A strong direct link from the layer 3/4 border to layer 6 of cat primary visual cortex.

The cat primary visual cortex (V1) is a cortical area for which we have one of the most detailed estimates of the connection 'weights' (expressed as number of synapses) between different neural populations in different layers (Binzegger et al in J Neurosci 24:8441-8453, 2004). Nevertheless, the majority of excitatory input sources to layer 6, the deepest layer in a local translaminar excitatory feedforward loop, was not accounted for by the known neuron types used to generate the quantitative Binzegger diagram. We aimed to fill this gap by using a retrograde tracer that would label neural cell bodies in and outside V1 that directly connect to layer 6 of V1. We found that more than 80% of labeled neurons projecting to layer 6 were within V1 itself. Our data indicate that a substantial fraction of the missing input is provided by a previously unidentified population of layer 3/4 border neurons, laterally distributed and connecting more strongly to layer 6 than the typical superficial layer pyramidal neurons considered by Binzegger et al. (Binzegger et al in J Neurosci 24:8441-8453, 2004). This layer 3/4 to layer 6 connection may be a parallel route to the layer 3 - layer 5 - layer 6 feedforward pathway, be associated with the fast-conducting, movement-related Y pathway and provide convergent input from distant (5-10 degrees) regions of the visual field.

Allometry: Alice in Pinwheel Land.

Brain size scales with body weight, but a new study has discovered that key circuits in the visual cortex of one of the world's smallest primates, the mouse lemur, Microcebus murinus, are built at the same scale as their equivalents in larger-brained primates.

Structure and function of a neocortical synapse.

In 1986, electron microscopy was used to reconstruct by hand the entire nervous system of a roundworm, the nematode Caenorhabditis elegans1. Since this landmark study, high-throughput electron-microscopic techniques have enabled reconstructions of much larger mammalian brain circuits at synaptic resolution2,3. Nevertheless, it remains unknown how the structure of a synapse relates to its physiological transmission strength-a key limitation for inferring brain function from neuronal wiring diagrams. Here we combine slice electrophysiology of synaptically connected pyramidal neurons in the mouse somatosensory cortex with correlated light microscopy and high-resolution electron microscopy of all putative synaptic contacts between the recorded neurons. We find a linear relationship between synapse size and strength, providing the missing link in assigning physiological weights to synapses reconstructed from electron microscopy. Quantal analysis also reveals that synapses contain at least 2.7 neurotransmitter-release sites on average. This challenges existing release models and provides further evidence that neocortical synapses operate with multivesicular release4-6, suggesting that they are more complex computational devices than thought, and therefore expanding the computational power of the canonical cortical microcircuitry.

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.

A biological blueprint for the axons of superficial layer pyramidal cells in cat primary visual cortex.

Pyramidal cells in the superficial layers of neocortex of higher mammals form a lateral network of axon clusters known as the 'daisy' network. The role of these axon clusters remains speculative and we still lack a comprehensive quantitative description of the single neurons forming the daisy or their heterogeneity. We filled intracellularly 50 superficial layer pyramidal neurons in the cat primary visual cortex and reconstructed the axonal tree and their synaptic boutons in 3D. Individual bouton clusters were identified using an objective mean-shift algorithm. By parameterizing the morphology of these 50 axonal trees and the 217 bouton clusters they formed, we were able to extract one set of relatively constant parameters and another set of variable parameters. Both sets combined allowed us to outline a comprehensive biological blueprint of superficial layer pyramidal neurons. Overall, our detailed analysis supports the hypothesis that pyramidal neurons use their lateral clusters to combine differential contextual cues, required for context-dependent processing of natural scenes.

Synaptic connections formed by patchy projections of pyramidal cells in the superficial layers of cat visual cortex.

The present study is the first to describe quantitatively the patterns of synaptic connections made by the patchy network of pyramidal cell axons in the superficial layers of cat V1 in relation to the orientation map. Intrinsic signal imaging of the orientation map was combined with 3D morphological reconstructions of physiologically-characterized neurons at light and electron microscope levels. A Similarity Index (SI) expressed the similarity of the orientation domain of a given bouton cluster to that of its parent dendritic tree. Six pyramidal cells whose axons had a wide range of SIs were examined. Boutons were sampled from five local and five distal clusters, and from the linear segments that link the clusters. The synaptic targets were reconstructed by serial section electron microscopy. Of the 233 synapses examined, 182 synapses were formed with spiny neurons, the remainder with smooth neurons. The proportion of smooth neurons that were synaptic targets varied greatly (from 0 to 50%) between the cluster samples, but was not correlated with the SI. The postsynaptic density sizes were similar for synapses in local and distal clusters, regardless of their SI. This heterogeneity in the synaptic targets of single cells within the superficial layers is a network feature well-suited for context-dependent processing.

An Ultrastructural Study of the Thalamic Input to Layer 4 of Primary Motor and Primary Somatosensory Cortex in the Mouse.

The traditional classification of primary motor cortex (M1) as an agranular area has been challenged recently when a functional layer 4 (L4) was reported in M1. L4 is the principal target for thalamic input in sensory areas, which raises the question of how thalamocortical synapses formed in M1 in the mouse compare with those in neighboring sensory cortex (S1). We identified thalamic boutons by their immunoreactivity for the vesicular glutamate transporter 2 (VGluT2) and performed unbiased disector counts from electron micrographs. We discovered that the thalamus contributed proportionately only half as many synapses to the local circuitry of L4 in M1 compared with S1. Furthermore, thalamic boutons in M1 targeted spiny dendrites exclusively, whereas ∼9% of synapses were formed with dendrites of smooth neurons in S1. VGluT2+ boutons in M1 were smaller and formed fewer synapses per bouton on average (1.3 vs 2.1) than those in S1, but VGluT2+ synapses in M1 were larger than in S1 (median postsynaptic density areas of 0.064 µm2 vs 0.042 µm2). In M1 and S1, thalamic synapses formed only a small fraction (12.1% and 17.2%, respectively) of all of the asymmetric synapses in L4. The functional role of the thalamic input to L4 in M1 has largely been neglected, but our data suggest that, as in S1, the thalamic input is amplified by the recurrent excitatory connections of the L4 circuits. The lack of direct thalamic input to inhibitory neurons in M1 may indicate temporal differences in the inhibitory gating in L4 of M1 versus S1.SIGNIFICANCE STATEMENT Classical interpretations of the function of primary motor cortex (M1) emphasize its lack of the granular layer 4 (L4) typical of sensory cortices. However, we show here that, like sensory cortex (S1), mouse M1 also has the canonical circuit motif of a core thalamic input to the middle cortical layer and that thalamocortical synapses form a small fraction (M1: 12%; S1: 17%) of all asymmetric synapses in L4 of both areas. Amplification of thalamic input by recurrent local circuits is thus likely to be a significant mechanism in both areas. Unlike M1, where thalamocortical boutons typically form a single synapse, thalamocortical boutons in S1 usually formed multiple synapses, which means they can be identified with high probability in the electron microscope without specific labeling.

Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.

The local field potential (LFP) is thought to reflect a temporal reference for neuronal spiking, which may facilitate information coding and orchestrate the communication between neural populations. To explore this proposed role, we recorded the LFP and simultaneously the spike activity of one to three nearby neurons in V1 of anesthetized cats during the presentation of drifting sinusoidal gratings, binary dense noise stimuli, and natural movies. In all stimulus conditions and during spontaneous activity, the average LFP power at frequencies >20 Hz was higher when neurons were spiking versus not spiking. The spikes were weakly but significantly phase locked to all frequencies of the LFP. The average spike phase of the LFP was stable across high and low levels of LFP power, but the strength of phase locking at low frequencies (≤10 Hz) increased with increasing LFP power. In a next step, we studied how strong stimulus responses of single neurons are reflected in the LFP and the LFP-spike relationship. We found that LFP power was slightly increased and phase locking was slightly stronger during strong compared with weak stimulus-locked responses. In summary, the coupling strength between high frequencies of the LFP and spikes was not strongly modulated by LFP power, which is thought to reflect spiking synchrony, nor was it strongly influenced by how strongly the neuron was driven by the stimulus. Furthermore, a comparison between neighboring neurons showed no clustering of preferred LFP phase. We argue that hypotheses on the relevance of phase locking in their current form are inconsistent with our findings.

Local Circuits for Contrast Normalization and Adaptation Investigated with Two-Photon Imaging in Cat Primary Visual Cortex.

Sensory neurons encode stimulus intensity in their instantaneous spike rate and adjust the set-points of the stimulus-response relationships by adaptation. In the visual cortex, adaptation is crucial because the mechanism of fast gain control (normalization) increases the contrast sensitivity of individual neurons at the cost of encoding a far narrower range of contrasts than is encountered in natural scenes. The mechanism of adaptation, however, is a slow process and has a time constant of seconds. Here we use two-photon calcium imaging of identified excitatory and inhibitory neurons in superficial layers of cat primary visual cortex to answer two questions: for a given set-point, what is range of contrasts represented within a local pool of neurons, and what accounts for the slow time constant of contrast adaptation? We found that a local patch of excitatory neurons has a large diversity of contrast tunings, which effectively extends the range of contrast that can be encoded instantaneously in cortex. Additionally, we identified a pool of parvalbumin-positive GABAergic neurons and neurons in the upper tier of imaging sites that showed a paradoxical slow increase in activity during adaptation, thus implicating them in the slow set-point adaptation of the excitatory population. Our results provide new insights into the circuits and mechanisms underlying cortical adaptation and gain control. SIGNIFICANCE STATEMENT: Neurons in the primary visual cortex (V1) respond near instantaneously over a limited range of contrasts but can also shift their operating range according to the average contrast of the scene. This "contrast adaptation" takes 5-10 s and ensures that a full range of contrasts can be encoded in V1, while remaining sensitive to small changes in local contrast. By optically recording many layer 2 neurons simultaneously, we discovered that networks of neurons collectively code for a much wider range of contrasts. Whereas most neurons responded to sustained increases in contrast by decreasing their spike firing rates, two types of inhibitory neurons in the cat's visual cortex paradoxically increased their firing rates and so could inhibit other neurons to produce contrast adaptation.

Superficial layer pyramidal cells communicate heterogeneously between multiple functional domains of cat primary visual cortex.

The axons of pyramidal neurons in the superficial layers of the neocortex of higher mammals form lateral networks of discrete clusters of synaptic boutons. In primary visual cortex the clusters are reported to link domains that share the same orientation preferences, but how individual neurons contribute to this network is unknown. Here we performed optical imaging to record the intrinsic signal, which is an indirect measure of neuronal firing, and determined the global map of orientation preferences in the cat primary visual system. In the same experiment, single cells were recorded and labelled intracellularly. We found that individual axons arborise within the retinotopic representation of the classical receptive field, but their bouton clusters were not aligned along their preferred axis of orientation along the retinotopic map. Axon clusters formed in a variety of different orientation domains, not just the like-orientation domains. This topography and heterogeneity of single-cell connectivity provides circuits for normalization and context-dependent feature processing of visual scenes.

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

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.

Functional heterogeneity in neighboring neurons of cat primary visual cortex in response to both artificial and natural stimuli.

Neurons in primary visual cortex of many mammals are clustered according to their preference to stimulus parameters such as orientation and spatial frequency. Nevertheless, responses to complex visual stimuli are highly heterogeneous between adjacent neurons. To investigate the relation between these observations, we recorded from pairs of neighboring neurons in area 17 of anesthetized cats in response to stimuli of differing complexity: sinusoidal drifting gratings, binary dense noise, and natural movies. Comparisons of the tuning curves revealed similar orientation and direction preferences for neighboring neurons, but large differences in preferred phase, direction selectivity, and tuning width of spatial frequency. No pair was similar across all tuning properties. The neurons' firing rates averaged across multiple stimulus repetitions (the "signal") were also compared. Binned between 10 and 200 ms, the correlation between these signals was close to zero in the median across all pairs for all stimulus classes. Signal correlations agreed poorly with differences in tuning properties, except for receptive field offset and relative modulation (i.e., the strength of phase modulation). Nonetheless, signal correlations for different stimulus classes were well correlated with each other, even for gratings and movies. Conversely, trial-to-trial fluctuations (termed "noise") were poorly correlated between neighboring neurons, suggesting low degrees of common input. In response to gratings and visual noise, signal and noise correlations were well correlated with each other, but less so for responses to movies. These findings have relevance for our understanding of the processing of natural stimuli in a functionally heterogeneous cortical network.

Sparse reconstruction of brain circuits: or, how to survive without a microscopic connectome.

Inside one voxel of a cubic millimeter of neocortex, fifty to hundred thousand neurons use 4 km of axonal cable to form three to fifteen hundred million synapses with each other. While in the human, such voxel is a small fragment of a cortical area, in the mouse an entire cortical area, like the primary auditory cortex, can be contained in a voxel of this size. This raises the fundamental question of what happens inside such a voxel? Are the circuits contained in this voxel, and their operations, different in every area, or are there general principles that are conserved across cortical areas and species? Such questions go to the heart of understanding how the neocortex wires itself and works. One proposal is to answer these questions by mapping the entire circuit at synaptic resolution to produce a 'connectome' - of the cortical column, or even of the entire brain. However, such a high-resolution connectome is self-evidently unachievable with the tools available and as a strategy it still leaves us short of understanding the 'principles of neural engineering'. We offer an alternative route that uses physiology and computational modeling as a means of generating 'predictive anatomy', where the questions about underlying structure are directed to fundamental principles of organization and operation of the cortical circuits. This approach involves 'sparse' rather than 'dense' reconstructions at light and electron microscope resolution to keep the questions well-matched to current experimental tools. Rather than providing a snap-shot of an entire wiring diagram, our strategy provides for a statistical description of the circuit and integrates theory, function, and structure in a common framework.

The fine structure of the dopaminergic innervation of area 10 of macaque prefrontal cortex.

In common with other areas of the prefrontal cortex, activity in frontopolar area 10 is probably modulated by dopamine. We studied the dopaminergic innervation of monkey prefrontal area 10 by immunostaining with tyrosine hydroxylase (TH) antibodies. TH-positive axons in layer 3 were examined by electron microscopy of series of ultrathin sections. TH-positive boutons containing vesicles were sparse (2 × 10(-4) per µm(3)) and the majority (94%, n = 52) had no identifiable synaptic specialization, which supports the hypothesis that dopamine is released non-synaptically and raises the question of whether the local microenvironment surrounding the boutons is special. Compared with unlabelled boutons TH-positive boutons had a higher proportion of their perimeter in contact with dendritic shafts and were more often in continuous contact with pairs of pre- and postsynaptic structures. However, this may result from exclusion from sites preferred by glutamatergic and GABAergic synapses as the density of all synapses in the closer vicinity was no different from any randomly selected site in the neuropil. This quantitative ultrastructural study presents basic features of the dopaminergic innervation in prefrontal area 10 and provides a more detailed understanding of the structural basis of dopamine signalling in the cortex.

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.

Pathways of attention: synaptic relationships of frontal eye field to V4, lateral intraparietal cortex, and area 46 in macaque monkey.

The frontal eye field (FEF) of the primate neocortex occupies a pivotal position in the matrix of inter-areal projections. In addition to its role in directing saccadic eye movements, it is the source of an attentional signal that modulates the activity of neurons in extrastriate and parietal cortex. Here, we tested the prediction that FEF preferentially excites inhibitory neurons in target areas during attentional modulation. Using the anterograde tracer biotinylated dextran amine, we found that the projections from FEF terminate in all cortical layers of area 46, lateral intraparietal area (LIP), and visual area V4. Axons in layer 1 spread extensively, those in layer 2/3 were most numerous, individual axons in layer 4 formed sprays of collaterals, and those of the deep layers were the finest caliber and irregular. All labeled synapses were the typical asymmetric morphology of excitatory synapses of pyramidal neurons. Dendritic spines were the most frequent synaptic target in all areas (95% in area 46, 89% in V4, 84% in LIP, 78% intrinsic local FEF). The remaining targets were one soma and dendritic shafts, most of which showed characteristics of inhibitory neurons with smooth dendrites (5% of all targets in area 46, 2% in V4, 9% in LIP, and 13% in FEF).

Neuroanatomy: uninhibited connectivity in neocortex?

The mouse neocortex is now the focus of research using twenty-first century techniques of circuit analyses, which are revealing different wiring strategies for excitatory and inhibitory connections and providing important insights into the possible computations of cortical circuits.

How thalamus connects to spiny stellate cells in the cat's visual cortex.

In the cat's visual cortex, the responses of simple cells seem to be totally determined by their thalamic input, yet only a few percent of the excitatory synapses in layer 4 arise from the thalamus. To resolve this discrepancy between structure and function, we used correlated light and electron microscopy to search individual spiny stellate cells (simple cells) for possible structural features that would explain the biophysical efficacy of the thalamic input, such as synaptic location on dendrites, size of postsynaptic densities, and postsynaptic targets. We find that thalamic axons form a small number of synapses with the spiny stellates (188 on average), that the median size of the synapses is slightly larger than that of other synapses on the dendrites of spiny stellates, that they are not located particularly proximal to the soma, and that they do not cluster on the dendrites. These findings point to alternative mechanisms, such as synchronous activation of the sparse thalamic synapses to boost the efficacy of the thalamic input. The results also support the idea that the thalamic input does not by itself determine the cortical response of spiny stellate cells, allowing the cortical microcircuit to amplify and modulate its response according to the particular context and computation being performed.