Map of the synapses onto layer 4 basket cells of the primary visual cortex of the cat

Physiological features of parvalbumin-expressing GABAergic interneurons contributing to high-frequency oscillations in the cerebral cortex

Parvalbumin-expressing (PV+) inhibitory interneurons drive gamma oscillations (30-80 Hz), which underlie higher cognitive functions. In this review, we discuss two groups/aspects of fundamental properties of PV+ interneurons. In the first group (dubbed Before Axon), we list properties representing optimal synaptic integration in PV+ interneurons designed to support fast oscillations. For example: [i] Information can neither enter nor leave the neocortex without the engagement of fast PV+ -mediated inhibition; [ii] Voltage responses in PV+ interneuron dendrites integrate linearly to reduce impact of the fluctuations in the afferent drive; and [iii] Reversed somatodendritic Rm gradient accelerates the time courses of synaptic potentials arriving at the soma. In the second group (dubbed After Axon), we list morphological and biophysical properties responsible for (a) short synaptic delays, and (b) efficient postsynaptic outcomes. For example: [i] Fast-spiking ability that allows PV+ interneurons to outpace other cortical neurons (pyramidal neurons). [ii] Myelinated axon (which is only found in the PV+ subclass of interneurons) to secure fast-spiking at the initial axon segment; and [iii] Inhibitory autapses - autoinhibition, which assures brief biphasic voltage transients and supports postinhibitory rebounds. Recent advent of scientific tools, such as viral strategies to target PV cells and the ability to monitor PV cells via in vivo imaging during behavior, will aid in defining the role of PV cells in the CNS. Given the link between PV+ interneurons and cognition, in the future, it would be useful to carry out physiological recordings in the PV+ cell type selectively and characterize if and how psychiatric and neurological diseases affect initiation and propagation of electrical signals in this cortical sub-circuit. Voltage imaging may allow fast recordings of electrical signals from many PV+ interneurons simultaneously.

Trafficking proteins show limited differences in mobility across different postsynaptic spines

The function of the postsynaptic compartment is based on the presence and activity of postsynaptic receptors, whose dynamics are controlled by numerous scaffolding, signaling and trafficking proteins. Although the receptors and the scaffolding proteins have received substantial attention, the trafficking proteins have not been investigated extensively. Their mobility rates are unknown, and it is unclear how the postsynaptic environment affects their dynamics. To address this, we analyzed several trafficking proteins (α-synuclein, amphiphysin, calmodulin, doc2a, dynamin, and endophilin), estimating their movement rates in the dendritic shaft, as well as in morphologically distinct "mushroom" and "stubby" postsynapse types. The diffusion parameters were surprisingly similar across dendritic compartments, and a few differences between proteins became evident only in the presence of a synapse neck. We conclude that the movement of trafficking proteins is not strongly affected by the postsynaptic compartment, in stark contrast to the presynapse, which regulates strongly the movement of such proteins.

The impact of neuron morphology on cortical network architecture

The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons, depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density, and the cellular diversity of the neuropil. The higher these three factors are, the more recurrent is the topology of the network. Conversely, the lower these factors are, the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular, and network scales from the specific morphological properties of its neuronal constituents.

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Neuronal network architectures reflect the morphologies of their constituents

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Morphology predicts nonrandom connectivity from subcellular to network scales

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Morphology predicts connectivity patterns consistent with those observed empirically

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Neuron morphology is a major source for wiring specificity in the cerebral cortex

A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex

How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.

Translaminar circuits formed by the pyramidal cells in the superficial layers of cat visual cortex

Pyramidal cells in the superficial layers of the neocortex provide a major excitatory projection to layer 5, which contains the pyramidal cells that project to subcortical motor-related targets. Both structurally and functionally rather little is known about this interlaminar pathway, especially in higher mammals. Here, we made sparse ultrastructural reconstructions of the projection to layer 5 of three pyramidal neurons from layer 3 in cat V1 whose morphology, physiology, and synaptic connections with layers 2 and 3 were known. The dominant targets of the 74 identified synapses in layer 5 were the dendritic spines of pyramidal cells. The fractions of target spiny dendrites were 59, 61, and 84% for the three cells, with the remaining targets being dendrites of smooth neurons. These fractions were similar to the distribution of targets of unlabeled asymmetric synapses in the surrounding neuropil. Serial section reconstructions revealed that the target dendrites were heterogenous in morphology, indicating that different cell types are innervated. This new evidence indicates that the descending projection from the superficial layer pyramidal cells does not simply drive the output pyramidal cells that project to cortical and subcortical targets, but participates in the complex circuitry of the deep cortical layers.

Spine Dynamics: Are They All the Same?

Since Cajal's first drawings of Golgi stained neurons, generations of researchers have been fascinated by the small protrusions, termed spines, studding many neuronal dendrites. Most excitatory synapses in the mammalian CNS are located on dendritic spines, making spines convenient proxies for excitatory synaptic presence. When in vivo imaging revealed that dendritic spines are dynamic structures, their addition and elimination were interpreted as excitatory synapse gain and loss, respectively. Spine imaging has since become a popular assay for excitatory circuit remodeling. In this review, we re-evaluate the validity of using spine dynamics as a straightforward reflection of circuit rewiring. Recent studies tracking both spines and synaptic markers in vivo reveal that 20% of spines lack PSD-95 and are short lived. Although they account for most spine dynamics, their remodeling is unlikely to impact long-term network structure. We discuss distinct roles that spine dynamics can play in circuit remodeling depending on synaptic content.

Axon topography of layer 6 spiny cells to orientation map in the primary visual cortex of the cat (area 18)

To uncover the functional topography of layer 6 neurons, optical imaging was combined with three-dimensional neuronal reconstruction. Apical dendrite morphology of 23 neurons revealed three distinct types. Type Aa possessed a short apical dendrite with many oblique branches, Type Ab was characterized by a short and less branched apical dendrite, whereas Type B had a long apical dendrite with tufts in layer 2. Each type had a similar number of boutons, yet their spatial distribution differed from each other in both radial and horizontal extent. Boutons of Type Aa and Ab were almost restricted to the column of the parent soma with a laminar preference to layer 4 and 5/6, respectively. Only Type B contributed to long horizontal connections (up to 1.5 mm) mostly in deep layers. For all types, bouton distribution on orientation map showed an almost equal occurrence at iso- (52.6 ± 18.8 %) and non-iso-orientation (oblique, 27.7 ± 14.9 % and cross-orientation 19.7 ± 10.9 %) sites. Spatial convergence of axons of nearby layer 6 spiny neurons depended on soma separation of the parent cells, but only weakly on orientation preference, contrary to orientation dependence of converging axons of layer 4 spiny cells. The results show that layer 6 connections have only a weak dependence on orientation preference compared with those of layers 2/3 (Buzás et al., J Comp Neurol 499:861–881, 2006) and 4 (Karube and Kisvárday, Cereb Cortex 21:1443–1458, 2011).

Selective Maturation of Temporal Dynamics of Intracortical Excitatory Transmission at the Critical Period Onset

Although the developmental maturation of cortical inhibitory synapses is known to be a critical factor in gating the onset of critical period (CP) for experience-dependent cortical plasticity, how synaptic transmission dynamics of other cortical synapses are regulated during the transition to CP remains unknown. Here, by systematically examining various intracortical synapses within layer 4 of the mouse visual cortex, we demonstrate that synaptic temporal dynamics of intracortical excitatory synapses on principal cells (PCs) and inhibitory parvalbumin- or somatostatin-expressing cells are selectively regulated before the CP onset, whereas those of intracortical inhibitory synapses and long-range thalamocortical excitatory synapses remain unchanged. This selective maturation of synaptic dynamics results from a ubiquitous reduction of presynaptic release and is dependent on visual experience. These findings provide an additional essential circuit mechanism for regulating CP timing in the developing visual cortex.

Pyramidal cells make specific connections onto smooth (GABAergic) neurons in mouse visual cortex

Light and electron microscopy of the primary visual cortex of mice indicates that pyramidal neurons connect preferentially to inhibitory neurons.

One of the hallmarks of neocortical circuits is the predominance of recurrent excitation between pyramidal neurons, which is balanced by recurrent inhibition from smooth GABAergic neurons. It has been previously described that in layer 2/3 of primary visual cortex (V1) of cat and monkey, pyramidal cells filled with horseradish peroxidase connect approximately in proportion to the spiny (excitatory, 95% and 81%, respectively) and smooth (GABAergic, 5% and 19%, respectively) dendrites found in the neuropil. By contrast, a recent ultrastructural study of V1 in a single mouse found that smooth neurons formed 51% of the targets of the superficial layer pyramidal cells. This suggests that either the neuropil of this particular mouse V1 had a dramatically different composition to that of V1 in cat and monkey, or that smooth neurons were specifically targeted by the pyramidal cells in that mouse. We tested these hypotheses by examining similar cells filled with biocytin in a sample of five mice. We found that the average composition of the neuropil in V1 of these mice was similar to that described for cat and monkey V1, but that the superficial layer pyramidal cells do form proportionately more synapses with smooth dendrites than the equivalent neurons in cat or monkey. These distributions may underlie the distinct differences in functional architecture of V1 between rodent and higher mammals.

The mammalian visual cortex, which is part of the cerebral cortex, contains 50 to 100 thousands of neurons per cubic millimetre, most of which are excitatory (85%) and the minority, inhibitory (15%). Unlike neurons in the retina, neurons in the visual cortex are preferentially activated by lines or edges of a particular orientation. This is termed a neuron's “orientation preference.” In the visual cortex of higher mammals like cats and monkeys, neurons that share an orientation preference are clustered in functional columns. However, in rodents like mice, orientation preferences are randomly distributed. In this study, we investigate whether the differences between columnar and non-columnar cortex is correlated with differences in the connectivity patterns between excitatory and inhibitory neurons. Using light and electron microscopy, we mapped the connectivity of pyramidal neurons—the primary excitatory neurons—in the superficial layers of the primary visual cortex (V1) of mice. Our results show that the ratio of excitatory-inhibitory neurons in mouse V1 is similar to that of cat or monkey V1, but in mouse V1 local pyramidal neurons target proportionately many more inhibitory neurons compared to what other studies found in cat or monkey. This difference may indicate the significance of inhibition in maintaining orientation selectivity in the non-columnar visual cortex of rodents like mice and is a distinct difference in the architecture of V1 between mice and higher mammals.

Structural determinants underlying the high efficacy of synaptic transmission and plasticity at synaptic boutons in layer 4 of the adult rat 'barrel cortex'

Excitatory layer 4 (L4) neurons in the 'barrel field' of the rat somatosensory cortex represent an important component in thalamocortical information processing. However, no detailed information exists concerning the quantitative geometry of synaptic boutons terminating on these neurons. Thus, L4 synaptic boutons were investigated using serial ultrathin sections and subsequent quantitative 3D reconstructions. In particular, parameters representing structural correlates of synaptic transmission and plasticity such as the number, size and distribution of pre- and postsynaptic densities forming the active zone (AZ) and of the three functionally defined pools of synaptic vesicles were analyzed. L4 synaptic boutons varied substantially in shape and size; the majority had a single, but large AZ with opposing pre- and postsynaptic densities that matched perfectly in size and position. More than a third of the examined boutons showed perforations of the postsynaptic density. Synaptic boutons contained on average a total pool of 561 ± 108 vesicles, with ~5% constituting the putative readily releasable, ~23% the recycling, and the remainder the reserve pool. These pools are comparably larger than other characterized central synapses. Synaptic complexes were surrounded by a dense network of fine astrocytic processes that reached as far as the synaptic cleft, thus regulating the temporal and spatial glutamate concentration, and thereby shaping the unitary EPSP amplitude. In summary, the geometry and size of AZs, the comparably large readily releasable and recycling pools, together with the tight astrocytic ensheathment, may explain and contribute to the high release probability, efficacy and modulation of synaptic transmission at excitatory L4 synaptic boutons. Moreover, the structural variability as indicated by the geometry of L4 synaptic boutons, the presence of mitochondria and the size and shape of the AZs strongly suggest that synaptic reliability, strength and plasticity is governed and modulated individually at excitatory L4 synaptic boutons.

Mechanisms of seizure propagation in 2-dimensional centre-surround recurrent networks

Understanding how seizures spread throughout the brain is an important problem in the treatment of epilepsy, especially for implantable devices that aim to avert focal seizures before they spread to, and overwhelm, the rest of the brain. This paper presents an analysis of the speed of propagation in a computational model of seizure-like activity in a 2-dimensional recurrent network of integrate-and-fire neurons containing both excitatory and inhibitory populations and having a difference of Gaussians connectivity structure, an approximation to that observed in cerebral cortex. In the same computational model network, alternative mechanisms are explored in order to simulate the range of seizure-like activity propagation speeds (0.1-100 mm/s) observed in two animal-slice-based models of epilepsy: (1) low extracellular [Formula: see text], which creates excess excitation and (2) introduction of gamma-aminobutyric acid (GABA) antagonists, which reduce inhibition. Moreover, two alternative connection topologies are considered: excitation broader than inhibition, and inhibition broader than excitation. It was found that the empirically observed range of propagation velocities can be obtained for both connection topologies. For the case of the GABA antagonist model simulation, consistent with other studies, it was found that there is an effective threshold in the degree of inhibition below which waves begin to propagate. For the case of the low extracellular [Formula: see text] model simulation, it was found that activity-dependent reductions in inhibition provide a potential explanation for the emergence of slowly propagating waves. This was simulated as a depression of inhibitory synapses, but it may also be achieved by other mechanisms. This work provides a localised network understanding of the propagation of seizures in 2-dimensional centre-surround networks that can be tested empirically.

Terminals of the major thalamic input to visual cortex are devoid of synapsin proteins

Synapsins are nerve-terminal proteins that are linked to synaptic transmission and key factors in several forms of synaptic plasticity. While synapsins are generally assumed to be ubiquitous in synaptic terminals, whether they are excluded from certain types of terminals is of interest. In the visual pathway, synapsins are lacking in photoreceptor and bipolar cell terminals as well as in retinogeniculate synapses. These are the terminals of the first three feedforward synapses in the visual pathway, implying that lack of synapsins may be a common property of terminals that provide the primary driver activity onto their postsynaptic neurons. To further investigate this idea, we studied the fourth driver synapse, thalamocortical synapses in visual cortex, using glutamatergic terminal antibody markers anti-VGluT1 and VGluT2, anti-Synapsin I and II, and confocal microscopy to analyze co-localization of these proteins in terminals. We also used pre-embedding immunocytochemical labeling followed by electron microscopy to investigate morphological similarities or differences between terminals containing synapsins or VGluT2. In visual cortex, synapsin coincided extensively with non-TC-neuron marker, VGluT1, while thalamocortical terminal marker VGluT2 and synapsin overlap was sparse. Morphologically, synapsin-stained terminals were smaller than non-stained, while VGluT2-positive thalamocortical terminals constituted the largest terminals in cortex. The size discrepancy between synapsin- and VGluT2-positive terminals, together with the complementary staining patterns, indicates that thalamocortical synapses are devoid of synapsins, and support the hypothesis that afferent sensory information is consistently transmitted without the involvement of synapsins. Furthermore, VGluT2 and synapsins were colocalized in other brain structures, suggesting that lack of synapsins is not a property of VGluT2-containing terminals, but a property of primary driver terminals in the visual system.

Fast recruitment of recurrent inhibition in the cat visual cortex

Neurons of the same column in L4 of the cat visual cortex are likely to share the same sensory input from the same region of the visual field. Using visually-guided patch clamp recordings we investigated the biophysical properties of the synapses of neighboring layer 4 neurons. We recorded synaptic connections between all types of excitatory and inhibitory neurons in L4. The E–E, E–I, and I–E connections had moderate CVs and failure rates. However, E–I connections had larger amplitudes, faster rise-times, and shorter latencies. Identification of the sites of putative synaptic contacts together with compartmental simulations on 3D reconstructed cells, suggested that E–I synapses tended to be located on proximal dendritic branches, which would explain their larger EPSP amplitudes and faster kinetics. Excitatory and inhibitory synapses were located at the same distance on distal dendrites of excitatory neurons. We hypothesize that this co-localization and the fast recruitment of local inhibition provides an efficient means of modulating excitation in a precisely timed way.

Parvalbumin-producing cortical interneurons receive inhibitory inputs on proximal portions and cortical excitatory inputs on distal dendrites

To examine inputs to parvalbumin (PV)-producing interneurons, we generated transgenic mice expressing somatodendritic membrane-targeted green fluorescent protein specifically in the interneurons, and completely visualized their dendrites and somata. Using immunolabeling for vesicular glutamate transporter (VGluT)1, VGluT2, and vesicular GABA transporter, we found that VGluT1-positive terminals made contacts 4- and 3.1-fold more frequently with PV-producing interneurons than VGluT2-positive and GABAergic terminals, respectively, in the primary somatosensory cortex. Even in layer 4, where VGluT2-positive terminals were most densely distributed, VGluT1-positive inputs to PV-producing interneurons were 2.4-fold more frequent than VGluT2-positive inputs. Furthermore, although GABAergic inputs to PV-producing interneurons were as numerous as VGluT2-positive inputs in most cortical layers, GABAergic inputs clearly preferred the proximal dendrites and somata of the interneurons, indicating that the sites of GABAergic inputs were more optimized than those of VGluT2-positive inputs. Simulation analysis with a PV-producing interneuron model compatible with the present morphological data revealed a plausible reason for this observation, by showing that GABAergic and glutamatergic postsynaptic potentials evoked by inputs to distal dendrites were attenuated to 60 and 87%, respectively, of those evoked by somatic inputs. As VGluT1-positive and VGluT2-positive axon terminals were presumed to be cortical and thalamic glutamatergic inputs, respectively, cortical excitatory inputs to PV-producing interneurons outnumbered the thalamic excitatory and intrinsic inhibitory inputs more than two-fold in any cortical layer. Although thalamic inputs are known to evoke about two-fold larger unitary excitatory postsynaptic potentials than cortical ones, the present results suggest that cortical inputs control PV-producing interneurons at least as strongly as thalamic inputs.

Effects of transcranial Direct Current Stimulation (tDCS) on cortical activity: a computational modeling study

Although it is well-admitted that transcranial Direct Current Stimulation (tDCS) allows for interacting with brain endogenous rhythms, the exact mechanisms by which externally-applied fields modulate the activity of neurons remain elusive. In this study a novel computational model (a neural mass model including subpopulations of pyramidal cells and inhibitory interneurons mediating synaptic currents with either slow or fast kinetics) of the cerebral cortex was elaborated to investigate the local effects of tDCS on neuronal populations based on an in-vivo experimental study. Model parameters were adjusted to reproduce evoked potentials (EPs) recorded from the somatosensory cortex of the rabbit in response to air-puffs applied on the whiskers. EPs were simulated under control condition (no tDCS) as well as under anodal and cathodal tDCS fields. Results first revealed that a feed-forward inhibition mechanism must be included in the model for accurate simulation of actual EPs (peaks and latencies). Interestingly, results revealed that externally-applied fields are also likely to affect interneurons. Indeed, when interneurons get polarized then the characteristics of simulated EPs become closer to those of real EPs. In particular, under anodal tDCS condition, more realistic EPs could be obtained when pyramidal cells were depolarized and, simultaneously, slow (resp. fast) interneurons became de- (resp. hyper-) polarized. Geometrical characteristics of interneurons might provide some explanations for this effect.

Synchronous chaos and broad band gamma rhythm in a minimal multi-layer model of primary visual cortex

Visually induced neuronal activity in V1 displays a marked gamma-band component which is modulated by stimulus properties. It has been argued that synchronized oscillations contribute to these gamma-band activity. However, analysis of Local Field Potentials (LFPs) across different experiments reveals considerable diversity in the degree of oscillatory behavior of this induced activity. Contrast-dependent power enhancements can indeed occur over a broad band in the gamma frequency range and spectral peaks may not arise at all. Furthermore, even when oscillations are observed, they undergo temporal decorrelation over very few cycles. This is not easily accounted for in previous network modeling of gamma oscillations. We argue here that interactions between cortical layers can be responsible for this fast decorrelation. We study a model of a V1 hypercolumn, embedding a simplified description of the multi-layered structure of the cortex. When the stimulus contrast is low, the induced activity is only weakly synchronous and the network resonates transiently without developing collective oscillations. When the contrast is high, on the other hand, the induced activity undergoes synchronous oscillations with an irregular spatiotemporal structure expressing a synchronous chaotic state. As a consequence the population activity undergoes fast temporal decorrelation, with concomitant rapid damping of the oscillations in LFPs autocorrelograms and peak broadening in LFPs power spectra. We show that the strength of the inter-layer coupling crucially affects this spatiotemporal structure. We predict that layer VI inactivation should induce global changes in the spectral properties of induced LFPs, reflecting their slower temporal decorrelation in the absence of inter-layer feedback. Finally, we argue that the mechanism underlying the emergence of synchronous chaos in our model is in fact very general. It stems from the fact that gamma oscillations induced by local delayed inhibition tend to develop chaos when coupled by sufficiently strong excitation.

Visual stimulation elicits neuronal responses in visual cortex. When the contrast of the used stimuli increases, the power of this induced activity is boosted over a broad frequency range (30–100 Hz), called the “gamma band.” It would be tempting to hypothesize that this phenomenon is due to the emergence of oscillations in which many neurons fire collectively in a rhythmic way. However, previous models trying to explain contrast-related power enhancements using synchronous oscillations failed to reproduce the observed spectra because they originated unrealistically sharp spectral peaks. The aim of our study is to reconcile synchronous oscillations with broad-band power spectra. We argue here that, thanks to the interaction between neuronal populations at different depths in the cortical tissue, the induced oscillatory responses are synchronous, but, at the same time, chaotic. The chaotic nature of the dynamics makes it possible to have broad-band power spectra together with synchrony. Our modeling study allows us formulating qualitative experimental predictions that provide a potential test for our theory. We predict that if the interactions between cortical layers are suppressed, for instance by inactivating neurons in deep layers, the induced responses might become more regular and narrow isolated peaks might develop in their power spectra.

Multiple clusters of release sites formed by individual thalamic afferents onto cortical interneurons ensure reliable transmission

Thalamic afferents supply the cortex with sensory information by contacting both excitatory neurons and inhibitory interneurons. Interestingly, thalamic contacts with interneurons constitute such a powerful synapse that even one afferent can fire interneurons, thereby driving feedforward inhibition. However, the spatial representation of this potent synapse on interneuron dendrites is poorly understood. Using Ca imaging and electron microscopy we show that an individual thalamic afferent forms multiple contacts with the interneuronal proximal dendritic arbor, preferentially near branch points. More contacts are correlated with larger amplitude synaptic responses. Each contact, consisting of a single bouton, can release up to seven vesicles simultaneously, resulting in graded and reliable Ca transients. Computational modeling indicates that the release of multiple vesicles at each contact minimally reduces the efficiency of the thalamic afferent in exciting the interneuron. This strategy preserves the spatial representation of thalamocortical inputs across the dendritic arbor over a wide range of release conditions.

Distinct functions for direct and transthalamic corticocortical connections

Essentially all cortical areas receive thalamic inputs and send outputs to lower motor centers. Cortical areas communicate with each other by means of direct corticocortical and corticothalamocortical pathways, often organized in parallel. We distinguish these functionally, stressing that the transthalamic pathways are class 1 (formerly known as “driver”) pathways capable of transmitting information, whereas the direct pathways vary, being either class 2 (formerly known as “modulator”) or class 1. The transthalamic pathways provide a thalamic gate that can be open or closed (and otherwise more subtly modulated), and these inputs to the thalamus are generally branches of axons with motor functions. Thus the transthalamic corticocortical pathways that can be gated carry information about the cortical processing in one cortical area and also about the motor instructions currently being issued from that area and copied to other cortical areas.

On the road to invariant object recognition: how cortical area V2 transforms absolute to relative disparity during 3D vision

Invariant recognition of objects depends on a hierarchy of cortical stages that build invariance gradually. Binocular disparity computations are a key part of this transformation. Cortical area V1 computes absolute disparity, which is the horizontal difference in retinal location of an image in the left and right foveas. Many cells in cortical area V2 compute relative disparity, which is the difference in absolute disparity of two visible features. Relative, but not absolute, disparity is invariant under both a disparity change across a scene and vergence eye movements. A neural network model is introduced which predicts that shunting lateral inhibition of disparity-sensitive layer 4 cells in V2 causes a peak shift in cell responses that transforms absolute disparity from V1 into relative disparity in V2. This inhibitory circuit has previously been implicated in contrast gain control, divisive normalization, selection of perceptual groupings, and attentional focusing. The model hereby links relative disparity to other visual functions and thereby suggests new ways to test its mechanistic basis. Other brain circuits are reviewed wherein lateral inhibition causes a peak shift that influences behavioral responses.

Network anatomy and in vivo physiology of visual cortical neurons

In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron's function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property—the preferred stimulus orientation—of a group of neurons in the mouse primary visual cortex. We then used large-scale electron microscopy (EM) of serial thin sections to trace a portion of these neurons’ local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.

Neocortical layer 4 as a pluripotent function linearizer

A highly effective kernel-based strategy used in machine learning is to transform the input space into a new "feature" space where nonlinear problems become linear and more readily solvable with efficient linear techniques. We propose that a similar "problem-linearization" strategy is used by the neocortical input layer 4 to reduce the difficulty of learning nonlinear relations between the afferent inputs to a cortical column and its to-be-learned upper layer outputs. The key to this strategy is the presence of broadly tuned feed-forward inhibition in layer 4: it turns local layer 4 domains into functional analogs of radial basis function networks, which are known for their universal function approximation capabilities. With the use of a computational model of layer 4 with feed-forward inhibition and Hebbian afferent connections, self-organized on natural images to closely match structural and functional properties of layer 4 of the cat primary visual cortex, we show that such layer-4-like networks have a strong intrinsic tendency to perform input transforms that automatically linearize a broad repertoire of potential nonlinear functions over the afferent inputs. This capacity for pluripotent function linearization, which is highly robust to variations in network parameters, suggests that layer 4 might contribute importantly to sensory information processing as a pluripotent function linearizer, performing such a transform of afferent inputs to a cortical column that makes it possible for neurons in the upper layers of the column to learn and perform their complex functions using primarily linear operations.

Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex

Different subtypes of GABAergic neurons in sensory cortex exhibit diverse morphology, histochemical markers, and patterns of connectivity. These subtypes likely play distinct roles in cortical function, but their in vivo response properties remain unclear. We used in vivo calcium imaging, combined with immunohistochemical and genetic labels, to record visual responses in excitatory neurons and up to three distinct subtypes of GABAergic neurons (immunoreactive for parvalbumin, somatostatin, or vasoactive intestinal peptide) in layer 2/3 of mouse visual cortex. Excitatory neurons had sharp response selectivity for stimulus orientation and spatial frequency, while all GABAergic subtypes had broader selectivity. Further, bias in the responses of GABAergic neurons toward particular orientations or spatial frequencies tended to reflect net biases of the surrounding neurons. These results suggest that the sensory responses of layer 2/3 GABAergic neurons reflect the pooled activity of the surrounding population--a principle that may generalize across species and sensory modalities.

Bifurcation analysis of neural mass models: Impact of extrinsic inputs and dendritic time constants

Neural mass models (NMMs) explain dynamics of neuronal populations and were designed to strike a balance between mathematical simplicity and biological plausibility. They are currently widely used as generative models for noninvasive electrophysiological brain measurements; that is, magneto- and electroencephalography (M/EEG). Here, we systematically describe the oscillatory regimes which a NMM of a single cortical source with extrinsic input from other cortical and subcortical areas to each subpopulation can explain. For this purpose, we used bifurcation analysis to describe qualitative changes in system behavior in response to quantitative input changes. This approach allowed us to describe sequences of oscillatory regimes, given some specific input trajectory. We systematically classified these sequential phenomena and mapped them into parameter space. Our analysis suggests a principled scheme of how complex M/EEG phenomena can be modeled parsimoniously on two time scales: While the system displays fast oscillations, it slowly traverses phase space to another qualitatively different oscillatory regime, depending on the input dynamics. The resulting scheme is useful for applications where one needs to model an ordered sequence of switching between qualitatively different oscillatory regimes, for example, in pharmacological interventions, epilepsy, sleep, or context-induced state changes.

The proportion of synapses formed by the axons of the lateral geniculate nucleus in layer 4 of area 17 of the cat

The connection between the dorsal lateral geniculate nucleus (dLGN) and area 17 of the cat is a classical model for studying thalamocortical relations. We investigated the proportion of asymmetric synapses in layer 4 of area 17 of cats formed by axons of the dLGN, because this is an important morphological parameter in understanding the impact of dLGN axons on their target neurons. Although the present consensus is that this proportion is small, the exact percentage remains in doubt. Most previous work estimated that the thalamus contributes less than 10% of excitatory synapses in layer 4, but one estimate was as high as 28%. Two issues contribute to these widely different estimates, one being the tracers used, the other being the use of biased stereological approaches. We have addressed both of these issues. Thalamic axons were labeled in vivo by injections of biotinylated dextran amine into the A lamina of the dLGN of anesthetized cats. After processing, the brain was cut serially and prepared for light and electron microscopy. The density of asymmetric synapses in the neuropil and the density of synapses formed by labeled dLGN boutons were measured by using an unbiased sampling method called the physical disector. Our counts indicate that, in the fixed cat brain, there are 5.9 x 10(8) +/- 0.9 x 10(8) asymmetric synapses per cubic millimeter of layer 4 in area 17, and the dLGN input provides only 6% of all asymmetric synapses in layer 4. The vast majority of synapses of layer 4 probably originate from other neurons in area 17.

Molecular genetics and imaging technologies for circuit-based neuroanatomy

Brain function emerges from the morphologies, spatial organization and patterns of connectivity established between diverse sets of neurons. Historically, the notion that neuronal structure predicts function stemmed from classic histological staining and neuronal tracing methods. Recent advances in molecular genetics and imaging technologies have begun to reveal previously unattainable details about patterns of functional circuit connectivity and the subcellular organization of synapses in the living brain. This sophisticated molecular and genetic 'toolbox', coupled with new methods in optical and electron microscopy, provides an expanding array of techniques for probing neural anatomy and function.

Receptive Field Self-Organization in a Model of the Fine Structure in V1 Cortical Columns

We study a dynamical model of processing and learning in the visual cortex, which reflects the anatomy of V1 cortical columns and properties of their neuronal receptive fields. Based on recent results on the fine-scale structure of columns in V1, we model the activity dynamics in subpopulations of excitatory neurons and their interaction with systems of inhibitory neurons. We find that a dynamical model based on these aspects of columnar anatomy can give rise to specific types of computations that result in self-organization of afferents to the column. For a given type of input, self-organization reliably extracts the basic input components represented by neuronal receptive fields. Self-organization is very noise tolerant and can robustly be applied to different types of input. To quantitatively analyze the system's component extraction capabilities, we use two standard benchmarks: the bars test and natural images. In the bars test, the system shows the highest noise robustness reported so far. If natural image patches are used as input, self-organization results in Gabor-like receptive fields. In quantitative comparison with in vivo measurements, we find that the obtained receptive fields capture statistical properties of V1 simple cells that algorithms such as independent component analysis or sparse coding do not reproduce.

The W cell pathway to cat primary visual cortex

The thalamic input to area 17 in the cat can be divided into at least three parallel pathways, the W, X, and Y. Although the latter two are some of the best studied synaptic connections in the brain, the former remains poorly understood both in structure and in function. By combining light and electron microscopy, we have reconstructed in 3-D single W axons and described quantitatively the synapses that they form. We have also made a structural comparison of reconstructed synapses from the three visual pathways. Thalamic axons were labeled in vivo by injections of biotinylated dextran amine into the dLGN. W axons originating from C laminae injections arborized in layers 1, 2/3, and 5. Axons that traversed layer 1 supplied a few descending collaterals to layer 2/3, but the most extensive innervation in layer 2/3 was provided by axons ascending from the white matter. Most W boutons formed a single synapse, dendritic spines being the most common target, with dendritic shafts forming the remaining targets. In layer 1, the area of the postsynaptic density of spine synapses (0.16 microm(2)) was significantly larger than that of layers 2/3 (0.11 microm(2)) and 5 (0.09 microm(2)). Synapses from X and Y axons in layer 4 were similar in size to synapses formed by W boutons in layer 1. In layer 1, the main targets of the W axons are likely the apical dendrites of pyramidal cells, so that both proximal and distal regions of pyramidal cell dendritic trees can be excited by the W pathway.

Spikes, synchrony, and attentive learning by laminar thalamocortical circuits

This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single-cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current source densities and local field potentials; and single-cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, learning, and consciousness. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

Lack of orientation and direction selectivity in a subgroup of fast-spiking inhibitory interneurons: cellular and synaptic mechanisms and comparison with other electrophysiological cell types

Neurons in cat area 17 can be grouped in 4 different electrophysiological cell classes (regular spiking, intrinsically bursting, chattering, and fast spiking [FS]). However, little is known of the functional properties of these different cell classes. Here we compared orientation and direction selectivity between these cell classes in cat area 17 and found that a subset of FS inhibitory neurons, usually with complex receptive fields, exhibited little selectivity in comparison with other cell types. Differences in occurrence and amplitude of gamma-range membrane fluctuations, as well as in numbers of action potentials in response to optimal visual stimuli, did not parallel differences observed for orientation and direction selectivity. Instead, differences in selectivity resulted mostly from differences in tuning of the membrane potential responses, although variations in spike threshold also contributed: weakly selective FS neurons exhibited both a lower spike threshold and more broadly tuned membrane potential responses in comparison with the other cell classes. Our results are consistent with the hypothesis that a subgroup of FS neurons receives connections and possesses intrinsic properties allowing the generation of weakly selective responses. The existence of weakly selective inhibitory neurons is consistent with orientation selectivity models that rely on broadly tuned inhibition.

The thalamus is more than just a relay

The lateral geniculate nucleus and pulvinar are examples of two different types of relay: the former is a first order relay, transmitting information from a subcortical source (retina), while the latter is mostly a higher order relay, transmitting information from layer 5 of one cortical area to another cortical area. First and higher order thalamic relays can also be recognized for much of the rest of thalamus, and most of thalamus seems to be comprised of higher order relays. Higher order relays seem especially important to general corticocortical communication, and this challenges and extends the conventional view that such communication is based on direct corticocortical connections.

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.

Synaptic basis for intense thalamocortical activation of feedforward inhibitory cells in neocortex

The thalamus provides fundamental input to the neocortex. This input activates inhibitory interneurons more strongly than excitatory neurons, triggering powerful feedforward inhibition. We studied the mechanisms of this selective neuronal activation using a mouse somatosensory thalamocortical preparation. Notably, the greater responsiveness of inhibitory interneurons was not caused by their distinctive intrinsic properties but was instead produced by synaptic mechanisms. Axons from the thalamus made stronger and more frequent excitatory connections onto inhibitory interneurons than onto excitatory cells. Furthermore, circuit dynamics allowed feedforward inhibition to suppress responses in excitatory cells more effectively than in interneurons. Thalamocortical excitatory currents rose quickly in interneurons, allowing them to fire action potentials before significant feedforward inhibition emerged. In contrast, thalamocortical excitatory currents rose slowly in excitatory cells, overlapping with feedforward inhibitory currents that suppress action potentials. These results demonstrate the importance of selective synaptic targeting and precise timing in the initial stages of neocortical processing.

Synaptic connection from cortical area V4 to V2 in macaque monkey

The major target of the V4 projection in V2 is layer 1, where it forms a tangential spread of asymmetric (excitatory) synapses. This is characteristic of a "feedback" projection. Some axons formed discrete clusters of bouton terminaux between lengths of myelinated axon, while others were unbranched and formed a continuous distribution of en passant boutons with no intercalated myelin. Minor projections were found in layers 2/3 and 6. Dendritic spines were the most frequently encountered targets of the V4 projection (80% in layer 1 and layer 2/3, 94% in layer 6). The remaining targets were dendritic shafts. In layer 1, 69% of target dendrites (12% of all targets) had characteristics identifying them as smooth (GABAergic) cells. In layer 2/3 and layer 6 virtually all the shaft synapses were on smooth dendrites (86% and 100%, respectively). Multisynaptic boutons were rare (mean 1.1 synapses per bouton). Synapses formed in layer 6 were smaller than those of layer 1 (mean area 0.073 microm(2) vs. 0.117 microm(2)). Synapses formed with spines had a more complex postsynaptic density than those formed with dendritic shafts. With respect to targets and synaptic type and size and morphology of synapses, the feedback projection from V4 to V2 resembles those of feedforward projections. The principal difference between the feedforward and feedback projection is in the lamina location of their terminal boutons. The concentration of the V4 projection on layer 1, where it forms asymmetric synapses mainly with spines, suggests that it excites the distal apical dendrites of pyramidal cells.

Glutathione deficit during development induces anomalies in the rat anterior cingulate GABAergic neurons: Relevance to schizophrenia

A series of studies in schizophrenic patients report a decrease of glutathione (GSH) in prefrontal cortex (PFC) and cerebrospinal fluid, a decrease in mRNA levels for two GSH synthesizing enzymes and a deficit in parvalbumin (PV) expression in a subclass of GABA neurons in PFC. GSH is an important redox regulator, and its deficit could be responsible for cortical anomalies, particularly in regions rich in dopamine innervation. We tested in an animal model if redox imbalance (GSH deficit and excess extracellular dopamine) during postnatal development would affect PV-expressing neurons. Three populations of interneurons immunolabeled for calcium-binding proteins were analyzed quantitatively in 16-day-old rat brain sections. Treated rats showed specific reduction in parvalbumin immunoreactivity in the anterior cingulate cortex, but not for calbindin and calretinin. These results provide experimental evidence for the critical role of redox regulation in cortical development and validate this animal model used in schizophrenia research.

Should I stay or should I go? Presynaptic boutons in the adult cortex still haven't made up their minds

Previous studies demonstrating turnover of the dendritic spines of cortical neurons have suggested a modest rate of turnover of synaptic connections. Now, two papers in this issue of Neuron address this question from the other side of the synapse, the presynaptic boutons. Both studies use in vivo multiphoton imaging of cortical axons to show that synaptic boutons come and go, just like spines. One of the studies shows remarkable diversity in the lability of boutons depending on the cell type from which they originate, with some boutons displaying nearly complete turnover in just a few months. The other study shows that bouton turnover occurs in primates as well as rodents.

Axons and synaptic boutons are highly dynamic in adult visual cortex

While recent studies of synaptic stability in adult cerebral cortex have focused on dendrites, how much axons change is unknown. We have used advances in axon labeling by viruses and in vivo two-photon microscopy to investigate axon branching and bouton dynamics in primary visual cortex (V1) of adult Macaque monkeys. A nonreplicative adeno-associated virus bearing the gene for enhanced green fluorescent protein (AAV.EGFP) provided persistent labeling of axons, and a custom-designed two-photon microscope enabled repeated imaging of the intact brain over several weeks. We found that large-scale branching patterns were stable but that a subset of small branches associated with terminaux boutons, as well as a subset of en passant boutons, appeared and disappeared every week. Bouton losses and gains were both approximately 7% of the total population per week, with no net change in the overall density. These results suggest ongoing processes of synaptogenesis and elimination in adult V1.

Inter- and intra-laminar connections of pyramidal cells in the neocortex

The flow of excitation through cortical columns has long since been predicted by studying the axonal projection patterns of excitatory neurones situated within different laminae. In grossly simplified terms and assuming random connectivity, such studies predict that input from the thalamus terminates primarily in layer 4, is relayed 'forward' to layer 3, then to layers 5 and 6 from where the modified signal may exit the cortex. Projection patterns also indicate 'back' projections from layer 5 to 3 and layer 6 to 4. More recently it has become clear that the interconnections between these layers are not random; forward projections primarily contact specific pyramidal subclasses and intracortical back projections innervate interneurones. This indicates that presynaptic axons or postsynaptic dendrites are capable of selecting their synaptic partners and that this selectivity is layer dependent. For the past decade, we and others have studied pyramidal cell targeting in circuits both within, and between laminae using paired intracellular recordings with biocytin filling and have begun to identify further levels of selectivity through the preferential targeting of electrophysiologically and/or morphologically distinct pyramidal subtypes. Presented here, therefore, is a brief overview of current thinking on the layer and subclass specific connectivity of neocortical principle excitatory cells.

Connection from cortical area V2 to V3 A in macaque monkey

The V2 projection to V3 A was labeled by pressure microinjecting biotinylated dextran amine (BDA) and Phaseolus vulgaris lectin (PHA-L) into V2 just posterior to the lunate sulcus. Dense terminal labeling in clusters was found in layer 4, with a weaker terminal projection in layer 3. About 3.5--4.1% of the synapses in the densest bouton clusters in layer 4 were made by labeled boutons. All were asymmetric (Gray's type 1) synapses, made by spiny, excitatory neurons. The most frequently encountered synaptic targets were spines (76% in layer 4, 98% in layer 2/3). The remainder of the synaptic targets were dendritic shafts, of which just less than half (44%) had the characteristic ultrastructure of smooth (inhibitory) cells. Multisynaptic boutons were rare (mean synapses per bouton for layer 4 1.2, for layer 2/3 1.1). The mean size of the postsynaptic densities found on spines (0.11 microm(2)) was not significantly different from that for dendrites (0.09 microm(2)). In terms of their type, laminar location, number, and targets, the synapses that formed the V2 projection to V3 A are typical of a major, excitatory, feedforward projection of macaque visual cortex.

Synaptic distinction of laminar-specific prefrontal-temporal pathways in primates

Prefrontal pathways exert diverse effects in widespread cortical areas, issuing projections both to the middle layers and to layer I, which are anatomically and functionally distinct. Here we addressed the still unanswered question of whether cortical pathways that terminate in different layers are distinct at the synaptic level. We addressed this issue using as a model system the robust and functionally significant pathways from prefrontal areas 10 and 32 to superior temporal areas in rhesus monkeys. Boutons from prefrontal axons synapsing in the middle layers of superior temporal cortex were significantly larger than boutons synapsing in layer I. Most synapses were on spines in both layers, which are found on dendrites of excitatory neurons. The less prevalent synapses on smooth dendrites, characteristic of inhibitory interneurons, were more common in the middle cortical layers than in layer I. Bouton volume was linearly related to vesicular and mitochondrial content in both layers, though a subset of small boutons, found mostly in layer I, contained no mitochondria. The systematic laminar-specific presynaptic differences in stable cortical synapses in adult primates were independent of their origin in the functionally distinct prefrontal areas 10 and 32, or their destination in architectonically distinct superior temporal areas. This synaptic distinction suggests differences in efficacy of synaptic transmission and metabolic demands in laminar-specific pathways that may be selectively recruited in behavior.

Properties of excitatory synaptic responses in fast-spiking interneurons and pyramidal cells from monkey and rat prefrontal cortex

In the prefrontal cortex (PFC) during working memory tasks fast-spiking (FS) interneurons might shape the spatial selectivity of pyramidal cell firing. In order to provide time control of pyramidal cell activity, incoming excitatory inputs should excite FS interneurons more vigorously than pyramidal cells. This can be achieved if subthreshold excitatory responses of interneurons are considerably stronger and faster than those in pyramidal neurons. Here we compared the functional properties of excitatory post-synaptic potentials (EPSPs) between pyramidal cells and FS interneurons in slices from monkey dorsolateral PFC and rat prelimbic cortex. Miniature, unitary (in connected pairs or by minimal stimulation) and compound (evoked by electrical stimulation of the white matter) EPSPs were recorded in whole cell mode. We found that EPSPs were significantly larger and faster in FS interneurons than those recorded from pyramidal cells, consistent with the idea of more efficient recruitment of FS interneurons compared to pyramidal neurons. Similar results were obtained in monkey and rat PFC, suggesting a stable role of FS interneurons in this circuitry across species.

Laminar cortical dynamics of 3D surface perception: stratification, transparency, and neon color spreading

The 3D LAMINART neural model is developed to explain how the visual cortex gives rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes. Such percepts are sensitive to whether contiguous image regions have the same contrast polarity and ocularity. The model predicts how like-polarity competition at V1 simple cells in layer 4 may cause these percepts when it interacts with other boundary and surface processes in V1, V2, and V4. The model also explains how: the Metelli Rules cause transparent percepts, bistable transparency percepts arise, and attention influences transparency reversal.