Topography of orientation centre connections in the primary visual cortex of the cat

Revisiting horizontal connectivity rules in V1: from like-to-like towards like-to-all

Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the similar length scale for the regularity found in cortical orientation maps, the currently accepted theoretical standpoint is that these maps are underpinned by a like-to-like connectivity rule: horizontal axons connect preferentially to neurons with similar preferred orientation. However, there is reason to doubt the rule's explanatory power, since a growing number of quantitative studies show that the like-to-like connectivity preference and bias mostly observed at short-range scale, are highly variable on a neuron-to-neuron level and depend on the origin of the presynaptic neuron. Despite the wide availability of published data, the accepted model of visual processing has never been revised. Here, we review three lines of independent evidence supporting a much-needed revision of the like-to-like connectivity rule, ranging from anatomy to population functional measures, computational models and to theoretical approaches. We advocate an alternative, distance-dependent connectivity rule that is consistent with new structural and functional evidence: from like-to-like bias at short horizontal distance to like-to-all at long horizontal distance. This generic rule accounts for the observed high heterogeneity in interactions between the orientation and retinotopic domains, that we argue is necessary to process non-trivial stimuli in a task-dependent manner.

The growth of cognition: Free energy minimization and the embryogenesis of cortical computation

The assumption that during cortical embryogenesis neurons and synaptic connections are selected to form an ensemble maximising synchronous oscillation explains mesoscopic cortical development, and a mechanism for cortical information processing is implied by consistency with the Free Energy Principle and Dynamic Logic. A heteroclinic network emerges, with stable and unstable fixed points of oscillation corresponding to activity in symmetrically connected, versus asymmetrically connected, sets of neurons. Simulations of growth explain a wide range of anatomical observations for columnar and non-columnar cortex, superficial patch connections, and the organization and dynamic interactions of neurone response properties. An antenatal scaffold is created, upon which postnatal learning can establish continuously ordered neuronal representations, permitting matching of co-synchronous fields in multiple cortical areas to solve optimization problems as in Dynamic Logic. Fast synaptic competition partitions equilibria, minimizing "the curse of dimensionality", while perturbations between imperfectly partitioned synchronous fields, under internal reinforcement, enable the cortex to become adaptively self-directed. As learning progresses variational free energy is minimized and entropy bounded.

Subdomains within orientation columns of primary visual cortex

In the mammalian visual system, early stages of visual form processing begin with orientation-selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in a beautifully arrayed pinwheel-like orientation columns, which shift in orientation preference across V1. However, to date, the relationship of orientation architecture to the encoding of multiple elemental aspects of visual contours is still unknown. Here, using a novel, highly accurate method of targeting electrode position, we report for the first time the presence of three subdomains within single orientation domains. We suggest that these zones subserve computation of distinct aspects of visual contours and propose a novel tripartite pinwheel-centered view of an orientation hypercolumn.

Beyond Rehabilitation of Acuity, Ocular Alignment, and Binocularity in Infantile Strabismus

Infantile strabismus impairs the perception of all attributes of the visual scene. High spatial frequency components are no longer visible, leading to amblyopia. Binocularity is altered, leading to the loss of stereopsis. Spatial perception is impaired as well as detection of vertical orientation, the fastest movements, directions of movement, the highest contrasts and colors. Infantile strabismus also affects other vision-dependent processes such as control of postural stability. But presently, rehabilitative therapies for infantile strabismus by ophthalmologists, orthoptists and optometrists are restricted to preventing or curing amblyopia of the deviated eye, aligning the eyes and, whenever possible, preserving or restoring binocular vision during the critical period of development, i.e., before ~10 years of age. All the other impairments are thus ignored; whether they may recover after strabismus treatment even remains unknown. We argue here that medical and paramedical professionals may extend their present treatments of the perceptual losses associated with infantile strabismus. This hypothesis is based on findings from fundamental research on visual system organization of higher mammals in particular at the cortical level. In strabismic subjects (as in normal-seeing ones), information about all of the visual attributes converge, interact and are thus inter-dependent at multiple levels of encoding ranging from the single neuron to neuronal assemblies in visual cortex. Thus if the perception of one attribute is restored this may help to rehabilitate the perception of other attributes. Concomitantly, vision-dependent processes may also improve. This could occur spontaneously, but still should be assessed and validated. If not, medical and paramedical staff, in collaboration with neuroscientists, will have to break new ground in the field of therapies to help reorganize brain circuitry and promote more comprehensive functional recovery. Findings from fundamental research studies in both young and adult patients already support our hypothesis and are reviewed here. For example, presenting different contrasts to each eye of a strabismic patient during training sessions facilitates recovery of acuity in the amblyopic eye as well as of 3D perception. Recent data also demonstrate that visual recoveries in strabismic subjects improve postural stability. These findings form the basis for a roadmap for future research and clinical development to extend presently applied rehabilitative therapies for infantile strabismus.

Neural field model to reconcile structure with function in primary visual cortex

Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.

Further Work on the Shaping of Cortical Development and Function by Synchrony and Metabolic Competition

This paper furthers our attempts to resolve two major controversies-whether gamma synchrony plays a role in cognition, and whether cortical columns are functionally important. We have previously argued that the configuration of cortical cells that emerges in development is that which maximizes the magnitude of synchronous oscillation and minimizes metabolic cost. Here we analyze the separate effects in development of minimization of axonal lengths, and of early Hebbian learning and selective distribution of resources to growing synapses, by showing in simulations that these effects are partially antagonistic, but their interaction during development produces accurate anatomical and functional properties for both columnar and non-columnar cortex. The resulting embryonic anatomical order can provide a cortex-wide scaffold for postnatal learning that is dimensionally consistent with the representation of moving sensory objects, and, as learning progressively overwrites the embryonic order, further associations also occur in a dimensionally consistent framework. The role ascribed to cortical synchrony does not demand specific frequency, amplitude or phase variation of pulses to mediate "feature linking." Instead, the concerted interactions of pulse synchrony with short-term synaptic dynamics, and synaptic resource competition can further explain cortical information processing in analogy to Hopfield networks and quantum computation.

Pinwheel-dipole configuration in cat early visual cortex

In the early visual cortex, information is processed within functional maps whose layouts are thought to underlie visual perception. However, the precise organization of these functional maps as well as their interrelationships remain unsettled. Here, we show that spatial frequency representation in cat early visual cortex exhibits singularities around which the map organizes like an electric dipole potential. These singularities are precisely co-located with singularities of the orientation map: the pinwheel centers. To show this, we used high resolution intrinsic optical imaging in cat areas 17 and 18. First, we show that a majority of pinwheel centers exhibit in their neighborhood both semi-global maximum and minimum in the spatial frequency map (i.e. extreme values of the spatial frequency in a hypercolumn). This contradicts pioneering studies suggesting that pinwheel centers are placed at the locus of a single spatial frequency extremum. Based on an analogy with electromagnetism, we proposed a mathematical model for a dipolar structure, accurately fitting optical imaging data. We conclude that a majority of orientation pinwheel centers form spatial frequency dipoles in cat early visual cortex. Given the functional specificities of neurons at singularities in the visual cortex, it is argued that the dipolar organization of spatial frequency around pinwheel centers could be fundamental for visual processing.

Long-range cortical connections give rise to a robust velocity map of V1

This paper proposes a two-dimensional velocity model (2DVM) of the primary visual cortex (V1). The model's novel aspect is that it specifies a particular pattern of long-range cortical temporal connections, via the Connection Algorithm, and shows how the addition of these connections to well-known spatial properties of V1 transforms V1 into a velocity map. The map implies a number of organizational properties of V1: (1) the singularity of each orientation pinwheel contributes to the detection of slow-moving spots across the visual field; (2) the speed component of neuronal velocity selectivity decreases monotonically across each joint orientation contour line for parallel motion and increases monotonically for orthogonal motion; (3) the cells that are direction selective to slow-moving objects are situated in the periphery of V1; and (4) neurons in distinct pinwheels tend to be connected to neurons with similar tuning preferences in other pinwheels. The model accounts for various types of known illusionary perceptions of human vision: perceptual filling-in, illusionary orientation and visual crowding. The three distinguishing features of 2DVM are: (1) it unifies the functional properties of the conventional energy model of V1; (2) it directly relates the functional properties to the known structure of the upper layers of V1; and (3) it implies that the spatial selectivity features of V1 are side effects of its more important role as a velocity map of the visual field.

Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection

Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical role in visual perception, the specific role of orientation-selective and non-selective inhibition in the task of contour detection is less known. To clarify above question, we first carried out computational analysis of the contour detection performance of V1 neurons with different types of surround inhibition, on the basis of which we then proposed two integrated models to evaluate their role in this specific perceptual task by combining the two types of surround inhibition with two different ways. The two models were evaluated with synthetic images and a set of challenging natural images, and the results show that both of the integrated models outperform the typical models with orientation-selective or non-selective inhibition alone. The findings of this study suggest that V1 neurons with different types of center–surround interaction work in cooperative and adaptive ways at least when extracting organized structures from cluttered natural scenes. This work is expected to inspire efficient phenomenological models for engineering applications in field of computational machine-vision.

An adaptable neuromorphic model of orientation selectivity based on floating gate dynamics

The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps in silicon.

The shape of dendritic arbors in different functional domains of the cortical orientation map

The neocortex is organized into macroscopic functional maps. However, at the microscopic scale, the functional preference and degree of feature selectivity between neighboring neurons can vary considerably. In the primary visual cortex, adjacent neurons in iso-orientation domains share the same orientation preference, whereas neighboring neurons near pinwheel centers are tuned to different stimulus orientations. Moreover, several studies have found greater orientation selectivity in iso-orientation domains than in pinwheel centers. These differences suggest that neurons sample local inputs in a spatially homogenous fashion and independently of the location of their soma on the orientation map. Here we determine whether dendritic geometry is affected by neuronal position on the orientation map. We labeled individual layer 2/3 pyramidal neurons with fluorescent dyes in specific domains of the orientation map in cat primary visual cortex and imaged their dendritic trees in vivo by two-photon microscopy. We found that the circularity and uniformity of dendritic trees is independent of somatic position on the orientation map. Moreover, the dendrites of neurons located close to pinwheel centers extend across all orientation domains in an unbiased fashion. Thus, unbiased dendritic trees appear to provide an anatomical substrate for the systematic variations in feature selectivity across the orientation map.

Developmental origin of patchy axonal connectivity in the neocortex: a computational model

Injections of neural tracers into many mammalian neocortical areas reveal a common patchy motif of clustered axonal projections. We studied in simulation a mathematical model for neuronal development in order to investigate how this patchy connectivity could arise in layer II/III of the neocortex. In our model, individual neurons of this layer expressed the activator-inhibitor components of a Gierer-Meinhardt reaction-diffusion system. The resultant steady-state reaction-diffusion pattern across the neuronal population was approximately hexagonal. Growth cones at the tips of extending axons used the various morphogens secreted by intrapatch neurons as guidance cues to direct their growth and invoke axonal arborization, so yielding a patchy distribution of arborization across the entire layer II/III. We found that adjustment of a single parameter yields the intriguing linear relationship between average patch diameter and interpatch spacing that has been observed experimentally over many cortical areas and species. We conclude that a simple Gierer-Meinhardt system expressed by the neurons of the developing neocortex is sufficient to explain the patterns of clustered connectivity observed experimentally.

On the dynamics of cortical development: synchrony and synaptic self-organization

We describe a model for cortical development that resolves long-standing difficulties of earlier models. It is proposed that, during embryonic development, synchronous firing of neurons and their competition for limited metabolic resources leads to selection of an array of neurons with ultra-small-world characteristics. Consequently, in the visual cortex, macrocolumns linked by superficial patchy connections emerge in anatomically realistic patterns, with an ante-natal arrangement which projects signals from the surrounding cortex onto each macrocolumn in a form analogous to the projection of a Euclidean plane onto a Möbius strip. This configuration reproduces typical cortical response maps, and simulations of signal flow explain cortical responses to moving lines as functions of stimulus velocity, length, and orientation. With the introduction of direct visual inputs, under the operation of Hebbian learning, development of mature selective response “tuning” to stimuli of given orientation, spatial frequency, and temporal frequency would then take place, overwriting the earlier ante-natal configuration. The model is provisionally extended to hierarchical interactions of the visual cortex with higher centers, and a general principle for cortical processing of spatio-temporal images is sketched.

Sharper orientation tuning of the extraclassical suppressive-surround due to a neuron's location in the V1 orientation map emerges late in time

Neuronal responses in primary visual cortex (V1) can be suppressed by a stimulus presented to the extraclassical surround, and such interactions are thought to be critical for figure ground segregation and form perception. While surround suppression likely originates from both feedforward afferents and multiple cortical circuits, it is unclear what role each circuit plays in the surround's orientation tuning. To investigate this we recorded from single units in V1 of anesthetized cat and analyzed the orientation tuning of the suppressive-surround over time. In addition, based on orientation maps derived through optical imaging prior to recording, neurons were classified as being located in domains or pinwheels. For both types of neurons, shortly after response onset (10 ms) the suppressive-surround is broadly tuned to orientation, but this is followed by a steep improvement in tuning over the next ∼30 ms. While the tuning of the pinwheel cells plateaus at this point, tuning is enhanced further for domain cells, especially those located superficially in the cortex, reaching a peak at 80 ms from response onset. This relatively slow evolution of the orientation tuning of the suppressive surround suggests that fast-arriving feedforward circuits (10 ms) likely only provide broadly tuned suppression, but that feedback from higher visual areas which is likely to arrive over the next 30 ms and can cover both the receptive field center and the extraclassical surround contributes to the initial steep rise in tuning for both cell types. Moreover, we speculate that the even later enhancement in tuning for domain neurons could mean the involvement of inputs from relatively long-range lateral connections, which not only propagate slowly but also link like-oriented domains corresponding to the receptive field of only the extraclassical surround.

Orientation tuning of the suppressive extraclassical surround depends on intrinsic organization of V1

The intrinsic functional architecture of early cortical areas in highly visual mammals is characterized by the presence of domains and pinwheels, with orientation preference of the inputs to these regions being more and less selective, respectively. We exploited this organizational feature to investigate mechanisms supporting extraclassical surround suppression, a process thought to be critical for figure ground segregation and form vision. Combining intrinsic signal optical imaging and single-unit recording in V1 of anesthetized cats, we show for the first time that the orientation tuning of the suppressive surround is sharper for domain than for pinwheel neurons. This difference depends on high center gain and is more pronounced in superficial cortex. In addition, when we remove the near component of the surround stimulus, the strength of suppression induced by the iso-oriented surround is significantly reduced for domain neurons but is unchanged for orthogonal oriented surrounds. This leads to broader orientation tuning of suppression that renders domain cells indistinguishable from pinwheel cells. Because the limited receptive field of the near surround can be accounted for by the lateral spread of long-range connections in V1, our findings suggest that intrinsic V1 circuits play a key role in the orientation tuning of extraclassical surround suppression.

From neural arbors to daisies

Pyramidal neurons in layers 2 and 3 of the neocortex collectively form an horizontal lattice of long-range, periodic axonal projections, known as the superficial patch system. The precise pattern of projections varies between cortical areas, but the patch system has nevertheless been observed in every area of cortex in which it has been sought, in many higher mammals. Although the clustered axonal arbors of single pyramidal cells have been examined in detail, the precise rules by which these neurons collectively merge their arbors remain unknown. To discover these rules, we generated models of clustered axonal arbors following simple geometric patterns. We found that models assuming spatially aligned but independent formation of each axonal arbor do not produce patchy labeling patterns for large simulated injections into populations of generated axonal arbors. In contrast, a model that used information distributed across the cortical sheet to generate axonal projections reproduced every observed quality of cortical labeling patterns. We conclude that the patch system cannot be built during development using only information intrinsic to single neurons. Information shared across the population of patch-projecting neurons is required for the patch system to reach its adult state.

Lateral Spread of Orientation Selectivity in V1 is Controlled by Intracortical Cooperativity

Neurons in the primary visual cortex receive subliminal information originating from the periphery of their receptive fields (RF) through a variety of cortical connections. In the cat primary visual cortex, long-range horizontal axons have been reported to preferentially bind to distant columns of similar orientation preferences, whereas feedback connections from higher visual areas provide a more diverse functional input. To understand the role of these lateral interactions, it is crucial to characterize their effective functional connectivity and tuning properties. However, the overall functional impact of cortical lateral connections, whatever their anatomical origin, is unknown since it has never been directly characterized. Using direct measurements of postsynaptic integration in cat areas 17 and 18, we performed multi-scale assessments of the functional impact of visually driven lateral networks. Voltage-sensitive dye imaging showed that local oriented stimuli evoke an orientation-selective activity that remains confined to the cortical feedforward imprint of the stimulus. Beyond a distance of one hypercolumn, the lateral spread of cortical activity gradually lost its orientation preference approximated as an exponential with a space constant of about 1 mm. Intracellular recordings showed that this loss of orientation selectivity arises from the diversity of converging synaptic input patterns originating from outside the classical RF. In contrast, when the stimulus size was increased, we observed orientation-selective spread of activation beyond the feedforward imprint. We conclude that stimulus-induced cooperativity enhances the long-range orientation-selective spread.

Whose Cortical Column Would that Be?

The cortical column has been an invaluable concept to explain the functional organization of the neocortex. While this idea was born out of experiments that cleverly combined electrophysiological recordings with anatomy, no one has ‘seen’ the anatomy of a column. All we know is that when we record through the cortex of primates, ungulates, and carnivores in a trajectory perpendicular to its surface there is a remarkable constancy in the receptive field properties of the neurons regarding one set of stimulus features. There is no obvious morphological analog for this functional architecture, in fact much of the anatomical data seems to challenge it. Here we describe historically the origins of the concept of the cortical column and the struggles of the pioneers to define the columnar architecture. We suggest that in the concept of a ‘canonical circuit’ we may find the means to reconcile the structure of neocortex with its functional architecture. The canonical microcircuit respects the known connectivity of the neocortex, and it is flexible enough to change transiently the architecture of its network in order to perform the required computations.

Mapping of contextual modulation in the population response of primary visual cortex

We review the evidence of long-range contextual modulation in V1. Populations of neurons in V1 are activated by a wide variety of stimuli outside of their classical receptive fields (RF), well beyond their surround region. These effects generally involve extra-RF features with an orientation component. The population mapping of orientation preferences to the upper layers of V1 is well understood, as far as the classical RF properties are concerned, and involves organization into pinwheel-like structures. We introduce a novel hypothesis regarding the organization of V1's contextual response. We show that RF and extra-RF orientation preferences are mapped in related ways. Orientation pinwheels are the foci of both types of features. The mapping of contextual features onto the orientation pinwheel has a form that recapitulates the organization of the visual field: an iso-orientation patch within the pinwheel also responds to extra-RF stimuli of the same orientation. We hypothesize that the same form of mapping applies to other stimulus properties that are mapped out in V1, such as colour and contrast selectivity. A specific consequence is that fovea-like properties will be mapped in a systematic way to orientation pinwheels. We review the evidence that cytochrome oxidase blobs comprise the foci of this contextual remapping for colour and low contrasts. Neurodynamics and motion in the visual field are argued to play an important role in the shaping and maintenance of this type of mapping in V1.

Inactivation of lateral connections in cat area 17

Excitatory synapses arising from local neurons in the cat visual cortex are much more numerous than the thalamocortical synapses, which provide the primary sensory input. Many of these local circuit synapses are involved in the connections between cortical layers, but lateral connections within layers provide a major component of the local circuit synapses. We tested the influence of these lateral connections in the primary visual cortex of cats by inactivating small patches of cortex about 450 microm lateral from the recording pipette. By use of the neurotransmitter gamma-aminobutyric acid (GABA), small patches of cortex were inhibited and released from inhibition in seconds. Orientation tuning curves derived from responses to oriented drifting gratings were obtained during short control periods interleaved with periods of GABA inactivation. About 30% of the cells (18/62, recorded in all layers) changed their orientation tuning when a small portion of their lateral input was silenced. There was no broadening of the orientation tuning curve during lateral inactivation. Instead, the recorded cells shifted their preferred orientation towards the orientation of the inactivated site. One explanation is that the GABA inactivation alters the balance of excitatory and inhibitory inputs to a cell, which results in a shift of the cell's preferred orientation.

Dynamics of orientation tuning in cat v1 neurons depend on location within layers and orientation maps

Analysis of the timecourse of the orientation tuning of responses in primary visual cortex (V1) can provide insight into the circuitry underlying tuning. Several studies have examined the temporal evolution of orientation selectivity in V1 neurons, but there is no consensus regarding the stability of orientation tuning properties over the timecourse of the response. We have used reverse-correlation analysis of the responses to dynamic grating stimuli to re-examine this issue in cat V1 neurons. We find that the preferred orientation and tuning curve shape are stable in the majority of neurons; however, more than forty percent of cells show a significant change in either preferred orientation or tuning width between early and late portions of the response. To examine the influence of the local cortical circuit connectivity, we analyzed the timecourse of responses as a function of receptive field type, laminar position, and orientation map position. Simple cells are more selective, and reach peak selectivity earlier, than complex cells. There are pronounced laminar differences in the timing of responses: middle layer cells respond faster, deep layer cells have prolonged response decay, and superficial cells are intermediate in timing. The average timing of neurons near and far from pinwheel centers is similar, but there is more variability in the timecourse of responses near pinwheel centers. This result was reproduced in an established network model of V1 operating in a regime of balanced excitatory and inhibitory recurrent connections, confirming previous results. Thus, response dynamics of cortical neurons reflect circuitry based on both vertical and horizontal location within cortical networks.

Neural network model of the primary visual cortex: from functional architecture to lateral connectivity and back

The role of intrinsic cortical dynamics is a debatable issue. A recent optical imaging study (Kenet et al., 2003) found that activity patterns similar to orientation maps (OMs), emerge in the primary visual cortex (V1) even in the absence of sensory input, suggesting an intrinsic mechanism of OM activation. To better understand these results and shed light on the intrinsic V1 processing, we suggest a neural network model in which OMs are encoded by the intrinsic lateral connections. The proposed connectivity pattern depends on the preferred orientation and, unlike previous models, on the degree of orientation selectivity of the interconnected neurons. We prove that the network has a ring attractor composed of an approximated version of the OMs. Consequently, OMs emerge spontaneously when the network is presented with an unstructured noisy input. Simulations show that the model can be applied to experimental data and generate realistic OMs. We study a variation of the model with spatially restricted connections, and show that it gives rise to states composed of several OMs. We hypothesize that these states can represent local properties of the visual scene.

Model-based analysis of excitatory lateral connections in the visual cortex

Excitatory lateral connections within the primary visual cortex are thought to link neurons with similar receptive field properties. Here we studied whether this rule can predict the distribution of excitatory connections in relation to cortical location and orientation preference in the cat visual cortex. To this end, we obtained orientation maps of areas 17 or 18 using optical imaging and injected anatomical tracers into these regions. The distribution of labeled axonal boutons originating from large populations of excitatory neurons was then analyzed and compared with that of individual pyramidal or spiny stellate cells. We demonstrate that the connection patterns of populations of nearby neurons can be reasonably predicted by Gaussian and von Mises distributions as a function of cortical location and orientation, respectively. The connections were best described by superposition of two components: a spatially extended, orientation-specific and a local, orientation-invariant component. We then fitted the same model to the connections of single cells. The composite pattern of nine excitatory neurons (obtained from seven different animals) was consistent with the assumptions of the model. However, model fits to single cell axonal connections were often poorer and their estimated spatial and orientation tuning functions were highly variable. We conclude that the intrinsic excitatory network is biased to similar cortical locations and orientations but it is composed of neurons showing significant deviations from the population connectivity rule.

Local networks in visual cortex and their influence on neuronal responses and dynamics

Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

Invariant computations in local cortical networks with balanced excitation and inhibition

Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

Intrinsic connections in tree shrew V1 imply a global to local mapping

The local-global map hypothesis states that locally organized response properties--such as orientation preference--result from visuotopically organized local maps of non-retinotopic response properties. In the tree shrew, the lateral extent of horizontal patchy connections is as much as 80-100% of V1 and is consistent with the length summation property. We argue that neural signals can be transmitted across the entire extent of V1 and this allows the formation of maps at the local scale that are visuotopically organized. We describe mechanisms relevant to the formation of local maps and report modeling results showing the same patterns of horizontal connectivity, and relationships to orientation preference, seen in vivo. The structure of the connectivity that emerges in the simulations reveals a 'hub and spoke' organization. Singularities form the centers of local maps, and linear zones and saddle-points arise as smooth border transitions between maps. These findings are used to present the case for the local-global map hypothesis for tree shrew V1.

Complex receptive fields in primary visual cortex

In the early 1960s, Hubel and Wiesel reported the first physiological description of cells in cat primary visual cortex. They distinguished two main cell types: simple cells and complex cells. Based on their distinct response properties, they suggested that the two cell types could represent two consecutive stages in receptive-field construction. Since the 1960s, new experimental and computational evidence provided serious alternatives to this hierarchical model. Parallel models put forward the idea that both simple and complex receptive fields could be built in parallel by direct geniculate inputs. Recurrent models suggested that simple cells and complex cells may not be different cell types after all. To this day, a consensus among hierarchical, parallel, and recurrent models has been difficult to attain; however, the circuitry used by all models is becoming increasingly similar. The authors review theoretical and experimental evidence for each line of models emphasizing their strengths and weaknesses.

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 degrees when we consider only the linear excitatory contribution from LGN. We observe a mean improvement of 22.8 degrees in tuning response due to the non-linear spiking mechanisms that include effects of threshold voltage and synaptic scaling factor.

Functional organization of the cat visual cortex in relation to the representation of a uniform surface

Neuronal activity in the early visual cortex has been extensively studied from the standpoint of contour representation. On the other hand, representation of the interior of a surface surrounded by a contour is much less well understood. Several studies have identified neurons activated by a uniform surface covering their receptive fields, but their distribution within the cortex is not yet known. The aim of the present study was to obtain a better understanding of the distribution of such neurons in the visual cortex. Using optical imaging of intrinsic signals, we found that there are a group of surface-responsive regions located in area 18, along the area 17/18 border, that tend to overlap the singular points of the orientation-preference map. Extracellular recordings confirmed that neurons responsive to uniform plane stimuli are accumulated in these regions. Such neurons also existed outside the surface-responsive regions around the singular points. These results suggest that there exists a functional organization related to the representation of a uniform surface in the early visual cortex.

Synaptic integration by V1 neurons depends on location within the orientation map

Neurons in the primary visual cortex (V1) are organized into an orientation map consisting of orientation domains arranged radially around "pinwheel centers" at which the representations of all orientations converge. We have combined optical imaging of intrinsic signals with intracellular recordings to estimate the subthreshold inputs and spike outputs of neurons located near pinwheel centers or in orientation domains. We find that neurons near pinwheel centers have subthreshold responses to all stimulus orientations but spike responses to only a narrow range of orientations. Across the map, the selectivity of inputs covaries with the selectivity of orientations in the local cortical network, while the selectivity of spike outputs does not. Thus, the input-output transformation performed by V1 neurons is powerfully influenced by the local structure of the orientation map.

Orientation tuning--a crooked path to the straight and narrow

Neurons in visual cortex are selective for the orientation of a visual stimulus, while the receptive fields of their thalamic input are circular. Cortical orientation selectivity arises from the organization of both thalamic input and local cortical circuits. In this issue of Neuron, Schummers and colleagues provide evidence that the local circuit mechanisms contributing to orientation selectivity differ depending on the local organization of the orientation map.

Orientation specificity of contrast adaptation in visual cortical pinwheel centres and iso-orientation domains

Exposure to a high-contrast visual stimulus causes adaptation, a psychophysical phenomenon that is quite selective for stimulus orientation. Its mechanism is largely cortical but the underlying circuitry is still not unambiguously resolved. It has been suggested that adaptation could be the result of integration of inputs from cells within a large local pool, effectively scaling their outputs with respect to local contrast. In this case, orientation selectivity of neuronal adaptation should depend on the location of neurons within the cortical map of orientation preference. We tested this hypothesis by quantifying adaptation to optimally oriented and to orthogonal-to-optimum gratings among neurons recorded either from iso-orientation domains or orientation pinwheel centres, as identified by optical imaging of cat visual cortex. We did not find a significant difference in adaptation characteristics for these two populations of cells, implying that these characteristics do not depend on the local functional architecture. Surprisingly, however, we additionally observed that under isoflurane (but not halothane) anaesthesia, most neurons exhibited adaptation by cross-oriented gratings, regardless of their location within the orientation map. It seems likely that, under isoflurane, inputs became visible that were masked by the commonly used, deeper halothane anaesthesia. For individual cells, the presence of these inputs was independent of their location within the cortical orientation map.

Pairing-induced changes of orientation maps in cat visual cortex

We have studied the precise temporal requirements for plasticity of orientation preference maps in kitten visual cortex. Pairing a brief visual stimulus with electrical stimulation in the cortex, we found that the relative timing determines the direction of plasticity: a shift in orientation preference toward the paired orientation occurs if the cortex is activated first visually and then electrically; the cortical response to the paired orientation is diminished if the sequence of visual and electrical activation is reversed. We furthermore show that pinwheel centers are less affected by the pairing than the pinwheel surround. Thus, plasticity is not uniformly distributed across the cortex, and, most importantly, the same spike time-dependent learning rules that have been found in single-cell in vitro studies are also valid on the level of cortical maps.