The functional geometry of local and horizontal connections in a model of V1.

A mathematical model of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the geometry of local and long-range horizontal connections. Each hypercolumn is modeled as a network of interacting excitatory and inhibitory neural populations with orientation and spatial frequency preferences organized around a pair of pinwheels. The pinwheels are arranged on a planar lattice, reflecting the crystalline-like structure of cortex. Local interactions within a hypercolumn generate orientation and spatial frequency tuning curves, which are modulated by horizontal connections between different hypercolumns on the lattice. The symmetry properties of the local and long-range connections play an important role in determining the types of spontaneous activity patterns that can arise in cortex.     

Shunting inhibition, a silent step in visual cortical computation

Brain computation, in the early visual system, is often considered as a hierarchical process in which features extracted in a given sensory relay are not present in previous stages of integration. In particular, orientation preference and its fine tuning selectivity are functional properties shared by most cortical cells and they are not observed at the preceding geniculate stage. A classical problem is identifying the mechanisms and circuitry underlying these computations. Several organizational principles have been proposed, giving different weights to the feedforward thalamocortical drive or to intracortical recurrent architectures. Within this context, an important issue is whether intracortical inhibition is fundamental for the genesis of stimulus selectivity, or rather normalizes spike response tuning with respect to other features such as stimulus strength or contrast, without influencing the selectivity bias and preference expressed in the excitatory input alone. We review here experimental observations concerning the presence or absence of inhibitory input evoked by non-preferred orientation/directions. Intracellular current clamp and voltage clamp recordings are analyzed in the light of new methods allowing us (1) to increase the visibility of inhibitory input, and (2) to continuously measure the visually evoked dynamics of input conductances. We conclude that there exists a diversity of synaptic input combinations generating the same profile of spike-based orientation selectivity, and that this diversity most likely reflects anatomical non-homogeneities in input sampling provided by the local context of the columnar and lateral intracortical network in which the considered cortical cell is embedded.     

GABA拮抗剂荷包牡丹碱对猫外膝体神经元方位调谐特性的影响

在十二只成年猫上用多管玻璃微电极记录了外膝体神经元对不同空间频率和不同方位的移动正弦光栅刺激的反应,共详细测定并对比研究了３８个方位敏感性细胞在微电泳荷包牡丹碱前后的方位调谐特性。在最优空间频率附近的较低空间频率下,微电泳荷包牡丹碱后,外膝体细胞的方位敏感性强度（Ｂｉａｓ）降低,而在截止频率附近的较高空间频率下,微电泳前后外膝细胞的方位敏感性强度（Ｂｉａｓ）从总体上看没有显著变化。结果表明,以空间频率为截止频率附近的移动正弦光栅作为刺激,外膝体细胞的方位敏感性可能主要是由视网膜神经节细胞的兴奋输入所形成,而非外膝体内抑制机制所致。     

A major role for intracortical circuits in the strength and tuning of odor-evoked excitation in olfactory cortex

In primary sensory cortices, there are two main sources of excitation: afferent sensory input relayed from the periphery and recurrent intracortical input. Untangling the functional roles of these two excitatory pathways is fundamental for understanding how cortical neurons process sensory stimuli. Odor representations in the primary olfactory (piriform) cortex depend on excitatory sensory afferents from the olfactory bulb. However, piriform cortex pyramidal cells also receive dense intracortical excitatory connections, and the relative contribution of these two pathways to odor responses is unclear. Using a combination of in vivo whole-cell voltage-clamp recording and selective synaptic silencing, we show that the recruitment of intracortical input, rather than olfactory bulb input, largely determines the strength of odor-evoked excitatory synaptic transmission in rat piriform cortical neurons. Furthermore, we find that intracortical synapses dominate odor-evoked excitatory transmission in broadly tuned neurons, whereas bulbar synapses dominate excitatory synaptic responses in more narrowly tuned neurons.     

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.     

A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientation Tuning

We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are grouped into large populations of similar neurons. For each population, we form a probability density that represents the distribution of neurons over all possible states. The populations are coupled via stochastic synapses in which the conductance of a neuron is modulated according to the firing rates of its presynaptic populations. The evolution equation for each of these probability densities is a partial differential-integral equation, which we solve numerically. Results obtained for several example networks are tested against conventional computations for groups of individual neurons.We apply this approach to modeling orientation tuning in the visual cortex. Our population density model is based on the recurrent feedback model of a hypercolumn in cat visual cortex of Somers et al. (1995). We simulate the response to oriented flashed bars. As in the Somers model, a weak orientation bias provided by feed-forward lateral geniculate input is transformed by intracortical circuitry into sharper orientation tuning that is independent of stimulus contrast.The population density approach appears to be a viable method for simulating large neural networks. Its computational efficiency overcomes some of the restrictions imposed by computation time in individual neuron simulations, allowing one to build more complex networks and to explore parameter space more easily. The method produces smooth rate functions with one pass of the stimulus and does not require signal averaging. At the same time, this model captures the dynamics of single-neuron activity that are missed in simple firing-rate models.     

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     

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.     

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.     

猫外膝体神经元非寻常的方位调谐特性──Ⅱ．在去视皮层猫和视觉剥夺猫（Dark－reared cats）的研究

以移动的正弦光栅作为刺激,用玻璃微电极记录以冰冻法毁损皮层１７、１８、１９区和外侧上雪氏回（ＬＳ）区后的猫外膝体的单细胞反应,测定了了５７９个细胞的方位调谐特性．另外还在视觉剥夺猫外膝体测定了３４４个细胞的方位调谐特性．与正常猫相似,去视皮层猫和视觉剥夺猫外膝体的少数细胞（约占１０％）具有非寻常的方位调谐特性,包括具蝴蝶形调谐曲线的方位调谐特性、双调谐（Ｂｉｍｏｄａｌ）的方位调谐特性和最优方位随刺激空间频率的不同而变化的方位调谐特性。结果表明,外膝体的非寻常的方位调谐特性并非主要由皮层下行投射所致,而是主要与先天遗传因素有关。     

猫外膝体神经元非寻常的方位调谐特性──Ⅱ．在去视皮层猫和视觉剥夺猫（Dark－reared cats）的研究

以移动的正弦光栅作为刺激,用玻璃微电极记录以冰冻法毁损皮层１７、１８、１９区和外侧上雪氏回区后的猫外膝体的单细胞反应,测定了５７９个细胞的方位调谐特性,另外还在视觉剥夺猫外膝体测定了３４４个细胞的方位调谐特性,与正常猫相似,去视以猫和视觉剥夺猫外膝体的少数细胞具有非寻常的方位调谐特性,包括具蝴蝶形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空间的不同而变化的方位调谐特性。结果表明外     

Anisotropic connectivity and cooperative phenomena as a basis for orientation sensitivity in the visual cortex

A computer simulation model of the neural circuitry underlying orientation sensitivity in cortical neurons is examined. The model consists of a network of 3000 neurons divided into two functionally distinct cell types: excitatory (E-cells) and inhibitory (I-cells). We demonstrate that both orientation sensitivity and shape selectivity can be accounted for by making the following assumptions: 1) thalamic afferents to a sheet of cortical neurons are retionotopically organized; 2) thalamic afferents come from a single neuron, or at most a few neurons, in the lateral geniculate nucleus; 3) cortical activity is cooperative, i.e. largely dependent on intracortical connections, some of which have anisotropies along directions parallel to the pial surface. Anisotropies are specified only by the distribution of cells which are postsynaptic to a particular neuron, without specifying the axonal or dendritic contributions. In this paper, orientation sensitivity arises through cooperative interactions among neurons having anisotropic excitatory, and isotropic inhibitory connections.     

Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning

This intracellular study investigates synaptic mechanisms of orientation and direction selectivity in cat area 17. Visually evoked inhibition was analyzed in 88 cells by detecting spike suppression, hyperpolarization, and reduction of trial-to-trial variability of membrane potential. In 25 of these cells, inhibition visibility was enhanced by depolarization and spike inactivation and by direct measurement of synaptic conductances. We conclude that excitatory and inhibitory inputs share the tuning preference of spiking output in 60% of cases, whereas inhibition is tuned to a different orientation in 40% of cases. For this latter type of cells, conductance measurements showed that excitation shared either the preference of the spiking output or that of the inhibition. This diversity of input combinations may reflect inhomogeneities in functional intracortical connectivity regulated by correlation-based activity-dependent processes.     

Processing in layer 4 of the neocortical circuit: new insights from visual and somatosensory cortex

Recent experimental and theoretical results in cat primary visual cortex and in the whisker-barrel fields of rodent primary somatosensory cortex suggest common organizing principles for layer 4, the primary recipient of sensory input from the thalamus. Response tuning of layer 4 cells is largely determined by a local interplay of feed-forward excitation (directly from the thalamus) and inhibition (from layer 4 inhibitory interneurons driven by the thalamus). Feed-forward inhibition dominates excitation, inherits its tuning from the thalamic input, and sharpens the tuning of excitatory cells. Recurrent excitation enhances responses to effective stimuli.     

A theory for the use of visual orientation information which exploits the columnar structure of striate cortex

A neural model is constructed based on the structure of a visual orientation hypercolumn in mammalian striate cortex. It is then assumed that the perceived orientation of visual contours is determined by the pattern of neuronal activity across orientation columns. Using statistical estimation theory, limits on the precision of orientation estimation and discrimination are calculated. These limits are functions of single unit response properties such as orientation tuning width, response amplitude and response variability, as well as the degree of organization in the neural network. It is shown that a network of modest size, consisting of broadly orientation selective units, can reliably discriminate orientation with a precision equivalent to human performance. Of the various network parameters, the discrimination threshold depends most critically on the number of cells in the hypercolumn. The form of the dependence on cell number correctly predicts the results of psychophysical studies of orientation discrimination. The model system's performance is also consistent with psychophysical data in two situations in which human performance is not optimal. First, interference with orientation discrimination occurs when multiple stimuli activate cells in the same hypercolumn. Second, systematic errors in the estimation of orientation can occur when a stimulus is composed of intersecting lines. The results demonstrate that it is possible to relate neural activity to visual performance by an examination of the pattern of activity across orientation columns. This provides support for the hypothesis that perceived orientation is determined by the distributed pattern of neural activity. The results also encourage the view of neural activity. The results also are determined by the responses of many neurons rather than the sensitivity of individual cells.     

Striate receptive fields mapped with single and bipartite stimuli

In 22 acute experiments with anesthetized and immobilized adult cats, 364 maps of receptive fields (RF) of 47 striate neurons were obtained by means of single local stimuli flashed at different parts of the visual field, or with additional asynchronous activation of the RF excitatory center with oscillating bar of the optimal orientation. Under bipartite stimulation, considerable and significant decrease in the square and weight of the central excitatory RF zone was revealed in more then 75% of the studied cells. Additional excitatory zones appeared in 54% of cases, or the square and weight of the excitatory zones substantially increased, and inhibitory zones developed in 90% of cases. These effects were correlated with the degree of increase in the background firing during transition from the mode of mapping with single stimulation to that with bipartite stimulation. The mechanism and possible functional role of cooperative excitatory and inhibitory intracortical interactions in organization of receptive fields and detection of features of a visual image are discussed.     

Lateral sharpening of cortical frequency tuning by approximately balanced inhibition

Cortical inhibition plays an important role in shaping neuronal processing. The underlying synaptic mechanisms remain controversial. Here, in vivo whole-cell recordings from neurons in the rat primary auditory cortex revealed that the frequency tuning curve of inhibitory input was broader than that of excitatory input. This results in relatively stronger inhibition in frequency domains flanking the preferred frequencies of the cell and a significant sharpening of the frequency tuning of membrane responses. The less selective inhibition can be attributed to a broader bandwidth and lower threshold of spike tonal receptive field of fast-spike inhibitory neurons than nearby excitatory neurons, although both types of neurons receive similar ranges of excitatory input and are organized into the same tonotopic map. Thus, the balance between excitation and inhibition is only approximate, and intracortical inhibition with high sensitivity and low selectivity can laterally sharpen the frequency tuning of neurons, ensuring their highly selective representation.     

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.