Axonal topography of cortical basket cells in relation to orientation, direction, and ocular dominance maps

Acetylcholine facilitates localized synaptic potentiation and location specific feature binding

Forebrain acetylcholine (ACh) signaling has been shown to drive attention and learning. Recent experimental evidence of spatially and temporally constrained cholinergic signaling has sparked interest to investigate how it facilitates stimulus-induced learning. We use biophysical excitatory-inhibitory (E-I) multi-module neural network models to show that external stimuli and ACh signaling can mediate spatially constrained synaptic potentiation patterns. The effects of ACh on neural excitability are simulated by varying the conductance of a muscarinic receptor-regulated hyperpolarizing slow K+ current (m-current). Each network module consists of an E-I network with local excitatory connectivity and global inhibitory connectivity. The modules are interconnected with plastic excitatory synaptic connections, that change via a spike-timing-dependent plasticity (STDP) rule. Our results indicate that spatially constrained ACh release influences the information flow represented by network dynamics resulting in selective reorganization of inter-module interactions. Moreover the information flow depends on the level of synchrony in the network. For highly synchronous networks, the more excitable module leads firing in the less excitable one resulting in strengthening of the outgoing connections from the former and weakening of its incoming synapses. For networks with more noisy firing patterns, activity in high ACh regions is prone to induce feedback firing of synchronous volleys and thus strengthening of the incoming synapses to the more excitable region and weakening of outgoing synapses. Overall, these results suggest that spatially and directionally specific plasticity patterns, as are presumed necessary for feature binding, can be mediated by spatially constrained ACh release.

Internal neural states influence the short-term effect of monocular deprivation in human adults

The adult human visual system maintains the ability to be altered by sensory deprivation. What has not been considered is whether the internal neural states modulate visual sensitivity to short-term monocular deprivation. In this study we manipulated the internal neural state and reported changes in intrinsic neural oscillations with a patched eye open or closed. We investigated the influence of eye open/eye closure on the unpatched eye's contrast sensitivity and ocular dominance (OD) shifts induced by short-term monocular deprivation. The results demonstrate that internal neural states influence not only baseline contrast sensitivity but also the extent to which the adult visual system can undergo changes in ocular dominance.

Form, synapses and orientation topography of a new cell type in layer 6 of the cat’s primary visual cortex

Here we report the morpho-functional features of a novel type of deep-layer neuron. The neuron was selected from a large pool of intracellularly labelled cells based on the large cell body, numerous spine-free dendrites with an overall interneuron morphology. However, the axon gave off long-range axons up to 2.8 mm from the parent soma in layers 5/6 before entering the white matter. The boutons were uniformly distributed along the axon without forming distinct clusters. Dendritic length, surface area and volume values were at least 3 times larger than any known cortical neuron types with the exception of giant pyramidal cells of layer 5. Electron microscopy of the boutons revealed that they targeted dendritic spines (78%) and less frequently dendritic shafts (22%). Nearly half of the postsynaptic dendrites were immunopositive to GABA. Superimposing the axonal field on the orientation map obtained with optical imaging showed a preponderance of boutons to cross-orientations (38%) and an equal representation of iso- and oblique orientations (31%). The results suggest an integrating role for the layer 6 stellate neuron which projects to a functionally broad range of neurons in the deep cortical layers and to other cortical and/or subcortical regions.

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.

Kv3.1 channels regulate the rate of critical period plasticity

Experience-dependent plasticity within visual cortex is controlled by postnatal maturation of inhibitory circuits, which are both morphologically diverse and precisely connected. Gene-targeted disruption of the voltage-dependent potassium channel K_v3.1 broadens action potentials and reduces net inhibitory function of parvalbumin (PV)-positive GABA subtypes within the neocortex. In mice lacking K_v3.1, the rate of input loss from an eye deprived of vision was slowed two-fold, despite otherwise normal critical period timecourse and receptive field properties. Rapid ocular dominance plasticity was restored by local or systemic enhancement of GABAergic transmission with acute benzodiazepine infusion. Diazepam instead exacerbated a global suppression of slow-wave oscillations during sleep described previously in these mutant mice, which therefore did not account for the rescued plasticity. Rapid ocular dominance shifts closely reflected K_v3.1 gene dosage that prevented prolonged spike discharge of their target pyramidal cells in vivo or the spike amplitude decrement of fast-spiking cells during bouts of high-frequency firing in vitro. Late postnatal expression of this unique channel in fast-spiking interneurons thus subtly regulates the speed of critical period plasticity with implications for mental illnesses.

Patching and Suppression in Amblyopia: One Mechanism or Two?

Purpose

To determine if benefits from occlusion therapy are due to decreased suppression from the fellow eye in children with amblyopia.

Methods

Ten newly diagnosed amblyopes (7.2 ± 1.4 years old), two with strabismus and eight with anisometropia, participated. Patients were first given a 2-month period of refractive adaptation, followed by occlusion therapy (i.e., patching their fellow eye with an opaque patch for 4 h/day). Visual acuity of the amblyopic eye and interocular suppression were measured before and after 0.5, 1, 2, 4, and 6 months of occlusion therapy. We quantified interocular suppression with a binocular phase combination task.

Results

Visual acuity (in logMAR) improved from 0.50 ± 0.22 (mean ± SD) to 0.33 ± 0.20 for patients who finished a short-term (2 months) occlusion (A1–A10), from 0.53 ± 0.20 to 0.32 ± 0.22 for patients who finished a medium-term (4 months) occlusion (A1–A9), and from 0.48 ± 0.19 to 0.22 ± 0.10 for patients who finished a long-term (6 months) occlusion (A1–A8). Although their visual acuity significantly improved, their degree of suppression, which was abnormal in all cases, did not change consistently. This was true in all durations of occlusion therapy.

Conclusion

Reduced suppression from the fixing eye might not be result from occlusion therapy.

Dynamical patterns underlying response properties of cortical circuits

Recent experimental studies show cortical circuit responses to external stimuli display varied dynamical properties. These include stimulus strength-dependent population response patterns, a shift from synchronous to asynchronous states and a decline in neural variability. To elucidate the mechanisms underlying these response properties and explore how they are mechanistically related, we develop a neural circuit model that incorporates two essential features widely observed in the cerebral cortex. The first feature is a balance between excitatory and inhibitory inputs to individual neurons; the second feature is distance-dependent connectivity. We show that applying a weak external stimulus to the model evokes a wave pattern propagating along lateral connections, but a strong external stimulus triggers a localized pattern; these stimulus strength-dependent population response patterns are quantitatively comparable with those measured in experimental studies. We identify network mechanisms underlying this population response, and demonstrate that the dynamics of population-level response patterns can explain a range of prominent features in neural responses, including changes to the dynamics of neurons' membrane potentials and synaptic inputs that characterize the shift of cortical states, and the stimulus-evoked decline in neuron response variability. Our study provides a unified population activity pattern-based view of diverse cortical response properties, thus shedding new insights into cortical processing.

Suppressive Traveling Waves Shape Representations of Illusory Motion in Primary Visual Cortex of Awake Primate

How does the brain link visual stimuli across space and time? Visual illusions provide an experimental paradigm to study these processes. When two stationary dots are flashed in close spatial and temporal succession, human observers experience a percept of apparent motion. Large spatiotemporal separation challenges the visual system to keep track of object identity along the apparent motion path, the so-called "correspondence problem." Here, we use voltage-sensitive dye imaging in primary visual cortex (V1) of awake monkeys to show that intracortical connections within V1 can solve this issue by shaping cortical dynamics to represent the illusory motion. We find that the appearance of the second stimulus in V1 creates a systematic suppressive wave traveling toward the retinotopic representation of the first. Using a computational model, we show that the suppressive wave is the emergent property of a recurrent gain control fed by the intracortical network. This suppressive wave acts to explain away ambiguous correspondence problems and contributes to precisely encode the expected motion velocity at the surface of V1. Together, these results demonstrate that the nonlinear dynamics within retinotopic maps can shape cortical representations of illusory motion. Understanding these dynamics will shed light on how the brain links sensory stimuli across space and time, by preformatting population responses for a straightforward read-out by downstream areas.SIGNIFICANCE STATEMENT Traveling waves have recently been observed in different animal species, brain areas, and behavioral states. However, it is still unclear what are their functional roles. In the case of cortical visual processing, waves propagate across retinotopic maps and can hereby generate interactions between spatially and temporally separated instances of feedforward driven activity. Such interactions could participate in processing long-range apparent motion stimuli, an illusion for which no clear neuronal mechanisms have yet been proposed. Using this paradigm in awake monkeys, we show that suppressive traveling waves produce a spatiotemporal normalization of apparent motion stimuli. Our study suggests that cortical waves shape the representation of illusory moving stimulus within retinotopic maps for a straightforward read-out by downstream areas.

Binocular Modulation of Monocular V1 Neurons

In humans and other primates, sensory signals from each eye remain separated until they arrive in the primary visual cortex (V1), but their exact meeting point is unknown. In V1, some neurons respond to stimulation of only one eye (monocular neurons), while most neurons respond to stimulation of either eye (binocular neurons). The main input layers of V1 contain most of the monocular neurons while binocular neurons dominate the layers above and below. This observation has given rise to the idea that the two eyes' signals remain separate until they converge outside V1's input layers. Here, we show that, despite responding to only one eye, monocular neurons in all layers, including the input layers, of V1 discriminate between stimulation of their driving eye alone and stimulation of both eyes. Some monocular V1 neurons' responses were significantly enhanced, or facilitated, when both eyes were stimulated. Binocular facilitation within V1's input layers tended to occur at the onset of the visual response, which could be explained by converging thalamocortical inputs. However, most V1 monocular neurons were significantly reduced, or suppressed, to binocular stimulation. In contrast to facilitation, binocular suppression occurred several milliseconds following the onset of the visual response, suggesting that the bulk of binocular modulation involves cortical inhibition. These findings, combined, suggest that binocular signals arise at an earlier processing stage than previously appreciated, as even so-called monocular neurons in V1's input layers encode what is shown to both eyes.

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.

Binocular response modulation in the lateral geniculate nucleus

The dorsal lateral geniculate nucleus of the thalamus (LGN) receives the main outputs of both eyes and relays those signals to the visual cortex. Each retina projects to separate layers of the LGN so that each LGN neuron is innervated by a single eye. In line with this anatomical separation, visual responses of almost all of LGN neurons are driven by one eye only. Nonetheless, many LGN neurons are sensitive to what is shown to the other eye as their visual responses differ when both eyes are stimulated compared to when the driving eye is stimulated in isolation. This, predominantly suppressive, binocular modulation of LGN responses might suggest that the LGN is the first location in the primary visual pathway where the outputs from the two eyes interact. Indeed, the LGN features several anatomical structures that would allow for LGN neurons responding to one eye to modulate neurons that respond to the other eye. However, it is also possible that binocular response modulation in the LGN arises indirectly as the LGN also receives input from binocular visual structures. Here we review the extant literature on the effects of binocular stimulation on LGN spiking responses, highlighting findings from cats and primates, and evaluate the neural circuits that might mediate binocular response modulation in the LGN.

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.

Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations

Voltage-sensitive dye (VSD) imaging produces an unprecedented real-time and high-resolution mesoscopic signal to measure the cortical population activity. We have previously shown that the neuronal compartments contributions to the signal are dynamic and stimulus-dependent (Chemla S, Chavane F. Neuroimage 53: 420-438, 2010). Moreover, the VSD signal can also be strongly affected by the network state, such as in anesthetized vs. awake preparations. Here, we investigated the impact of the network state, through GABAA receptors modulation, on the VSD signal using a computational approach. We therefore systematically measured the effect of the GABAA-mediated inhibitory postsynaptic potentials (IPSPs) decay time constant (τG) on our modeled VSD response to an input stimulus of increasing strength. Our simulations suggest that τG strongly modulates the dynamics of the VSD signal, affecting the amplitude, input response function, and the transient balance of excitation and inhibition. We confirmed these predictions experimentally on awake and anesthetized monkeys, comparing VSD responses to drifting gratings stimuli of various contrasts. Lastly, one in vitro study has suggested that GABAA receptors may also be directly affected by the VSDs themselves (Mennerick S, Chisari M, Shu H, Taylor A, Vasek M, Eisenman L, Zorumski C. J Neurosci 30: 2871-2879, 2010). Our modeling approach suggests that the type of modulation described in this study would actually have a negligible influence on the population response. This study highlights that functional results acquired with different techniques and network states must be compared with caution. Biophysical models are proposed here as an adequate tool to delineate the domain of VSD data interpretation.

Storing structured sparse memories in a multi-modular cortical network model

We study the memory performance of a class of modular attractor neural networks, where modules are potentially fully-connected networks connected to each other via diluted long-range connections. On this anatomical architecture we store memory patterns of activity using a Willshaw-type learning rule. P patterns are split in categories, such that patterns of the same category activate the same set of modules. We first compute the maximal storage capacity of these networks. We then investigate their error-correction properties through an exhaustive exploration of parameter space, and identify regions where the networks behave as an associative memory device. The crucial parameters that control the retrieval abilities of the network are (1) the ratio between the number of synaptic contacts of long- and short-range origins (2) the number of categories in which a module is activated and (3) the amount of local inhibition. We discuss the relationship between our model and networks of cortical patches that have been observed in different cortical areas.

Origins of feature selectivities and maps in the mammalian primary visual cortex

A common feature of the mammalian striate cortex is the arrangement of 'orientation domains' containing neurons preferring similar stimulus orientations. They are arranged as spokes of a pinwheel that converge at singularities known as 'pinwheel centers'. We propose that a cortical network of feedforward and intracortical lateral connections elaborates a full set of optimum orientations from geniculate inputs that show a bias to stimulus orientation and form a set of two or a small number of 'Cartesian' coordinates. Because each geniculate afferent carries signals only from one eye and its receptive field (RF) is either ON or OFF center, the network constructs also ocular dominance columns and a quasi-segregation of ON and OFF responses across the horizontal extent of the striate cortex.

Precise visuotopic organization of the blind spot representation in primate V1

The optic disk is a region of the retina consisting mainly of ganglion cell axons and blood vessels, which generates a visual scotoma known as the blind spot (BS). Information present in the surroundings of the BS can be used to complete the missing information. However, the neuronal mechanisms underlying these perceptual phenomena are poorly understood. We investigate the topography of the BS representation (BSR) in cortical area V1 of the capuchin monkey, using single and multiple electrodes. Receptive fields (RFs) of neurons inside the BSR were investigated using two distinct automatic bias-free mapping methods. The first method (local mapping) consisted of randomly flashing small white squares. For the second mapping method (global mapping), we used a single long bar that moved in one of eight directions. The latter stimulus was capable of eliciting neuronal activity inside the BSR, possibly attributable to long-range surround activity taking place outside the borders of the BSR. Importantly, we found that the neuronal activity inside the BSR is organized topographically in a manner similar to that found in other portions of V1. On average, the RFs inside the BS were larger than those outside. However, no differences in orientation or direction tuning were found between the two regions. We propose that area V1 exhibits a continuous functional topographic map, which is not interrupted in the BSR, as expected by the distribution of photoreceptors in the retina. Thus V1 topography is better described as “visuotopic” rather than as a discontinuous “retinotopic” map.

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.

Large-scale axonal reorganization of inhibitory neurons following retinal lesions

The functional properties of adult cortical neurons are subject to alterations in sensory experience. Retinal lesions lead to remapping of cortical topography in the region of primary visual cortex representing the lesioned part of the retina, the lesion projection zone (LPZ), with receptive fields shifting to the intact parts of the retina. Neurons within the LPZ receive strengthened input from the surrounding region by growth of the plexus of excitatory long-range horizontal connections. Here, by combining cell type-specific labeling with a genetically engineered recombinant adeno-associated virus and in vivo two-photon microscopy in adult macaques, we showed that the remapping was also associated with alterations in the axonal arbors of inhibitory neurons, which underwent a parallel process of pruning and growth. The axons of inhibitory neurons located within the LPZ extended across the LPZ border, suggesting a mechanism by which new excitatory input arising from the peri-LPZ is balanced by reciprocal inhibition arising from the LPZ.

Spontaneous slow oscillations and sequential patterns due to short-term plasticity in a model of the cortex

We study a realistic model of a cortical column taking into account short-term plasticity between pyramidal cells and interneurons. The simulation of leaky integrate-and-fire neurons shows that low-frequency oscillations emerge spontaneously as a result of intrinsic network properties. These oscillations are composed of prolonged phases of high and low activity reminiscent of cortical up and down states, respectively. We simplify the description of the network activity by using a mean field approximation and reduce the system to two slow variables exhibiting some relaxation oscillations. We identify two types of slow oscillations. When the combination of dynamic synapses between pyramidal cells and those between interneurons accounts for the generation of these slow oscillations, the end of the up phase is characterized by asynchronous fluctuations of the membrane potentials. When the slow oscillations are mainly driven by the dynamic synapses between interneurons, the network exhibits fluctuations of membrane potentials, which are more synchronous at the end than at the beginning of the up phase. Additionally, finite size effect and slow synaptic currents can modify the irregularity and frequency, respectively, of these oscillations. Finally, we consider possible roles of a slow oscillatory input modeling long-range interactions in the brain. Spontaneous slow oscillations of local networks are modulated by the oscillatory input, which induces, notably, synchronization, subharmonic synchronization, and chaotic relaxation oscillations in the mean field approximation. In the case of forced oscillations, the slow population-averaged activity of leaky integrate-and-fire neurons can have both deterministic and stochastic temporal features. We discuss the possibility that long-range connectivity controls the emergence of slow sequential patterns in local populations due to the tendency of a cortical column to oscillate at low frequency.

Formation and regulation of dynamic patterns in two-dimensional spiking neural circuits with spike-timing-dependent plasticity

Spike-timing-dependent plasticity (STDP) is an important synaptic dynamics that is capable of shaping the complex spatiotemporal activity of neural circuits. In this study, we examine the effects of STDP on the spatiotemporal patterns of a spatially extended, two-dimensional spiking neural circuit. We show that STDP can promote the formation of multiple, localized spiking wave patterns or multiple spike timing sequences in a broad parameter space of the neural circuit. Furthermore, we illustrate that the formation of these dynamic patterns is due to the interaction between the dynamics of ongoing patterns in the neural circuit and STDP. This interaction is analyzed by developing a simple model able to capture its essential dynamics, which give rise to symmetry breaking. This occurs in a fundamentally self-organizing manner, without fine-tuning of the system parameters. Moreover, we find that STDP provides a synaptic mechanism to learn the paths taken by spiking waves and modulate the dynamics of their interactions, enabling them to be regulated. This regulation mechanism has error-correcting properties. Our results therefore highlight the important roles played by STDP in facilitating the formation and regulation of spiking wave patterns that may have crucial functional roles in brain information processing.

Communication and wiring in the cortical connectome

In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns.

Dynamic modulation of an orientation preference map by GABA responsible for age-related cognitive performance

Accumulating evidence suggests that cognitive declines in old (healthy) animals could arise from depression of intracortical inhibition, for which a decreased ability to produce GABA during senescence might be responsible. By simulating a neural network model of a primary visual cortical (V1) area, we investigated whether and how a lack of GABA affects cognitive performance of the network: detection of the orientation of a visual bar-stimulus. The network was composed of pyramidal (P) cells and GABAergic interneurons such as small (S) and large (L) basket cells. Intrasynaptic GABA-release from presynaptic S or L cells contributed to reducing ongoing-spontaneous (background) neuronal activity in a different manner. Namely, the former exerted feedback (S-to-P) inhibition and reduced the frequency (firing rate) of action potentials evoked in P cells. The latter reduced the number of saliently firing P cells through lateral (L-to-P) inhibition. Non-vesicular GABA-release, presumably from glia and/or neurons, into the extracellular space reduced the both, activating extrasynaptic GABAa receptors and providing P cells with tonic inhibitory currents. By this combinatorial, spatiotemporal inhibitory mechanism, the background activity as noise was significantly reduced, compared to the stimulus-evoked activity as signal, thereby improving signal-to-noise (S/N) ratio. Interestingly, GABA-spillover from the intrasynaptic cleft into the extracellular space was effective for improving orientation selectivity (orientation bias), especially when distractors interfered with detecting the bar-stimulus. These simulation results may provide some insight into how the depression of intracortical inhibition due to a reduction in GABA content in the brain leads to age-related cognitive decline.

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.

Neocortical axon arbors trade-off material and conduction delay conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal's conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations.

Within the grey matter of cerebral cortex is a complex network formed by a dense tangle of individual branching axons mostly of cortical origin. Yet remarkably when presented with a barrage of complex, noisy sensory stimuli this convoluted network architecture computes accurately and rapidly. How does such a highly interconnected though jumbled forest of axonal trees process vital information so quickly? Pioneering neuroscientist Ramón y Cajal thought the size and shape of individual neurons was governed by simple rules to save cellular material and to reduce signal conduction delay. In this study, we investigated how these rules applied to whole axonal trees in neocortex by comparing their 3D structure to equivalent artificial arbors optimized for these rules. We discovered that neocortical axonal trees achieve a balance between these two rules so that a little more cellular material than necessary was used to substantially reduce conduction delays. Importantly, we suggest the nature of arbor branching balances time and material so that neocortical axons may communicate with a high degree of temporal precision, enabling accurate and rapid computation within local cortical networks. This approach could be applied to other neural structures to better understand the functional principles of brain design.

Distributed dynamical computation in neural circuits with propagating coherent activity patterns

Activity in neural circuits is spatiotemporally organized. Its spatial organization consists of multiple, localized coherent patterns, or patchy clusters. These patterns propagate across the circuits over time. This type of collective behavior has ubiquitously been observed, both in spontaneous activity and evoked responses; its function, however, has remained unclear. We construct a spatially extended, spiking neural circuit that generates emergent spatiotemporal activity patterns, thereby capturing some of the complexities of the patterns observed empirically. We elucidate what kind of fundamental function these patterns can serve by showing how they process information. As self-sustained objects, localized coherent patterns can signal information by propagating across the neural circuit. Computational operations occur when these emergent patterns interact, or collide with each other. The ongoing behaviors of these patterns naturally embody both distributed, parallel computation and cascaded logical operations. Such distributed computations enable the system to work in an inherently flexible and efficient way. Our work leads us to propose that propagating coherent activity patterns are the underlying primitives with which neural circuits carry out distributed dynamical computation.

The brain processes information with extraordinary efficiency, and can perform feats such as effortlessly recognizing objects from among thousands of possibilities within a fraction of a second. This is accomplished because the brain represents and processes information in a distributed fashion and in a dynamical way. This processing is manifested in spatiotemporal neural activity patterns of great complexities within the brain. Here, we construct a spiking neural circuit that can reproduce some of the complexities, which are evident in terms of multiple wave patterns with interactions between each other. We show that their dynamics can support propagating pattern-based computation; spiking wave patterns signal information by propagating across neural circuits, and computational operations occur when they collide with each other. Such dynamical computation contrasts sharply with that done by static and physically fixed logic gates operating in other computing machines such as computers. Moreover, we elucidate that the collective dynamics of multiple, interacting wave patterns enable computation processing implemented in a fundamentally distributed and parallel manner in the neural circuit.

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.

Two-point heterogeneous connections in a continuum neural field model

We examine a novel heterogeneous connection scheme in a 1D continuum neural field model. Multiple two-point connections are added to a local connection function in order to model the "patchy" connections seen in, for example visual cortex. We use a numerical approach to solve the equations, choosing the locations of the two-point connections stochastically. We observe self-sustained persistent fluctuations of activity which can be classified into two types (one of which is similar to that seen in network models of discrete excitable neurons, the other being particular to this model). We study the effect of parameters such as system size and the range, number and strength of connections, on the probability that a particular realisation of the connections is able to exhibit persistent fluctuations.

The operating regime of local computations in primary visual cortex

In V1, local circuitry depends on the position in the orientation map: close to pinwheel centers, recurrent inputs show variable orientation preferences; within iso-orientation domains, inputs are relatively uniformly tuned. Physiological properties such as cell's membrane potentials, spike outputs, and temporal characteristics change systematically with map location. We investigate in a firing rate and a Hodgkin-Huxley network model what constraints these tuning characteristics of V1 neurons impose on the cortical operating regime. Systematically varying the strength of both recurrent excitation and inhibition, we test a wide range of model classes and find the likely models to account for the experimental observations. We show that recent intracellular and extracellular recordings from cat V1 provide the strongest evidence for a regime where excitatory and inhibitory recurrent inputs are balanced and dominate the feed-forward input. Our results are robust against changes in model assumptions such as spatial extent and strength of lateral inhibition. Intriguingly, the most likely recurrent regime is in a region of parameter space where small changes have large effects on the network dynamics, and it is close to a regime of "runaway excitation," where the network shows strong self-sustained activity. This could make the cortical response particularly sensitive to modulation.

Persistent fluctuations of activity in undriven continuum neural field models with power-law connections

We study the effect of random inhomogeneous connections on a continuous field description of neural tissue. We focus on a regime in which persistent random fluctuations in activity arise spontaneously in the absence of either time-varying or spatially inhomogeneous input. While present in real tissue and network models of discrete neurons, such behavior has not been reported in continuum models of this type. The activity contains frequencies similar to those seen experimentally. We consider a power-law envelope r(-alpha) for the inhomogeneity and present evidence that the statistical coherence (a measure of two-point correlation) rapidly percolates across the system as alpha is reduced below alphac approximately 1,2 in one and two dimensions, respectively.

Layout of transcallosal activity in cat visual cortex revealed by optical imaging

The contribution of interhemispheric connections to functional maps in cat visual cortex was investigated by using optical imaging of intrinsic signals. In order to isolate the functional inputs arriving via the corpus callosum (CC) from other inputs, we used the split-chiasm preparation. The regions activated through the CC in visual areas 17 (A17) and 18 (A18) were localized and characterized by stimulating monocularly split-chiasm cats with moving, high contrast oriented gratings. We found that the CC mediates the activation of orientation selective domains in the transition zone (TZ) between A17 and A18 and occasionally within portions of both of these areas. We observed transcallosally activated orientation domains all along the TZ without any obvious interruption, and these domains were arranged around "pinwheel" centers. Interestingly, the TZ was divided in two parallel regions, which resemble A17 and A18 in their preferred temporal and spatial frequencies. Finally, we demonstrated that orientation maps evoked through the transcallosal and geniculo-cortical pathways were similar within the TZ, indicating a convergence of inputs of matching orientations in this region. These results contribute to a better understanding of the role of the CC in visual perception of orientations and shapes, at the level of the visual cortex.

Potentiation of cortical inhibition by visual deprivation

The fine-tuning of circuits in sensory cortex requires sensory experience during an early critical period. Visual deprivation during the critical period has catastrophic effects on visual function, including loss of visual responsiveness to the deprived eye, reduced visual acuity, and loss of tuning to many stimulus characteristics. These changes occur faster than the remodelling of thalamocortical axons, but the intracortical plasticity mechanisms that underlie them are incompletely understood. Long-term depression of excitatory intracortical synapses has been proposed as a general candidate mechanism for the loss of cortical responsiveness after visual deprivation. Alternatively (or in addition), the decreased ability of the deprived eye to activate cortical neurons could be due to enhanced intracortical inhibition. Here we show that visual deprivation leaves excitatory connections in layer 4 (the primary input layer to cortex) unaffected, but markedly potentiates inhibitory feedback between fast-spiking basket cells (FS cells) and star pyramidal neurons (star pyramids). Further, a previously undescribed form of long-term potentiation of inhibition (LTPi) could be induced at synapses from FS cells to star pyramids, and was occluded by previous visual deprivation. These data suggest that potentiation of inhibition is a major cellular mechanism underlying the deprivation-induced degradation of visual function, and that this form of LTPi is important in fine-tuning cortical circuitry in response to visual experience.

Olfactory epithelia differentially express neuronal markers

All three olfactory epithelia, the olfactory epithelium proper (OE), the septal organ of Masera (SO), and the vomeronasal organ of Jacobson (VNO) originate from the olfactory placode. Here, their diverse neurochemical phenotypes were analyzed using the immunohistochemical expression pattern of different neuronal markers. The olfactory bulb (OB) served as neuronal control. Neuronal Nuclei Marker (NeuN) is neither expressed in sensory neurons in any of the three olfactory epithelia, nor in relay neurons (mitral/tufted cells) of the OB. However, OB interneurons (periglomerular/granule cells) labeled, as did supranuclear structures of VNO supporting cells and VNO glands. Protein Gene Product 9.5 (PGP9.5 = C-terminal ubiquitin hydrolase L1 = UCHL1) expression is exactly the opposite: all olfactory sensory neurons express PGP9.5 as do OB mitral/tufted cells but not interneurons. Neuron Specific Enolase (NSE) expression is highest in the most apically located OE and SO sensory neurons and patchy in VNO. In contrast, the cytoplasm of the most basally located neurons of OE and SO immunoreacted for Growth Associated Protein 43 (GAP-43/B50). In VNO neurons GAP-43 labeling is also nuclear. In the cytoplasm, Olfactory Marker Protein (OMP) is most intensely expressed in SO, followed by OE and least in VNO neurons; further, OMP is also expressed in the nucleus of basally located VNO neurons. OB mitral/tufted cells express OMP at low levels. Neurons closer to respiratory epithelium often expressed a higher level of neuronal markers, suggesting a role of those markers for neuronal protection against take-over. Within the VNO the neurons show clear apical-basal expression diversity, as they do for factors of the signal transduction cascade. Overall, expression patterns of the investigated neuronal markers suggest that OE and SO are more similar to each other than to VNO.

Amygdala input monosynaptically innervates parvalbumin immunoreactive local circuit neurons in rat medial prefrontal cortex

The projection from the basolateral nucleus of the amygdala (BLA) conveys information about the affective significance of sensory stimuli to the medial prefrontal cortex (mPFC). By using an anterograde tract-tracing procedure combined with immunocytochemistry and correlated light/electron microscopical examination, labeled BLA afferents to layers 2-6 of the rat mPFC are shown to establish asymmetrical synaptic contacts, not only with dendritic spines (approximately 95.7% of targets innervated), but also with the aspiny dendritic shafts and somata of multipolar parvalbumin immunopositive (PV+) neurons. A population of PV- dendritic shafts was also innervated. Labeled BLA synaptic input to identified PV+ structures occurred in layers 2-6 of mPFC. The results indicate that labeled BLA afferents predominantly contact the spiny processes of presumed pyramidal cells and also provide a direct and specific innervation to a sub-population of local circuit neurons in mPFC containing PV. Since PV+ cells include two significant classes of fast-spiking GABAergic inhibitory interneuron (basket and axo-axonic cells), these novel observations indicate that the amygdalocortical pathway in the rat has the ability to directly influence functionally strategic 'feed-forward' inhibitory mechanisms at the first stage of processing amygdalocortical information.

Intracortical origins of interocular suppression in the visual cortex

The response of neurons in the primary visual cortex to an optimally oriented grating is usually suppressed quite dramatically when a second grating of, for example, orthogonal orientation is superimposed. Such "cross-orientation suppression" has been implicated in the generation of cortical orientation selectivity and local response normalization. Until recently, little experimental evidence was available concerning the neurophysiological substrate of this phenomenon, although an involvement of intracortical inhibition was commonly assumed. However, Freeman et al. (2002) proposed that cortical cross-orientation suppression is caused by suppression in the thalamus and depression at geniculocortical synapses. Here, we examine a dichoptic form of cross-orientation suppression, termed interocular suppression and thought to be involved in binocular rivalry (Sengpiel et al., 1995a). We show that its dependency on the drift rate of the suppressing stimulus is consistent with a cortical origin; unlike monocular cross-orientation suppression, it cannot be evoked by very fast-moving stimuli. Moreover, we find that previous adaptation to the orthogonal stimulus essentially eliminates interocular suppression. Because adaptation is a cortical phenomenon, this result also argues in favor of a cortical locus of suppression, again unlike monocular cross-orientation suppression, which is not affected by adaptation to the suppressor (Freeman et al., 2002). Finally, interocular suppression is greatly reduced in the presence of the GABA antagonist bicuculline. Together, our study demonstrates that interocular suppression is substantially different from monocular cross-orientation suppression and is mediated by inhibitory circuitry within the visual cortex.

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.

Critical period plasticity in local cortical circuits

Neuronal circuits in the brain are shaped by experience during 'critical periods' in early postnatal life. In the primary visual cortex, this activity-dependent development is triggered by the functional maturation of local inhibitory connections and driven by a specific, late-developing subset of interneurons. Ultimately, the structural consolidation of competing sensory inputs is mediated by a proteolytic reorganization of the extracellular matrix that occurs only during the critical period. The reactivation of this process, and subsequent recovery of function in conditions such as amblyopia, can now be studied with realistic circuit models that might generalize across systems.

A quantitative map of the circuit of cat primary visual cortex

We developed a quantitative description of the circuits formed in cat area 17 by estimating the "weight" of the projections between different neuronal types. To achieve this, we made three-dimensional reconstructions of 39 single neurons and thalamic afferents labeled with horseradish peroxidase during intracellular recordings in vivo. These neurons served as representatives of the different types and provided the morphometrical data about the laminar distribution of the dendritic trees and synaptic boutons and the number of synapses formed by a given type of neuron. Extensive searches of the literature provided the estimates of numbers of the different neuronal types and their distribution across the cortical layers. Applying the simplification that synapses between different cell types are made in proportion to the boutons and dendrites that those cell types contribute to the neuropil in a given layer, we were able to estimate the probable source and number of synapses made between neurons in the six layers. The predicted synaptic maps were quantitatively close to the estimates derived from the experimental electron microscopic studies for the case of the main sources of excitatory and inhibitory input to the spiny stellate cells, which form a major target of layer 4 afferents. The map of the whole cortical circuit shows that there are very few "strong" but many "weak" excitatory projections, each of which may involve only a few percentage of the total complement of excitatory synapses of a single neuron.

A periodic network of neurochemical modules in the inferior colliculus

A new organization has been found in shell nuclei of rat inferior colliculus. Chemically specific modules with a periodic distribution fill about half of layer 2 of external cortex and dorsal cortex. Modules contain clusters of small glutamic acid decarboxylase-positive neurons and large boutons at higher density than in other inferior colliculus subdivisions. The modules are also present in tissue stained for parvalbumin, cytochrome oxidase, nicotinamide adenine dinucleotide phosphate-diaphorase, and acetylcholinesterase. Six to seven bilaterally symmetrical modules extend from the caudal extremity of the external cortex of the inferior colliculus to its rostral pole. Modules are from approximately 800 to 2200 microm long and have areas between 5000 and 40,000 microm2. Modules alternate with immunonegative regions. Similar modules are found in inbred and outbred strains of rat, and in both males and females. They are absent in mouse, squirrel, cat, bat, macaque monkey, and barn owl. Modules are immunonegative for glycine, calbindin, serotonin, and choline acetyltransferase. The auditory cortex and ipsi- and contralateral inferior colliculi project to the external cortex. Somatic sensory influences from the dorsal column nuclei and spinal trigeminal nucleus are the primary ascending sensory input to the external cortex; ascending auditory input to layer 2 is sparse. If the immunopositive modular neurons receive this input, the external cortex could participate in spatial orientation and somatic motor control through its intrinsic and extrinsic projections.

Critical Period Mechanisms in Developing Visual Cortex

Binocular vision is shaped by experience during a critical period of early postnatal life. Loss of visual acuity following monocular deprivation is mediated by a shift of spiking output from the primary visual cortex. Both synaptic and network explanations have been offered for this heightened brain plasticity. Direct experimental control over its timing, duration, and closure has now been achieved through a consideration of balanced local circuit excitation-inhibition. Notably, canonical models of homosynaptic plasticity at excitatory synapses alone (LTP/LTD) fail to produce predictable manipulations of the critical period in vivo. Instead, a late functional maturation of intracortical inhibition is the driving force, with one subtype in particular standing out. Parvalbumin-positive large basket cells that innervate target cell bodies with synapses containing the alpha1-subunit of GABA(A) receptors appear to be critical. With age, these cells are preferentially enwrapped in peri-neuronal nets of extracellular matrix molecules, whose disruption by chondroitinase treatment reactivates ocular dominance plasticity in adulthood. In fact, critical period plasticity is best viewed as a continuum of local circuit computations ending in structural consolidation of inputs. Monocular deprivation induces an increase of endogenous proteolytic (tPA-plasmin) activity and consequently motility of spines followed by their pruning, then re-growth. These early morphological events faithfully reflect competition only during the critical period and lie downstream of excitatory-inhibitory balance on a timescale (of days) consistent with the physiological loss of deprived-eye responses in vivo. Ultimately, thalamic afferents retract or expand accordingly to hardwire the rapid functional changes in connectivity. Competition detected by local inhibitory circuits then implemented at an extracellular locus by proteases represents a novel, cellular understanding of the critical period mechanism. It is hoped that this paradigm shift will lead to novel therapies and training strategies for rehabilitation, recovery from injury, and lifelong learning in adulthood.

An integrative model of binocular vision: a stereo model utilizing interocularly unpaired points produces both depth and binocular rivalry

Half-occluded points (visible only in one eye) are perceived at a certain depth behind the occluding surface without binocular rivalry, even though no disparity is defined at such points. Here we propose a stereo model that reconstructs 3D structures not only from disparity information of interocularly paired points but also from unpaired points. Starting with an array of depth detection cells, we introduce cells that detect unpaired points visible only in the left eye or the right eye (left and right unpaired point detection cells). They interact cooperatively with each other based on optogeometrical constraints (such as uniqueness, cohesiveness, occlusion) to recover the depth and the border of 3D objects. Since it is contradictory for monocularly visible regions to be visible in both eyes, we introduce mutual inhibition between left and right unpaired point detection cells. When input images satisfy occlusion geometry, the model outputs the depth of unpaired points properly. An interesting finding is that when we input two unmatched images, the model shows an unstable output that alternates between interpretations of monocularly visible regions for the left and the right eyes, thereby reproducing binocular rivalry. The results suggest that binocular rivalry arises from the erroneous output of a stereo mechanism that estimates the depth of half-occluded unpaired points. In this sense, our model integrates stereopsis and binocular rivalry, which are usually treated separately, into a single framework of binocular vision. There are two general theories for what the "rivals" are during binocular rivalry: the two eyes, or representations of two stimulus patterns. We propose a new hypothesis that bridges these two conflicting hypotheses: interocular inhibition between representations of monocularly visible regions causes binocular rivalry. Unlike the traditional eye theory, the level of the interocular inhibition introduced here is after binocular convergence at the stage solving the correspondence problem, and thus open to pattern-specific mechanisms.

A model of contextual interactions and contour detection in primary visual cortex

A new model of contour extraction and perceptual grouping in the primary visual cortex is presented and discussed. It differs from previous models since it incorporates four main mechanisms, according to recent physiological data: a feed-forward input from the lateral geniculate nucleus, characterized by Gabor elongated receptive fields; an inhibitory feed-forward input, maximally oriented in the orthogonal direction of the target cell, which suppresses non-optimal stimuli and warrants contrast invariance; an excitatory cortical feedback, which respects co-axial and co-modularity criteria; and a long-range isotropic feedback inhibition. Model behavior has been tested on artificial images with contours of different curvatures, in the presence of considerable noise or in the presence of broken contours, and on a few real images. A sensitivity analysis has also been performed on the role of intracortical synapses. Results show that the model can extract correct contours within acceptable time from image presentation (30-40 ms). The feed-forward input plays a major role to set an initial correct bias for the subsequent feedback and to ensure contrast-invariance. Long-range inhibition is essential to suppress noise, but it may suppress small contours due to excessive competition with greater contours. Cortical excitation sharpens the initial bias and improves saliency of the contours. Model results support the idea that contour extraction is one the primary steps in the visual processing stream, and that local processing in V1 is able to solve this task even in difficult conditions, without the participation of higher visual centers.

Critical period regulation

Neuronal circuits are shaped by experience during critical periods of early postnatal life. The ability to control the timing, duration, and closure of these heightened levels of brain plasticity has recently become experimentally accessible, especially in the developing visual system. This review summarizes our current understanding of known critical periods across several systems and species. It delineates a number of emerging principles: functional competition between inputs, role for electrical activity, structural consolidation, regulation by experience (not simply age), special role for inhibition in the CNS, potent influence of attention and motivation, unique timing and duration, as well as use of distinct molecular mechanisms across brain regions and the potential for reactivation in adulthood. A deeper understanding of critical periods will open new avenues to "nurture the brain"-from international efforts to link brain science and education to improving recovery from injury and devising new strategies for therapy and lifelong learning.

The contribution of vertical and horizontal connections to the receptive field center and surround in V1

Here we review the results of anatomical and physiological studies in tree shrew visual cortex which focus on the contribution of vertical and horizontal inputs to receptive field center and surround properties of layer 2/3 neurons. A fundamental feature of both sets of connections is the arrangement of axon arbors in a fashion that respects both the orientation preference and retinotopic displacement of the target site. As a result, layer 2/3 neurons receive convergent input from populations of layer 4 and other layer 2/3 neurons whose receptive fields are displaced along an axis in visual space that corresponds to their preferred orientation. Although, horizontal connections extend for greater distances across the cortical surface than vertical connections, the majority of these inputs link neurons with overlapping receptive fields, emphasizing that both feed-forward and recurrent circuits are likely to play a constructive role in generating properties (such as orientation selectivity) that define the receptive field center. Both within and beyond the dimensions of the receptive field center, the distribution of horizontal connections accords remarkably well with the magnitude and axial tuning of length summation effects. Taken together, these results suggest a continuum of functional properties that transcends the traditional designation of receptive field center and surround. By extension, we suggest that the perceptual effects of stimulus context may arise from stimulus interactions within the receptive field center as well as between center and surround.

Large-scale modeling of the primary visual cortex: influence of cortical architecture upon neuronal response

A large-scale computational model of a local patch of input layer 4 [Formula: see text] of the primary visual cortex (V1) of the macaque monkey, together with a coarse-grained reduction of the model, are used to understand potential effects of cortical architecture upon neuronal performance. Both the large-scale point neuron model and its asymptotic reduction are described. The work focuses upon orientation preference and selectivity, and upon the spatial distribution of neuronal responses across the cortical layer. Emphasis is given to the role of cortical architecture (the geometry of synaptic connectivity, of the ordered and disordered structure of input feature maps, and of their interplay) as mechanisms underlying cortical responses within the model. Specifically: (i) Distinct characteristics of model neuronal responses (firing rates and orientation selectivity) as they depend upon the neuron's location within the cortical layer relative to the pinwheel centers of the map of orientation preference; (ii) A time independent (DC) elevation in cortico-cortical conductances within the model, in contrast to a "push-pull" antagonism between excitation and inhibition; (iii) The use of asymptotic analysis to unveil mechanisms which underly these performances of the model; (iv) A discussion of emerging experimental data. The work illustrates that large-scale scientific computation--coupled together with analytical reduction, mathematical analysis, and experimental data, can provide significant understanding and intuition about the possible mechanisms of cortical response. It also illustrates that the idealization which is a necessary part of theoretical modeling can outline in sharp relief the consequences of differing alternative interpretations and mechanisms--with final arbiter being a body of experimental evidence whose measurements address the consequences of these analyses.

Specific GABAA circuits for visual cortical plasticity

Weak inhibition within visual cortex early in life prevents experience-dependent plasticity. Loss of responsiveness to an eye deprived of vision can be initiated prematurely by enhancing gamma-aminobutyric acid (GABA)-mediated transmission with benzodiazepines. Here, we use a mouse "knockin" mutation to alpha subunits that renders individual GABA type A (GABA(A)) receptors insensitive to diazepam to show that a particular inhibitory network controls expression of the critical period. Only alpha1-containing circuits were found to drive cortical plasticity, whereas alpha2-enriched connections separately regulated neuronal firing. This dissociation carries implications for models of brain development and the safe design of benzodiazepines for use in infants.

Columnar architecture sculpted by GABA circuits in developing cat visual cortex

The mammalian visual cortex is organized into columns. Here, we examine cortical influences upon developing visual afferents in the cat by altering intrinsic gamma-aminobutyric acid (GABA)-mediated inhibition with benzodiazepines. Local enhancement by agonist (diazepam) infusion did not perturb visual responsiveness, but did widen column spacing. An inverse agonist (DMCM) produced the opposite effect. Thus, intracortical inhibitory circuits shape the geometry of incoming thalamic arbors, suggesting that cortical columnar architecture depends on neuronal activity.

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.