field changes in primary auditory cortex of the unanaesthetized Mongolian gerbil

Learning-induced changes of the spectro-temporal characteristics of primary auditory cortex (AI) units were studied by response plane analysis of recordings from the AI in unanaesthetized Mongolian gerbils. Using response planes obtained prior to and after auditory discrimination training bins of significant change were identified and their spectro-temporal distribution was studied. Bins of significant changes were generally found to be distributed over the entire spectro-temporal receptive field but occurred most frequently within the first 100 ms of response in the spectral neighbourhood (1.5 octaves) of the frequency of the reinforced conditioned stimulus. Training-induced response decreases occurred early after 10 ms for reinforced conditioned tones and tones in the frequency neighbourhood. Response increases occurred so early only for non-reinforced tones in the neighbourhood of the reinforced frequency and occurred later (after 40 ms) for the reinforced tones. The results are discussed in the light of dynamic disinhibition. Accepted: 13 August 1997     

Spatiotemporal organization of simple-cell receptive fields in area 18 of cat''s cortex

Spatiotemporal structures of receptive-fields (RF) have been studied for simple cells in area 18 of eat by measuring the temporal transfer function (TTF) over different locations (subregions) within the RF. The temporal characteristics of different subregions differed from each other in the absolute phase shift (APS) to visual stimuli. Two types of relationships can be seen: (i)The APS varied continuously from one subregion to the next: (ii) A 180°-phase jump was seen as the stimulus position changed somewhere within the receptive field. Spatiotemporal receptive field profiles have been determined by applying reverse Fourier analysis to responses in the frequency domain. For the continuous type, spatial and temporal characteristics cannot be dissociated (space time inseparable) and the spatiotemporal structure is oriented. On the contrary, the spatial and temporal characteristics for the jumping type can be dissociated (space-time separable) and the structure is not oriented in the space-time plane. Based on the APSs measured at different subregions, the optimal direction of motion and optimal spatial frequency of neurons can be predicted. Project supported by the National Natural Science Foundation of China (Grant Nos. 39570206, 39330110) and the Laboratory of Visual Information Processing, Chinese Academy of Sciences.     

Sparse thalamocortical convergence

1. Download : Download high-res image (99KB)
2. Download : Download full-size image

     

Spatiotemporal organization of simple-cell receptive fields in area 18 of cat''''s cortex

Ｍｏｓｔｓｔｕｄｉｅｓｏｎｔｈｅｒｅｃｅｐｔｉｖｅｆｉｅｌｄ(ＲＦ)ｏｒｇａｎｉｚａｔｉｏｎｏｆｖｉｓｕａｌｃｏｒｔｅｘｎｅｕｒｏｎｓｈａｖｅｆｏｃｕｓｅｄｏｎｉｔｓｓｐａｔｉａｌｓｔｒｕｃｔｕｒｅ.Ｓｔｉｍｕｌｉｉｎｔｈｅｎａｔｕｒａｌｖｉｓｕａｌｗｏｒｌｄ,ｈｏｗｅｖｅｒ,ｉｎｃｌｕｄｅｂｏｔｈｓｐａｔｉａｌａｎｄｔｅｍｐｏｒａｌａｓｐｅｃｔｓ.Ｆｏｒａｍｏｒｅｃｏｍｐｌｅｔｅｆｕｎｃｔｉｏｎａｌｄｅｓｃｒｉｐｔｉｏｎｏｆｔｈｅｖｉｓｕａｌｎｅｕｒｏｎｓ,ｉｔｉｓｎｅｃｅｓｓａｒｙｔｏｉｎｖｅｓｔ…     

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.     

Global perception depends on coherent work of bilateral visual cortices: Transcranial magnetic stimulation (TMS) studies

Previous research suggests that the right and left hemispheres dominate global and local perception of hierarchical patterns, respectively. The current work examined whether global perception of hierarchi-cal stimuli requires coherent work of bilateral visual cortices using transcranial magnetic stimulation (TMS). Subjects discriminated global or local properties of compound letters in Experiment 1. Reaction times were recorded when single-pulse real TMS or sham TMS was delivered over the left or right visual cortex. While a global precedence effect (i.e., faster responses to global than local targets and stronger global-to-local interference than the reverse) was observed, TMS decreased global-to-local interference whereas increased local-to-global interference. Experiment 2 ruled out the possibility that the effects observed in Experiment 1 resulted from perceptual learning. Experiment 3 used compound shapes and observed TMS effect similar to that in Experiment 1. Moreover, TMS also slowed global RTs whereas speeded up local RTs in Experiment 3. Finally, the TMS effects observed in Experiments 1 and 3 did not differ between the conditions when TMS was applied over the left and right hemispheres. The results support a coherence hypothesis that global perception of compound stimuli depends upon the co-herent work of bilateral visual cortices.     

Global perception depends on coherent work of bilateral visual cortices: Transcranial magnetic stimulation (TMS) studies

Previous research suggests that the right and left hemispheres dominate global and local perception of hierarchical patterns, respectively. The current work examined whether global perception of hierarchical stimuli requires coherent work of bilateral visual cortices using transcranial magnetic stimulation (TMS). Subjects discriminated global or local properties of compound letters in Experiment 1. Reaction times were recorded when single-pulse real TMS or sham TMS was delivered over the left or right visual cortex. While a global precedence effect (i.e., faster responses to global than local targets and stronger global-to-local interference than the reverse) was observed, TMS decreased global-to-local interference whereas increased local-to-global interference. Experiment 2 ruled out the possibility that the effects observed in Experiment 1 resulted from perceptual learning. Experiment 3 used compound shapes and observed TMS effect similar to that in Experiment 1. Moreover, TMS also slowed global RTs whereas speeded up local RTs in Experiment 3. Finally, the TMS effects observed in Experiments 1 and 3 did not differ between the conditions when TMS was applied over the left and right hemispheres. The results support a coherence hypothesis that global perception of compound stimuli depends upon the coherent work of bilateral visual cortices.     

A Hallucinogenic Serotonin-2A Receptor Agonist Reduces Visual Response Gain and Alters Temporal Dynamics in Mouse V1

1. Download high-res image (198KB)
2. Download full-size image

     

在体神经元胞外记录用于大脑皮层可塑性研究

神经元网络可塑性是大脑学习和记忆功能的基础,可塑性的变化也是某些脑功能疾病的成因。研究大脑皮层可塑性不仅可以为认识可塑性机制提供基本方法,也可对自然衰老过程和神经退行性疾病的病理过程进行观测,进而可以为评价抗衰老药物和治疗神经退行性疾病提供新方法。本文基于经典的大鼠胡须配对模型建立了一套实验方案,通过在体细胞外记录实验的数据分析,比较修剪胡须后相同时间内神经元感受野不对称变化程度的差异,衡量不同生理条件下大鼠体感皮层神经元网络可塑性。本文以中年和青年大鼠体感皮层神经元网络可塑性比较为例,详细介绍了实验方法中的关键技术和操作,如皮层D2功能柱的定位和D2功能柱内不同层神经元的定位等,结果和我室以前相关研究证明了此实验方案的可行性。