One axon-multiple functions: specificity of lateral inhibitory connections by large basket cells

Angular gyrus: an anatomical case study for association cortex

The angular gyrus is associated with a spectrum of higher order cognitive functions. This mini-review undertakes a broad survey of putative neuroanatomical substrates, guided by the premise that area-specific specializations derive from a combination of extrinsic connections and intrinsic area properties. Three levels of spatial resolution are discussed: cellular, supracellular connectivity, and synaptic micro-scale, with examples necessarily drawn mainly from experimental work with nonhuman primates. A significant factor in the functional specialization of the human parietal cortex is the pronounced enlargement. In addition to "more" cells, synapses, and connections, however, the heterogeneity itself can be considered an important property. Multiple anatomical features support the idea of overlapping and temporally dynamic membership in several brain wide subnetworks, but how these features operate in the context of higher cognitive functions remains for continued investigations.

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.

Impact of Perineuronal Nets on Electrophysiology of Parvalbumin Interneurons, Principal Neurons, and Brain Oscillations: A Review

Perineuronal nets (PNNs) are specialized extracellular matrix structures that surround specific neurons in the brain and spinal cord, appear during critical periods of development, and restrict plasticity during adulthood. Removal of PNNs can reinstate juvenile-like plasticity or, in cases of PNN removal during early developmental stages, PNN removal extends the critical plasticity period. PNNs surround mainly parvalbumin (PV)-containing, fast-spiking GABAergic interneurons in several brain regions. These inhibitory interneurons profoundly inhibit the network of surrounding neurons via their elaborate contacts with local pyramidal neurons, and they are key contributors to gamma oscillations generated across several brain regions. Among other functions, these gamma oscillations regulate plasticity associated with learning, decision making, attention, cognitive flexibility, and working memory. The detailed mechanisms by which PNN removal increases plasticity are only beginning to be understood. Here, we review the impact of PNN removal on several electrophysiological features of their underlying PV interneurons and nearby pyramidal neurons, including changes in intrinsic and synaptic membrane properties, brain oscillations, and how these changes may alter the integration of memory-related information. Additionally, we review how PNN removal affects plasticity-associated phenomena such as long-term potentiation (LTP), long-term depression (LTD), and paired-pulse ratio (PPR). The results are discussed in the context of the role of PV interneurons in circuit function and how PNN removal alters this function.

Conduction Velocity Along the Local Axons of Parvalbumin Interneurons Correlates With the Degree of Axonal Myelination

Parvalbumin-containing (PV+) basket cells in mammalian neocortex are fast-spiking interneurons that regulate the activity of local neuronal circuits in multiple ways. Even though PV+ basket cells are locally projecting interneurons, their axons are myelinated. Can this myelination contribute in any significant way to the speed of action potential propagation along such short axons? We used dual whole cell recordings of synaptically connected PV+ interneurons and their postsynaptic target in acutely prepared neocortical slices from adult mice to measure the amplitude and latency of single presynaptic action potential-evoked inhibitory postsynaptic currents. These same neurons were then imaged with immunofluorescent array tomography, the synapses between them identified and a precise map of the connections was generated, with the exact axonal length and extent of myelin coverage. Our results support that myelination of PV+ basket cells significantly increases conduction velocity, and does so to a degree that can be physiologically relevant.

Altered Balance of Receptive Field Excitation and Suppression in Visual Cortex of Amblyopic Macaque Monkeys

In amblyopia, a visual disorder caused by abnormal visual experience during development, the amblyopic eye (AE) loses visual sensitivity whereas the fellow eye (FE) is largely unaffected. Binocular vision in amblyopes is often disrupted by interocular suppression. We used 96-electrode arrays to record neurons and neuronal groups in areas V1 and V2 of six female macaque monkeys (Macaca nemestrina) made amblyopic by artificial strabismus or anisometropia in early life, as well as two visually normal female controls. To measure suppressive binocular interactions directly, we recorded neuronal responses to dichoptic stimulation. We stimulated both eyes simultaneously with large sinusoidal gratings, controlling their contrast independently with raised-cosine modulators of different orientations and spatial frequencies. We modeled each eye's receptive field at each cortical site using a difference of Gaussian envelopes and derived estimates of the strength of central excitation and surround suppression. We used these estimates to calculate ocular dominance separately for excitation and suppression. Excitatory drive from the FE dominated amblyopic visual cortex, especially in more severe amblyopes, but suppression from both the FE and AEs was prevalent in all animals. This imbalance created strong interocular suppression in deep amblyopes: increasing contrast in the AE decreased responses at binocular cortical sites. These response patterns reveal mechanisms that likely contribute to the interocular suppression that disrupts vision in amblyopes.SIGNIFICANCE STATEMENT Amblyopia is a developmental visual disorder that alters both monocular vision and binocular interaction. Using microelectrode arrays, we examined binocular interaction in primary visual cortex and V2 of six amblyopic macaque monkeys (Macaca nemestrina) and two visually normal controls. By stimulating the eyes dichoptically, we showed that, in amblyopic cortex, the binocular combination of signals is altered. The excitatory influence of the two eyes is imbalanced to a degree that can be predicted from the severity of amblyopia, whereas suppression from both eyes is prevalent in all animals. This altered balance of excitation and suppression reflects mechanisms that may contribute to the interocular perceptual suppression that disrupts vision in amblyopes.

Perisomatic GABAergic synapses of basket cells effectively control principal neuron activity in amygdala networks

Efficient control of principal neuron firing by basket cells is critical for information processing in cortical microcircuits, however, the relative contribution of their perisomatic and dendritic synapses to spike inhibition is still unknown. Using in vitro electrophysiological paired recordings we reveal that in the mouse basal amygdala cholecystokinin- and parvalbumin-containing basket cells provide equally potent control of principal neuron spiking. We performed pharmacological manipulations, light and electron microscopic investigations to show that, although basket cells innervate the entire somato-denditic membrane surface of principal neurons, the spike controlling effect is achieved primarily via the minority of synapses targeting the perisomatic region. As the innervation patterns of individual basket cells on their different postsynaptic partners show high variability, the impact of inhibitory control accomplished by single basket cells is also variable. Our results show that both basket cell types can powerfully regulate the activity in amygdala networks predominantly via their perisomatic synapses.

DOI:http://dx.doi.org/10.7554/eLife.20721.001

Distinct neural mechanisms of distractor suppression in the frontal and parietal lobe

The posterior parietal cortex and the prefrontal cortex are associated with eye movements and visual attention, but their specific contributions are poorly understood. We compared the dorsolateral prefrontal cortex (dlPFC) and the lateral intraparietal area (LIP) in monkeys using a memory saccade task in which a salient distractor flashed at a variable timing and location during the memory delay. We found that the two areas had similar responses to target selection, but made distinct contributions to distractor suppression. Distractor responses were more strongly suppressed and more closely correlated with performance in the dlPFC relative to LIP. Moreover, reversible inactivation of the dlPFC produced much larger increases in distractibility than inactivation of LIP. These findings suggest that LIP and dlPFC mediate different aspects of selective attention. Although both areas can contribute to the perceptual selection of salient information, the dlPFC has a decisive influence on whether and how attended stimulus is linked with actions.

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.

Small-scale module of the rat granular retrosplenial cortex: an example of the minicolumn-like structure of the cerebral cortex

Structures associated with the small-scale module called “minicolumn” can be observed frequently in the cerebral cortex. However, the description of functional characteristics remains obscure. A significant confounding factor is the marked variability both in the definition of a minicolumn and in the diagnostic markers for identifying a minicolumn (see for review, Jones, 2000; DeFelipe et al., 2002; Rockland and Ichinohe, 2004). Within a minicolumn, cell columns are easily visualized by conventional Nissl staining. Dendritic bundles were first discovered with Golgi methods, but are more easily seen with microtubule-associated protein 2 immunohistochemistry. Myelinated axon bundles can be seen by Tau immunohistochemistry or myelin staining. Axon bundles of double bouquet cell can be seen by calbindin immunohistochemistry. The spatial interrelationship among these morphological elements is more complex than expected and is neither clear nor unanimously agreed upon. In this review, I would like to focus first on the minicolumnar structure found in layers 1 and 2 of the rat granular retrosplenial cortex. This modular structure was first discovered as a combination of prominent apical dendritic bundles from layer 2 pyramidal neurons and spatially matched thalamocortical patchy inputs (Wyss et al., 1990). Further examination showed more intricate components of this modular structure, which will be reviewed in this paper. Second, the postnatal development of this structure and potential molecular players for its formation will be reviewed. Thirdly, I will discuss how this modular organization is transformed in mutant rodents with a disorganized layer structure in the cerebral cortex (i.e., reeler mouse and shaking rat Kawasaki). Lastly, the potential significance of this type of module will be discussed.

Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex

Inhibitory interneurons in the cerebral cortex include a vast array of subtypes, varying in their molecular signatures, electrophysiological properties, and connectivity patterns. This diversity suggests that individual inhibitory classes have unique roles in cortical circuits; however, their characterization to date has been limited to broad classifications including many subtypes. We used the Cre/LoxP system, specifically labeling parvalbumin(PV)-expressing interneurons in visual cortex of PV-Cre mice with red fluorescent protein (RFP), followed by targeted loose-patch recordings and two-photon imaging of calcium responses in vivo to characterize the visual receptive field properties of these cells. Despite their relative molecular and morphological homogeneity, we find that PV+ neurons have a diversity of feature-specific visual responses that include sharp orientation and direction-selectivity, small receptive fields, and band-pass spatial frequency tuning. These results suggest that subsets of parvalbumin interneurons are components of specific cortical networks and that perisomatic inhibition contributes to the generation of precise response properties.

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.

Influence of 'feedback' signals on spatial integration in receptive fields of cat area 17 neurons

'Feedback' signals from mammalian extrastriate visual cortices are reported to exert primarily an excitatory influence on the classical receptive field (CRF) of neurons in the primary visual cortex (V1). However, given the much larger CRFs of neurons in extrastriate visual cortices it is not yet understood how feedback signals influence the spatial integration of visual signals by V1 neurons. To investigate this, we reversibly inactivated one of the 'form-processing' extrastriate visual cortices, the postero-temporal visual (PTV) cortex, and examined changes in responses of V1 neurons to drifting grating patches up to 28 degrees in diameter. We found that during inactivation of PTV cortex the magnitude of the responses to CRF-confined stimuli and that to large stimuli inducing maximum suppression (i.e. minimum responses) was significantly reduced, while the spatial extent of the CRF remained largely unaffected. As a result, the relative strength of the surround suppression increased marginally. This effect was apparent in both simple and complex cells. It was also strong and consistent in cells located in supragranular and infragranular layers. For those cells exhibiting some relief from surround suppression or 'counter-suppression' when large stimuli patches were applied, the effect on counter-suppression was heterogeneous. Overall, the relative integrated responses to the 28 degrees grating patches were also decreased when PTV cortex was inactivated. Thus, a substantial reduction in the CRF response and the largely unaffected spatial extent of the CRF as well as a weak surround effect observed in the present study are consistent with a multiplicative scaling effect.

Cortical circuitry implementing graphical models

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

The fractions of short- and long-range connections in the visual cortex

When analyzing synaptic connectivity in a brain tissue slice, it is difficult to discern between synapses made by local neurons and those arising from long-range axonal projections. We analyzed a data set of excitatory neurons and inhibitory basket cells reconstructed from cat primary visual cortex in an attempt to provide a quantitative answer to the question: What fraction of cortical synapses is local, and what fraction is mediated by long-range projections? We found an unexpectedly high proportion of nonlocal synapses. For example, 92% of excitatory synapses near the axis of a 200-microm-diameter iso-orientation column come from neurons located outside the column, and this fraction remains high--76%--even for an 800-micromocular dominance column. The long-range nature of connectivity has dramatic implications for experiments in cortical tissue slices. Our estimate indicates that in a 300-microm-thick section cut perpendicularly to the cortical surface, the number of viable excitatory synapses is reduced to about 10%, and the number of synapses made by inhibitory basket cell axons is reduced to 38%. This uneven reduction in the numbers of excitatory and inhibitory synapses changes the excitation-inhibition balance by a factor of 3.8 toward inhibition, and may result in cortical tissue that is less excitable than in vivo. We found that electrophysiological studies conducted in tissue sections may significantly underestimate the extent of cortical connectivity; for example, for some projections, the reported probabilities of finding connected nearby neuron pairs in slices could understate the in vivo probabilities by a factor of 3.

Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation

PURPOSE

A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of the evolving bursting activity, as well as effects due to network stimulation.

METHODS

The model represents a cortical region of 1.6 mm x 1.6mm, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. There are a total of 65,536 modeled single compartment neurons that operate according to a version of Hodgkin-Huxley dynamics. The intercellular wiring is based on histological studies and our previous modeling efforts.

RESULTS

The bursting phase is characterized by a flat frequency spectrum. Stimulation pulses are applied to this modeled network, with an electric field provided by a 1mm radius circular electrode represented mathematically in the simulation. A phase dependence to the post-stimulation quiescence is demonstrated, with local relative maxima in efficacy occurring before or during the network depolarization phase in the underlying activity. Brief periods of network insensitivity to stimulation are also demonstrated. The phase dependence was irregular and did not reach statistical significance when averaged over the full 2.5s of simulated bursting investigated. This result provides comparison with previous in vivo studies which have also demonstrated increased efficacy of stimulation when pulses are applied at the peak of the local field potential during cortical after discharges. The network bursting is synchronous when comparing the different neuron classes represented up to an uncertainty of 10 ms. Studies performed with an excitatory chandelier cell component demonstrated increased synchronous bursting in the model, as predicted from experimental work.

CONCLUSIONS

This large-scale multi-neuron neural network simulation reproduces many aspects of evolving cortical bursting behavior as well as the timing-dependent effects of electrical stimulation on that bursting.

Studies of stimulus parameters for seizure disruption using neural network simulations

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 mum x 800 mum region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.

Local potential connectivity in cat primary visual cortex

Time invariant description of synaptic connectivity in cortical circuits may be precluded by the ongoing growth and retraction of dendritic spines accompanied by the formation and elimination of synapses. On the other hand, the spatial arrangement of axonal and dendritic branches appears stable. This suggests that an invariant description of connectivity can be cast in terms of potential synapses, which are locations in the neuropil where an axon branch of one neuron is proximal to a dendritic branch of another neuron. In this paper, we attempt to reconstruct the potential connectivity in local cortical circuits of the cat primary visual cortex (V1). Based on multiple single-neuron reconstructions of axonal and dendritic arbors in 3 dimensions, we evaluate the expected number of potential synapses and the probability of potential connectivity among excitatory (pyramidal and spiny stellate) neurons and inhibitory basket cells. The results provide a quantitative description of structural organization of local cortical circuits. For excitatory neurons from different cortical layers, we compute local domains, which contain their potentially pre- and postsynaptic excitatory partners. These domains have columnar shapes with laminar specific radii and are roughly of the size of the ocular dominance column. Therefore, connections between most excitatory neurons in the ocular dominance column can be implemented by local synaptogenesis. Structural connectivity involving inhibitory basket cells is generally weaker than excitatory connectivity. Here, only nearby neurons are capable of establishing more than one potential synapse, implying that within the ocular dominance column these connections have more limited potential for circuit remodeling.

The distributed auditory cortex

A synthesis of cat auditory cortex (AC) organization is presented in which the extrinsic and intrinsic connections interact to derive a unified profile of the auditory stream and use it to direct and modify cortical and subcortical information flow. Thus, the thalamocortical input provides essential sensory information about peripheral stimulus events, which AC redirects locally for feature extraction, and then conveys to parallel auditory, multisensory, premotor, limbic, and cognitive centers for further analysis. The corticofugal output influences areas as remote as the pons and the cochlear nucleus, structures whose effects upon AC are entirely indirect, and it has diverse roles in the transmission of information through the medial geniculate body and inferior colliculus. The distributed AC is thus construed as a functional network in which the auditory percept is assembled for subsequent redistribution in sensory, premotor, and cognitive streams contingent on the derived interpretation of the acoustic events. The confluence of auditory and multisensory streams likely precedes cognitive processing of sound. The distributed AC constitutes the largest and arguably the most complete representation of the auditory world. Many facets of this scheme may apply in rodent and primate AC as well. We propose that the distributed auditory cortex contributes to local processing regimes in regions as disparate as the frontal pole and the cochlear nucleus to construct the acoustic percept.

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.

Controlling synaptic input patterns in vitro by dynamic photo stimulation

Recent experimental and theoretical work indicates that both the intensity and the temporal structure of synaptic activity strongly modulate the integrative properties of single neurons in the intact brain. However, studying these effects experimentally is complicated by the fact that, in experimental systems, network activity is either absent, as in the acute slice preparation, or difficult to monitor and to control, as in in vivo recordings. Here, we present a new implementation of neurotransmitter uncaging in acute brain slices that uses functional projections to generate tightly controlled, spatio-temporally structured synaptic input patterns in individual neurons. For that, a set of presynaptic neurons is activated in a precisely timed sequence through focal photolytic release of caged glutamate with the help of a fast laser scanning system. Integration of synaptic inputs can be studied in postsynaptic neurons that are not directly stimulated with the laser, but receive input from the targeted neurons through intact axonal projections. Our new approach of dynamic photo stimulation employs functional synapses, accounts for their spatial distribution on the dendrites, and thus allows study of the integrative properties of single neurons with physiologically realistic input. Data obtained with our new technique suggest that, not only the neuronal spike generator, but also synaptic transmission and dendritic integration in neocortical pyramidal cells, can be highly reliable.

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.

Neuronal circuits of the neocortex

We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.

Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory

A conspicuous feature of cortical organization is the wide diversity of inhibitory interneurons; their differential computational functions remain unclear. Here we propose a local cortical circuit in which three major subtypes of interneurons play distinct roles. In a model designed for spatial working memory, stimulus tuning of persistent activity arises from the concerted action of widespread inhibition mediated by perisoma-targeting (parvalbumin-containing) interneurons and localized disinhibition of pyramidal cells via interneuron-targeting (calretinin-containing) interneurons. Moreover, resistance against distracting stimuli (a fundamental property of working memory) is dynamically controlled by dendrite-targeting (calbindin-containing) interneurons. The experimental observation of inverted tuning curves of monkey prefrontal neurons recorded during working memory supports a key model prediction. This work suggests a framework for understanding the division of labor and cooperation among different inhibitory cell types in a recurrent cortical circuit.