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.

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.

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.

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.

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.

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.

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.

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.

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).

Mapping the matrix: the ways of neocortex.

While we know that the neocortex occupies 85% of our brains and that its circuits allow an enormous flexibility and repertoire of behavior (not to mention unexplained phenomena like consciousness), a century after Cajal we have very little knowledge of the details of the cortical circuits or their mode of function. One simplifying hypothesis that has existed since Cajal is that the neocortex consists of repeated copies of the same fundamental circuit. However, finding that fundamental circuit has proved elusive, although partial drafts of a "canonical circuit" appear in many different guises of structure and function. Here, we review some critical stages in the history of this quest. In doing so, we consider the style of cortical computation in relation to the neuronal machinery that supports it. We conclude that the structure and function of cortex honors two major computational principles: "just-enough" and "just-in-time."

The synaptic organization of the claustral projection to the cat's visual cortex.

The claustrum is a subcortical structure reciprocally connected with most areas of neocortex. This strategic location suggests an integrative role of the claustrum across different sensory modalities. However, our knowledge of the synaptic relationship between the neocortex and the claustrum is basic. In this study, we address this question through a structural investigation of the claustral projection to the ipsilateral primary visual cortex of the cat. Light microscopic reconstructions of axons from the entire thickness of cortex showed a very sparse innervation of the entire cortical depth, with most synaptic boutons in layers 2/3 and 6. Axons bearing numerous boutons terminaux and boutons en passant branched in these laminae. The sparse innervation did not seem to be compensated by particularly large synapses, given that the postsynaptic densities in the superficial layers are of comparable sizes (0.1 µm(2)) to other cortical synapses. All claustral synapses were asymmetric and in most cases targeted spines (87% in layer 4, 94% in layers 2/3 and 97% in layer 6). The pattern of innervation together with the known physiology of this projection suggests that the claustrum has a modulatory effect on visual cortex.

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.

Selective targeting of the dendrites of corticothalamic cells by thalamic afferents in area 17 of the cat.

Pyramidal cells of layer 6 in cat visual cortex are the source of the corticothalamic projection, and their recurrent collaterals provide substantially more excitatory synapses in layer 4 than does the thalamic input. They have predominantly simple receptive fields and can be driven monosynaptically by electrically stimulating thalamic relay cells. Layer 6 cells could thus provide a significant disynaptic amplification of the thalamic input to layer 4, particularly since their synapses facilitate, unlike the thalamic afferents whose synapses depress. However, purely geometric considerations of the relation of their dendritic trees to the thalamic input indicate that they should form a far smaller number of synapses with thalamic afferents than do the simple cells of layer 4. We thus analyzed quantitatively the thalamic input to identified corticothalamic cells by labeling the thalamic afferents and corticothalamic cells in vivo. We made a correlated light and electron microscopic study of 73 "contacts" between thalamic afferents and five corticothalamic cells. The electron microscope revealed that only 24 of the contacts identified at light microscope level were indeed synapses and, contrary to geometric predictions, virtually all were located on spines on the basal dendrites. Our quantitative estimates indicate that the corticothalamic cells form even fewer synapses with the thalamic afferents than predicted by geometric considerations and only 1/10 as many as do the layer 4 simple cells. These data strongly suggest it is the collective computation of cortical neurons, not the monosynaptic thalamic input, that determines the output of the corticothalamic cells.

The synaptic connections between cortical areas V1 and V2 in macaque monkey.

The primary visual cortex (V1) and V2 together form approximately 24% of the total neocortex of the macaque monkey and have each other as their major partners. The major target of the V1 projection to V2 is layer 4, where it forms clusters of boutons, which form asymmetric (excitatory) synapses mainly with dendritic spines (75%). The remainder form synapses with dendritic shafts. The synapses found on spines were often more complex, perforated postsynaptic densities than those found on dendritic shafts. The reciprocal projection from V2 to V1 targeted layers 1, 2/3, and 5 and was formed of axons of different morphologies. One axon type, originating from superficial layer pyramidal cells, had a morphology resembling those of local pyramidal cell collaterals. These axons arborized in layers 1, 2/3, and 5 of V1. Another type of axon, arborizing in layer 1, was slender (0.3 microm), unbranched, unmyelinated, and uniformly covered with boutons terminaux and formed asymmetric synapses mainly with slender spines. Yet a third type of axon also confined to layer 1, was thick (>1 microm), branched, heavily myelinated, and formed separate small clusters of large ( approximately 1 microm) en passant multisynaptic boutons that formed asymmetric synapses mainly with large flat spines. These data show the existence of a reciprocal excitatory loop between V1 and V2 that is formed by different axonal types, each with preferred layers of termination.

High-amplitude positive spikes recorded extracellularly in cat visual cortex.

We simulated the shape and amplitude of extracellular action potentials (APs or "spikes") using biophysical models based on detailed reconstructions of single neurons from the cat's visual cortex. We compared these predictions with spikes recorded from the cat's primary visual cortex under a standard protocol. The experimental data were derived from a large number of neurons throughout all layers. The majority of spikes were biphasic, with a dominant negative peak (mean amplitude, -0.11 mV), whereas a minority of APs had a dominant positive peak of +0.54-mV mean amplitude, with a maximum of +1.5 mV. The largest positive amplitude spikes were recorded in layer 5. The simulations demonstrated that a pyramidal neuron under known biophysical conditions may generate a negative peak with amplitude up to -1.5 mV, but that the amplitude of the positive peak may be at most 0.5 mV. We confirmed that spikes with large positive peaks were not produced by juxtacellular patch recordings. We conclude that there is a significant gap in our present understanding of either the spike-generation process in pyramidal neurons, the biophysics of extracellular recording, or both.

Inactivation of lateral connections in cat area 17.

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