Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Spike timing-dependent plasticity as the origin of the formation of clustered synaptic efficacy engrams

Synapse location, dendritic active properties and synaptic plasticity are all known to play some role in shaping the different input streams impinging onto a neuron. It remains unclear however, how the magnitude and spatial distribution of synaptic efficacies emerge from this interplay. Here, we investigate this interplay using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and spike timing-dependent plasticity (STDP). Specifically, we focus on the issue of how the efficacy of synapses contributed by different input streams are spatially represented in dendrites after STDP learning. We construct a simple feed forward network where a detailed model neuron receives synaptic inputs independently from multiple yet equally sized groups of afferent fibers with correlated activity, mimicking the spike activity from different neuronal populations encoding, for example, different sensory modalities. Interestingly, ensuing STDP learning, we observe that for all afferent groups, STDP leads to synaptic efficacies arranged into spatially segregated clusters effectively partitioning the dendritic tree. These segregated clusters possess a characteristic global organization in space, where they form a tessellation in which each group dominates mutually exclusive regions of the dendrite. Put simply, the dendritic imprint from different input streams left after STDP learning effectively forms what we term a “dendritic efficacy mosaic.” Furthermore, we show how variations of the inputs and STDP rule affect such an organization. Our model suggests that STDP may be an important mechanism for creating a clustered plasticity engram, which shapes how different input streams are spatially represented in dendrite.

Quantal analysis reveals a functional correlation between presynaptic and postsynaptic efficacy in excitatory connections from rat neocortex

At many central synapses, the presynaptic bouton and postsynaptic density are structurally correlated. However, it is unknown whether this correlation extends to the functional properties of the synapses. To investigate this, we made recordings from synaptically coupled pairs of pyramidal neurons in rat visual cortex. The mean peak amplitude of EPSPs recorded from pairs of L2/3 neurons ranged between 40 microV and 2.9 mV. EPSP rise times were consistent with the majority of the synapses being located on basal dendrites; this was confirmed by full anatomical reconstructions of a subset of connected pairs. Over a third of the connections could be described using a quantal model that assumed simple binomial statistics. Release probability (P(r)) and quantal size (Q), as measured at the somatic recording site, showed considerable heterogeneity between connections. However, across the population of connections, values of P(r) and Q for individual connections were positively correlated with one another. This correlation also held for inputs to layer 5 pyramidal neurons from both layer 2/3 and neighboring layer 5 pyramidal neurons, suggesting that during development of cortical connections presynaptic and postsynaptic strengths are dependently scaled. For 2/3 to 2/3 connections, mean EPSP amplitude was correlated with both Q and P(r) values but uncorrelated with N, the number of functional release sites mediating the connection. The efficacy of a cortical connection is thus set by coordinated presynaptic and postsynaptic strength.

Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex

It is well known that neural activity exhibits variability, in the sense that identical sensory stimuli produce different responses, but it has been difficult to determine what this variability means. Is it noise, or does it carry important information-about, for example, the internal state of the organism? Here we address this issue from the bottom up, by asking whether small perturbations to activity in cortical networks are amplified. Based on in vivo whole-cell patch-clamp recordings in rat barrel cortex, we find that a perturbation consisting of a single extra spike in one neuron produces approximately 28 additional spikes in its postsynaptic targets. We also show, using simultaneous intra- and extracellular recordings, that a single spike in a neuron produces a detectable increase in firing rate in the local network. Theoretical analysis indicates that this amplification leads to intrinsic, stimulus-independent variations in membrane potential of the order of +/-2.2-4.5 mV-variations that are pure noise, and so carry no information at all. Therefore, for the brain to perform reliable computations, it must either use a rate code, or generate very large, fast depolarizing events, such as those proposed by the theory of synfire chains. However, in our in vivo recordings, we found that such events were very rare. Our findings are thus consistent with the idea that cortex is likely to use primarily a rate code.

Alterations of cortical pyramidal neurons in mice lacking high-affinity nicotinic receptors

The neuronal nicotinic acetylcholine receptors (nAChRs) are allosteric membrane proteins involved in multiple cognitive processes, including attention, learning, and memory. The most abundant form of heterooligomeric nAChRs in the brain contains the beta2- and alpha4- subunits and binds nicotinic agonists with high affinity. In the present study, we investigated in the mouse the consequences of the deletion of one of the nAChR components: the beta2-subunit (beta2(-/-)) on the microanatomy of cortical pyramidal cells. Using an intracellular injection method, complete basal dendritic arbors of 650 layer III pyramidal neurons were sampled from seven cortical fields, including primary sensory, motor, and associational areas, in both beta2(-/-) and WT animals. We observed that the pyramidal cell phenotype shows significant quantitative differences among different cortical areas in mutant and WT mice. In WT mice, the density of dendritic spines was rather similar in all cortical fields, except in the prelimbic/infralimbic cortex, where it was significantly higher. In the absence of the beta2-subunit, the most significant reduction in the density of spines took place in this high-order associational field. Our data suggest that the beta2-subunit is involved in the dendritic morphogenesis of pyramidal neurons and, in particular, in the circuits that contribute to the high-order functional connectivity of the cerebral cortex.

Corticofugal direct projections to primary afferent neurons in the trigeminal mesencephalic nucleus of rats

Little is known about projections from the cerebral cortex to the trigeminal mesencephalic nucleus (Vmes) which contains the cell bodies of primary sensory afferents innervating masticatory muscle spindles and periodontal ligaments of the teeth. To address this issue, we employed retrograde (Fluorogold, FG) and anterograde (biotinylated dextranamine, BDA) tracing techniques in the rat. After injections of FG into the Vmes, a large number of neurons were retrogradely labeled in the prefrontal cortex including the medial agranular cortex, anterior cingulate cortex, prelimbic cortex, infralimbic cortex, deep peduncular cortex and insular cortex; the labeling was bilateral, but with an ipsilateral predominance to the injection site. Almost no FG-labeled neurons were found in the somatic sensorimotor cortex. After BDA injections into the prefrontal cortex, anterogradely labeled axon fibers and boutons were distributed bilaterally in a topographic pattern within the Vmes, but with an ipsilateral predominance to the injection site. The rostral Vmes received more preferential projections from the medial agranular cortex, while the deep peduncular cortex and insular cortex projected more preferentially to the caudal Vmes. Several BDA-labeled axonal boutons made close associations (possible synaptic contacts) with the cell bodies of Vmes neurons. The present results have revealed the direct projections from the prefrontal cortex to the primary sensory neurons in the Vmes and their unique features, suggesting that deep sensory inputs conveyed by the Vmes neurons from masticatory muscle spindles and periodontal ligaments are regulated with specific biological significance in terms of the descending control by the cerebral cortex.

Blockade of different muscarinic receptor subtypes changes the equilibrium between excitation and inhibition in rat visual cortex

We have shown that cortical acetylcholine modulates the balance between excitation and inhibition evoked in layer 5 pyramidal neurons of rat visual cortex [Lucas-Meunier E, Monier C, Amar M, Baux G, Frégnac Y, Fossier P (2009) Cereb Cortex 19:2411-2427]. Our aim is now to establish a functional basis for the role of the different types of muscarinic receptors (MRs) on glutamate fibers and on GABAergic interneurons and to analyse their contribution to the modulation of excitation-inhibition balance in the rat visual cortex. To ascertain that there was a basis for our functional study, we first checked for the presence of the various MR subtypes by single cell RT-PCR and immunolabeling experiments. Then, recording the composite responses in layer 5 pyramidal neurons to layer 1-2 stimulation (which also recruits cholinergic fibers) in the presence of specific antagonists of the different types of MR allowed us to determine their modulatory role. We show that the specific blockade of the widely distributed M1R (with the mamba toxin, MT7) induced a significant increase in the excitatory conductance without modifying the inhibitory conductance, pointing to a localization of M1R on glutamatergic neurons where their activation would decrease the release of glutamate. From our functional results, M2/M4Rs appear to be located on glutamatergic neurons afferent to the recorded layer 5 pyramidal neuron and they decrease glutamate release. The extended distribution of M4Rs in the cortex compared to the restricted distribution of M2R (layers 3-5) is in favour of a major role as a modulator of M4R. The selective antagonist of M3Rs, 4-DAMP, decreased the inhibitory conductance, showing that activated M3Rs increase the release of GABA and thus are located on GABAergic interneurons. The activation of the different types of MRs located either on glutamatergic neurons or on GABAergic interneurons converges to reinforce the dominance of inhibitory inputs thus decreasing the excitability of layer 5 pyramidal neurons.

Cell type-specific thalamic innervation in a column of rat vibrissal cortex

This is the concluding article in a series of 3 studies that investigate the anatomical determinants of thalamocortical (TC) input to excitatory neurons in a cortical column of rat primary somatosensory cortex (S1). We used viral synaptophysin-enhanced green fluorescent protein expression in thalamic neurons and reconstructions of biocytin-labeled cortical neurons in TC slices to quantify the number and distribution of boutons from the ventral posterior medial (VPM) and posteromedial (POm) nuclei potentially innervating dendritic arbors of excitatory neurons located in layers (L)2–6 of a cortical column in rat somatosensory cortex. We found that 1) all types of excitatory neurons potentially receive substantial TC input (90–580 boutons per neuron); 2) pyramidal neurons in L3–L6 receive dual TC input from both VPM and POm that is potentially of equal magnitude for thick-tufted L5 pyramidal neurons (ca. 300 boutons each from VPM and POm); 3) L3, L4, and L5 pyramidal neurons have multiple (2–4) subcellular TC innervation domains that match the dendritic compartments of pyramidal cells; and 4) a subtype of thick-tufted L5 pyramidal neurons has an additional VPM innervation domain in L4. The multiple subcellular TC innervation domains of L5 pyramidal neurons may partly explain their specific action potential patterns observed in vivo. We conclude that the substantial potential TC innervation of all excitatory neuron types in a cortical column constitutes an anatomical basis for the initial near-simultaneous representation of a sensory stimulus in different neuron types.

Dynamics of synaptic transmission between fast-spiking interneurons and striatal projection neurons of the direct and indirect pathways

The intrastriatal microcircuit is a predominantly inhibitory GABAergic network comprised of a majority of projection neurons [medium spiny neurons (MSNs)] and a minority of interneurons. The connectivity within this microcircuit is divided into two main categories: lateral connectivity between MSNs, and inhibition mediated by interneurons, in particular fast spiking (FS) cells. To understand the operation of striatum, it is essential to have a good description of the dynamic properties of these respective pathways and how they affect different types of striatal projection neurons. We recorded from neuronal pairs, triplets, and quadruplets in slices of rat and mouse striatum and analyzed the dynamics of synaptic transmission between MSNs and FS cells. Retrograde fluorescent labeling and transgenic EGFP (enhanced green fluorescent protein) mice were used to distinguish between MSNs of the direct (striatonigral) and indirect (striatopallidal) pathways. Presynaptic neurons were stimulated with trains of action potentials, and activity-dependent depression and facilitation of synaptic efficacy was recorded from postsynaptic neurons. We found that FS cells provide a strong and homogeneously depressing inhibition of both striatonigral and striatopallidal MSN types. Moreover, individual FS cells are connected to MSNs of both types. In contrast, both MSN types receive sparse and variable, depressing and facilitating synaptic transmission from nearby MSNs. The connection probability was higher for pairs with presynaptic striatopallidal MSNs; however, the variability in synaptic dynamics did not depend on the types of interconnected MSNs. The differences between the two inhibitory pathways were clear in both species and at different developmental stages. Our findings show that the two intrastriatal inhibitory pathways have fundamentally different dynamic properties that are, however, similarly applied to both direct and indirect striatal projections.

Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: gamma-range synchronization between sensory and executive cortical areas

In this computational work, we investigated gamma-band synchronization across cortical circuits associated with selective attention. The model explicitly instantiates a reciprocally connected loop of spiking neurons between a sensory-type (area MT) and an executive-type (prefrontal/parietal) cortical circuit (the source area for top-down attentional signaling). Moreover, unlike models in which neurons behave as clock-like oscillators, in our model single-cell firing is highly irregular (close to Poisson), while local field potential exhibits a population rhythm. In this "sparsely synchronized oscillation" regime, the model reproduces and clarifies multiple observations from behaving animals. Top-down attentional inputs have a profound effect on network oscillatory dynamics while only modestly affecting single-neuron spiking statistics. In addition, attentional synchrony modulations are highly selective: interareal neuronal coherence occurs only when there is a close match between the preferred feature of neurons, the attended feature, and the presented stimulus, a prediction that is experimentally testable. When interareal coherence was abolished, attention-induced gain modulations of sensory neurons were slightly reduced. Therefore, our model reconciles the rate and synchronization effects, and suggests that interareal coherence contributes to large-scale neuronal computation in the brain through modest enhancement of rate modulations as well as a pronounced attention-specific enhancement of neural synchrony.

Electrotonic coupling between pyramidal neurons in the neocortex

Electrotonic couplings (i.e., electrical synapses or gap junctions) are fundamental to neuronal synchronization, and thus essential for many physiological functions and pathological disorders. Interneuron electrical synapses have been studied intensively. Although studies on electrotonic couplings between pyramidal cells (PCs) are emerging, particularly in the hippocampus, evidence is still rare in the neocortex. The electrotonic coupling of PCs in the neocortex is therefore largely unknown in terms of electrophysiological, anatomical and synaptological properties. Using multiple patch-clamp recording with differential interference contrast infrared videomicroscopy (IR-DIC) visualization, histochemical staining, and 3D-computer reconstruction, electrotonic coupling was recorded between close PCs, mainly in the medial prefrontal cortex as well as in the visual cortical regions of ferrets and rats. Compared with interneuron gap junctions, these electrotonic couplings were characterized by several special features. The recording probability of an electrotonic coupling between PCs is extremely low; but the junctional conductance is notably high, permitting the direct transmission of action potentials (APs) and even tonic firing between coupled neurons. AP firing is therefore perfectly synchronized between coupled PCs; Postjunctional APs and spikelets alternate following slight changes of membrane potentials; Postjunctional spikelets, especially at high frequencies, are summated and ultimately reach AP-threshold to fire. These properties of pyramidal electrotonic couplings largely fill the needs, as predicted by simulation studies, for the synchronization of a neuronal assembly. It is therefore suggested that the electrotonic coupling of PCs plays a unique role in the generation of neuronal synchronization in the neocortex.

Properties of glutamatergic synapses in immature layer Vb pyramidal neurons: coupling of pre- and postsynaptic maturational states

Following initial contact formation, glutamatergic synapses in cortical neurons undergo pronounced functional maturation. These maturational events, occurring both pre- and postsynaptically, have been well described in the developing hippocampus. In this paper, we characterized glutamatergic synapses in immature layer Vb pyramidal neurons of the mouse somatosensory cortex during early postnatal development. At postnatal day 7, a significant subpopulation of glutamatergic synapses exhibited a low release probability that was accompanied by strong paired-pulse facilitation of AMPA EPSCs (paired-pulse ratio C > or = 2). Increasing extracellular Ca(2+) concentration increased release probability and led to paired-pulse depression. During further postnatal development, these functionally immature synapses disappeared. As shown pharmacologically,these synapses expressed postsynaptic NMDA receptors containing NR2B subunits, while NMDA receptors with NR2A subunits were lacking. Taken together, a low release probability presynaptically was coupled to postsynaptic NR2B signaling. This subpopulation of neocortical synapses thus differed from the majority of synapses in the developing hippocampus, where high release probability is coupled to NR2B signaling. The novel type of functionally immature glutamatergic synapse described here might play an important role in early developmental synapse elimination and in the activity-dependent refinement of the neocortical synaptic microcircuitry.

Chronic network stimulation enhances evoked action potentials

Neurons cultured on multielectrode arrays almost always lack external stimulation except during the acute experimental phase. We have investigated the effects of chronic stimulation during the course of development in cultured hippocampal neural networks by applying paired pulses at half of the electrodes for 0, 1 or 3 r/day for 8 days. Spike latencies increased from 4 to 16 ms as the distance from the stimulus increased from 200 to 1700 microm, suggesting an average of four synapses over this distance. Compared to no chronic stimulation, our results indicate that chronic stimulation increased evoked spike counts per stimulus by 50% at recording sites near the stimulating electrode and increased the instantaneous firing rate. On trials where both pulses elicited responses, spike count was 40-80% higher than when only one of the pulses elicited a response. In attempts to identify spike amplitude plasticity, we found mainly amplitude variation with different latencies suggesting recordings from neurons with different identities. These data suggest plastic network changes induced by chronic stimulation that enhance the reliability of information transmission and the efficiency of multisynaptic network communication.

Clustered cortical organization and the enhanced probability of intra-areal functional integration

Similarly responsive neurons organize into submillimeter-sized clusters (domains) across many neocortical areas, notably in Areas V1 and V2 of primate visual cortex. While this clustered organization may arise from wiring minimization or from self-organizing development, it could potentially support important neural computation benefits. Here, we suggest that domain organization offers an efficient computational mechanism for intra-areal functional integration in certain cortical areas and hypothesize that domain proximity could support a higher-than-expected spatial correlation of their respective terminals yielding higher probabilities of integration of differing domain preferences. To investigate this hypothesis we devised a spatial model inspired by known parameters of V2 functional organization, where neighboring domains prefer either colored or oriented stimuli. Preference-selective joint probabilities were calculated for model terminal co-occurrence with configurations encompassing diverse domain proximity, shape, and projection. Compared to random distributions, paired neighboring domains (< or =1200 microm apart) yielded significantly enhanced coincidence of terminals converging from each domain. Using this reference data, a second larger-scale model indicated that V2 domain organization may accommodate relatively complete sets of intra-areal color/orientation integrations. Together, these data indicate that domain organization could support significant and efficient intra-areal integration of different preferences and suggest further experiments investigating prevalence and mechanisms of domain-mediated intra-areal integration.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV: structuring synaptic pathways among recurrent connections

In neuronal networks, the changes of synaptic strength (or weight) performed by spike-timing-dependent plasticity (STDP) are hypothesized to give rise to functional network structure. This article investigates how this phenomenon occurs for the excitatory recurrent connections of a network with fixed input weights that is stimulated by external spike trains. We develop a theoretical framework based on the Poisson neuron model to analyze the interplay between the neuronal activity (firing rates and the spike-time correlations) and the learning dynamics, when the network is stimulated by correlated pools of homogeneous Poisson spike trains. STDP can lead to both a stabilization of all the neuron firing rates (homeostatic equilibrium) and a robust weight specialization. The pattern of specialization for the recurrent weights is determined by a relationship between the input firing-rate and correlation structures, the network topology, the STDP parameters and the synaptic response properties. We find conditions for feed-forward pathways or areas with strengthened self-feedback to emerge in an initially homogeneous recurrent network.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks III: Partially connected neurons driven by spontaneous activity

In contrast to a feed-forward architecture, the weight dynamics induced by spike-timing-dependent plasticity (STDP) in a recurrent neuronal network is not yet well understood. In this article, we extend a previous study of the impact of additive STDP in a recurrent network that is driven by spontaneous activity (no external stimulating inputs) from a fully connected network to one that is only partially connected. The asymptotic state of the network is analyzed, and it is found that the equilibrium and stability conditions for the firing rates are similar for both full and partial connectivity: STDP causes the firing rates to converge toward the same value and remain quasi-homogeneous. However, when STDP induces strong weight competition, the connectivity affects the weight dynamics in that the distribution of the weights disperses more quickly for lower density than for higher density. The asymptotic weight distribution strongly depends upon that at the beginning of the learning epoch; consequently, homogeneous connectivity alone is not sufficient to obtain homogeneous neuronal activity. In the absence of external inputs, STDP can nevertheless generate structure in the network through autocorrelation effects, for example, by introducing asymmetry in network topology.

Multiquantal release underlies the distribution of synaptic efficacies in the neocortex

Inter-pyramidal synaptic connections are characterized by a wide range of EPSP amplitudes. Although repeatedly observed at different brain regions and across layers, little is known about the synaptic characteristics that contribute to this wide range. In particular, the range could potentially be accounted for by differences in all three parameters of the quantal model of synaptic transmission, i.e. the number of release sites, release probability and quantal size. Here, we present a rigorous statistical analysis of the transmission properties of excitatory synaptic connections between layer-5 pyramidal neurons of the somato-sensory cortex. Our central finding is that the EPSP amplitude is strongly correlated with the number of estimated release sites, but not with the release probability or quantal size. In addition, we found that the number of release sites can be more than an order of magnitude higher than the typical number of synaptic contacts for this type of connection. Our findings indicate that transmission at stronger synaptic connections is mediated by multiquantal release from their synaptic contacts. We propose that modulating the number of release sites could be an important mechanism in regulating neocortical synaptic transmission.

Dynamical origin of the effective storage capacity in the brain's working memory

The capacity of working memory (WM), a short-term buffer for information in the brain, is limited. We suggest a model for sequential WM that is based upon winnerless competition amongst representations of available informational items. Analytical results for the underlying mathematical model relate WM capacity and relative lateral inhibition in the corresponding neural network. This implies an upper bound for WM capacity, which is, under reasonable neurobiological assumptions, close to the "magical number seven."

Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner

Complex neural dynamics produced by the recurrent architecture of neocortical circuits is critical to the cortex's computational power. However, the synaptic learning rules underlying the creation of stable propagation and reproducible neural trajectories within recurrent networks are not understood. Here, we examined synaptic learning rules with the goal of creating recurrent networks in which evoked activity would: (1) propagate throughout the entire network in response to a brief stimulus while avoiding runaway excitation; (2) exhibit spatially and temporally sparse dynamics; and (3) incorporate multiple neural trajectories, i.e., different input patterns should elicit distinct trajectories. We established that an unsupervised learning rule, termed presynaptic-dependent scaling (PSD), can achieve the proposed network dynamics. To quantify the structure of the trained networks, we developed a recurrence index, which revealed that presynaptic-dependent scaling generated a functionally feedforward network when training with a single stimulus. However, training the network with multiple input patterns established that: (1) multiple non-overlapping stable trajectories can be embedded in the network; and (2) the structure of the network became progressively more complex (recurrent) as the number of training patterns increased. In addition, we determined that PSD and spike-timing-dependent plasticity operating in parallel improved the ability of the network to incorporate multiple and less variable trajectories, but also shortened the duration of the neural trajectory. Together, these results establish one of the first learning rules that can embed multiple trajectories, each of which recruits all neurons, within recurrent neural networks in a self-organizing manner.

Encoding and decoding bursts by NMDA spikes in basal dendrites of layer 5 pyramidal neurons

Bursts of action potentials are important information-bearing signals in the brain, although the neuronal specializations underlying burst generation and detection are only partially understood. In apical dendrites of neocortical pyramidal neurons, calcium spikes are known to contribute to burst generation, but a comparable understanding of basal dendritic mechanisms is lacking. Here we show that NMDA spikes in basal dendrites mediate both detection and generation of bursts through a postsynaptic mechanism. High-frequency inputs to basal dendrites markedly facilitated NMDA spike initiation compared with low-frequency activation or single inputs. Unlike conventional temporal summation effects based on voltage, however, NMDA spike facilitation depended mainly on residual glutamate bound to NMDA receptors from previous activations. Once triggered by an input burst, we found that NMDA spikes in turn reliably trigger output bursts under in vivo-like stimulus conditions. Through their unique biophysical properties, NMDA spikes are thus ideally suited to promote the propagation of bursts through the cortical network.

Selective expression of ligand-gated ion channels in L5 pyramidal cell axons

NMDA receptor (NMDAR)-dependent strengthening of neurotransmitter release has been widely observed, including in layer 5 (L5) pyramidal cells of the visual cortex, and is attributed to the axonal expression of NMDARs. However, we failed to detect NMDAR-mediated depolarizations or Ca(2+) entry in L5 pyramidal cell axons when focally stimulated with NMDAR agonists. This suggests that NMDARs are excluded from the axon. In contrast, local GABA(A) receptor activation alters axonal excitability, indicating that exclusion of ligand-gated ion channels from the axon is not absolute. Because NMDARs are restricted to the dendrite, NMDARs must signal to the axon by an indirect mechanism to alter release. Although subthreshold somatic depolarizations were found to spread electrotonically hundreds of micrometers through the axon, the resulting axonal potential was insufficient to open voltage-sensitive Ca(2+) channels. Therefore, if NMDAR-mediated facilitation of release is cell autonomous, it may depend on voltage signaling but apparently is independent of changes in basal Ca(2+). Alternatively, this facilitation may be even less direct, requiring a cascade of events that are merely triggered by NMDAR activation.

Sensory Experience and Cortical Rewiring

Adult primary sensory cortex is not hard wired, but adapts to sensory experience. The cellular basis for cortical plasticity involves a combination of functional and structural changes in cortical neurons and the connections between them. Functional changes such as synaptic strengthening have been the focus of many investigations. However, structural modifications to the connections between neurons play an important role in cortical plasticity. In this review, the authors focus on structural remodeling that leads to rewiring of cortical circuits. Recent work has identified axonal remodeling, growth of new dendritic spines, and synapse turnover as important structural mechanisms for experience-dependent plasticity in mature cortex. These findings have begun to unravel how rewiring occurs in adult neocortex and offer new insights into the cellular mechanisms for learning and memory.

Intact long-term potentiation but reduced connectivity between neocortical layer 5 pyramidal neurons in a mouse model of Rett syndrome

Mutations in MECP2 cause Rett syndrome and some related forms of mental retardation and autism. Mecp2-null mice exhibit symptoms reminiscent of Rett syndrome including deficits in learning. Previous reports demonstrated impaired long-term potentiation (LTP) in slices of symptomatic Mecp2-null mice, and decreased excitatory neurotransmission, but the causal relationship between these phenomena is unclear. Reduced plasticity could lead to altered transmission, or reduced excitatory transmission could alter the ability to induce LTP. To help distinguish these possibilities, we compared LTP induction and baseline synaptic transmission at synapses between layer 5 cortical pyramidal neurons in slices of wild-type and Mecp2-null mice. Paired recordings reveal that LTP induction mechanisms are intact in Mecp2-null connections, even after the onset of symptoms. However, fewer connections were found in Mecp2-null mice and individual connections were weaker. These data suggest that loss of MeCP2 function reduces excitatory synaptic connectivity and that this precedes deficits in plasticity.

Hebbian crosstalk prevents nonlinear unsupervised learning

Learning is thought to occur by localized, activity-induced changes in the strength of synaptic connections between neurons. Recent work has shown that induction of change at one connection can affect changes at others (“crosstalk”). We studied the role of such crosstalk in nonlinear Hebbian learning using a neural network implementation of independent components analysis. We find that there is a sudden qualitative change in the performance of the network at a threshold crosstalk level, and discuss the implications of this for nonlinear learning from higher-order correlations in the neocortex.

Frequency-dependent disynaptic inhibition in the pyramidal network: a ubiquitous pathway in the developing rat neocortex

The general structure of the mammalian neocortex is remarkably similar across different cortical areas. Despite certain cytoarchitectural specializations and deviations from the general blueprint, the principal organization of the neocortex is relatively uniform. It is not known, however, to what extent stereotypic synaptic pathways resemble each other between cortical areas, and how far they might reflect possible functional uniformity or specialization. Here, we show that frequency-dependent disynaptic inhibition (FDDI) is a generic circuit motif that is present in all neocortical areas we investigated (primary somatosensory, auditory and motor cortex, secondary visual cortex and medial prefrontal cortex of the developing rat). We did find, however, area-specific differences in occurrence and kinetics of FDDI and the short-term dynamics of monosynaptic connections between pyramidal cells (PCs). Connectivity between PCs, both monosynaptic and via FDDI, is higher in primary cortices. The long-term effectiveness of FDDI is likely to be limited by an activity-dependent attenuation of the PC-interneuron synaptic transmission. Our results suggest that the basic construction of neocortical synaptic pathways follows principles that are independent of modality or hierarchical order within the neocortex.

How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains

Functional interactions between neurons in vivo are often quantified by cross-correlation functions (CCFs) between their spike trains. It is therefore essential to understand quantitatively how CCFs are shaped by different factors, such as connectivity, synaptic parameters, and background activity. Here, we study the CCF between two neurons using analytical calculations and numerical simulations. We quantify the role of synaptic parameters, such as peak conductance, decay time, and reversal potential, and analyze how various patterns of connectivity influence CCF shapes. In particular, we find that the symmetry of the CCF distinguishes in general, but not always, the case of shared inputs between two neurons from the case in which they are directly synaptically connected. We systematically examine the influence of background synaptic inputs from the surrounding network that set the baseline firing statistics of the neurons and modulate their response properties. We find that variations in the background noise modify the amplitude of the cross-correlation function as strongly as variations of synaptic strength. In particular, we show that the postsynaptic neuron spiking regularity has a pronounced influence on CCF amplitude. This suggests an efficient and flexible mechanism for modulating functional interactions.

Cooperative synapse formation in the neocortex

Neuron morphology plays an important role in defining synaptic connectivity. Clearly, only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, such axo-dendritic oppositions, termed potential synapses, must be bridged by dendritic spines to form synaptic connections. To explore the rules by which synaptic connections are formed within the constraints imposed by neuron morphology, we compared the distributions of the numbers of actual and potential synapses between pre- and postsynaptic neurons forming different laminar projections in rat barrel cortex. Quantitative comparison explicitly ruled out the hypothesis that individual synapses between neurons are formed independently of each other. Instead, the data are consistent with a cooperative scheme of synapse formation where multiple-synaptic connections between neurons are stabilized while neurons that do not establish a critical number of synapses are not likely to remain synaptically coupled.

Cell-type identity: a key to unlocking the function of neocortical circuits

A central tenet of neuroscience is that the precise patterns of connectivity among neurons in a given brain area underlie its function. However, assigning any aspect of perception or behavior to the wiring of local circuits has been challenging. Here, we review recent work in sensory neocortex that demonstrates the power of identifying specific cell types when investigating the functional organization of brain circuits. These studies indicate that knowing the identity of both the presynaptic and postsynaptic cell type is key when analyzing neocortical circuits. Furthermore, identifying the circuit organization of particular cell types in the neocortex allows the recording and manipulation of each cell type's activity and the direct testing of its functional role in perception and behavior.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity--symmetry breaking

Spike-timing-dependent plasticity (STDP) is believed to structure neuronal networks by slowly changing the strengths (or weights) of the synaptic connections between neurons depending upon their spiking activity, which in turn modifies the neuronal firing dynamics. In this paper, we investigate the change in synaptic weights induced by STDP in a recurrently connected network in which the input weights are plastic but the recurrent weights are fixed. The inputs are divided into two pools with identical constant firing rates and equal within-pool spike-time correlations, but with no between-pool correlations. Our analysis uses the Poisson neuron model in order to predict the evolution of the input synaptic weights and focuses on the asymptotic weight distribution that emerges due to STDP. The learning dynamics induces a symmetry breaking for the individual neurons, namely for sufficiently strong within-pool spike-time correlation each neuron specializes to one of the input pools. We show that the presence of fixed excitatory recurrent connections between neurons induces a group symmetry-breaking effect, in which neurons tend to specialize to the same input pool. Consequently STDP generates a functional structure on the input connections of the network.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity--strengthening correlated input pathways

Spike-timing-dependent plasticity (STDP) determines the evolution of the synaptic weights according to their pre- and post-synaptic activity, which in turn changes the neuronal activity. In this paper, we extend previous studies of input selectivity induced by (STDP) for single neurons to the biologically interesting case of a neuronal network with fixed recurrent connections and plastic connections from external pools of input neurons. We use a theoretical framework based on the Poisson neuron model to analytically describe the network dynamics (firing rates and spike-time correlations) and thus the evolution of the synaptic weights. This framework incorporates the time course of the post-synaptic potentials and synaptic delays. Our analysis focuses on the asymptotic states of a network stimulated by two homogeneous pools of "steady" inputs, namely Poisson spike trains which have fixed firing rates and spike-time correlations. The (STDP) model extends rate-based learning in that it can implement, at the same time, both a stabilization of the individual neuron firing rates and a slower weight specialization depending on the input spike-time correlations. When one input pathway has stronger within-pool correlations, the resulting synaptic dynamics induced by (STDP) are shown to be similar to those arising in the case of a purely feed-forward network: the weights from the more correlated inputs are potentiated at the expense of the remaining input connections.

Cell-type specific properties of pyramidal neurons in neocortex underlying a layout that is modifiable depending on the cortical area

To understand sensory representation in cortex, it is crucial to identify its constituent cellular components based on cell-type-specific criteria. With the identification of cell types, an important question can be addressed: to what degree does the cellular properties of neurons depend on cortical location? We tested this question using pyramidal neurons in layer 5 (L5) because of their role in providing major cortical output to subcortical targets. Recently developed transgenic mice with cell-type-specific enhanced green fluorescent protein labeling of neuronal subtypes allow reliable identification of 2 cortical cell types in L5 throughout the entire neocortex. A comprehensive investigation of anatomical and functional properties of these 2 cell types in visual and somatosensory cortex demonstrates that, with important exceptions, most properties appear to be cell-type-specific rather than dependent on cortical area. This result suggests that although cortical output neurons share a basic layout throughout the sensory cortex, fine differences in properties are tuned to the cortical area in which neurons reside.

Implications of synaptic biophysics for recurrent network dynamics and active memory

In cortical networks, synaptic excitation is mediated by AMPA- and NMDA-type receptors. NMDA differ from AMPA synaptic potentials with regard to peak current, time course, and a strong voltage-dependent nonlinearity. Here we illustrate based on empirical and computational findings that these specific biophysical properties may have profound implications for the dynamics of cortical networks, and via dynamics on cognitive functions like active memory. The discussion will be led along a minimal set of neural equations introduced to capture the essential dynamics of the various phenomena described. NMDA currents could establish cortical bistability and may provide the relatively constant synaptic drive needed to robustly maintain enhanced levels of activity during working memory epochs, freeing fast AMPA currents for other computational purposes. Perhaps more importantly, variations in NMDA synaptic input-due to their biophysical particularities-control the dynamical regime within which single neurons and networks reside. By provoking bursting, chaotic irregularity, and coherent oscillations their major effect may be on the temporal pattern of spiking activity, rather than on average firing rate. During active memory, neurons may thus be pushed into a spiking regime that harbors complex temporal structure, potentially optimal for the encoding and processing of temporal sequence information. These observations provide a qualitatively different view on the role of synaptic excitation in neocortical dynamics than entailed by many more abstract models. In this sense, this article is a plead for taking the specific biophysics of real neurons and synapses seriously when trying to account for the neurobiology of cognition.

Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors

The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.

Coupling of mesoscopic brain oscillations: recent advances in analytical and theoretical perspectives

Oscillatory brain activities have been traditionally studied in the context of how oscillations at a single frequency recorded from a single area could reveal functional insights. Recent advances in methodology used in signal analysis have revealed that cross-frequency coupling, within or between functional related areas, is more informative in determining the possible roles played by brain oscillations. In this review, we begin by describing the cellular basis of oscillatory field potentials and its theorized as well as demonstrated role in brain function. The recent development of mathematical tools that allow the investigation of cross-frequency and cross-area oscillation coupling will be presented and discussed in the context of recent advances in oscillation research based on animal data. Particularly, some pitfalls and caveats of methods currently available are discussed. Data generated from the application of examined techniques are integrated back into the theoretical framework regarding the functional role of brain oscillations. We suggest that the coupling of oscillatory activities at different frequencies between brain regions is crucial for understanding the brain from a functional ensemble perspective. Effort should be directed to elucidate how cross-frequency and area coupling are modulated and controlled. To achieve this, only the correct application of analytical tools may shed light on the intricacies of information representation, generation, binding, encoding, storage and retrieval in the brain.

Activity level-dependent synapse-specific AMPA receptor trafficking regulates transmission kinetics

Central glutamatergic synapses may express AMPA-sensitive glutamate receptors (AMPA-Rs) with distinct gating properties and exhibit different transmission dynamics, which are important for computing various synaptic inputs received at different populations of synapses. However, how glutamatergic synapses acquire AMPA-Rs with distinct kinetics to influence synaptic integration remains poorly understood. Here I report synapse-specific trafficking of distinct AMPA-Rs in rat cortical layer 4 stellate and layer 5 pyramidal neurons. The analysis indicates that in single layer 4 stellate neurons thalamocortical synapses generate faster synaptic responses than intracortical synapses. Moreover, GluR1-containing AMPA-Rs traffic selectively into intracortical synapses, and this process requires sensory experience-dependent activity and slows down transmission kinetics. GluR4-containing AMPA-Rs traffic more heavily into thalamocortical synapses than intracortical synapses, and this process requires spontaneous synaptic activity and speeds up transmission kinetics. GluR2-containing AMPA-Rs traffic equally into both thalamocortical and intracortical synapses, and this process requires no synaptic activity and resets transmission kinetics. Notably, synaptic trafficking of distinct AMPA-Rs differentially regulates synaptic integration. Thus, synapse-specific AMPA-R trafficking coarsely sets and synaptic activity finely tunes transmission kinetics and integration properties at different synapses in central neurons.

Postnatal development of dendritic synaptic integration in rat neocortical pyramidal neurons

The dendritic tree of layer 5 (L5) pyramidal neurons spans the neocortical layers, allowing the integration of intra- and extracortical synaptic inputs. Here we investigate the postnatal development of the integrative properties of rat L5 pyramidal neurons using simultaneous whole cell recording from the soma and distal apical dendrite. In young (P9-10) neurons, apical dendritic excitatory synaptic input powerfully drove action potential output by efficiently summating at the axonal site of action potential generation. In contrast, in mature (P25-29) neurons, apical dendritic excitatory input provided little direct depolarization at the site of action potential generation but was integrated locally in the apical dendritic tree leading to the generation of dendritic spikes. Consequently, over the first postnatal month the fraction of action potentials driven by apical dendritic spikes increased dramatically. This developmental remodeling of the integrative operations of L5 pyramidal neurons was controlled by a >10-fold increase in the density of apical dendritic Hyperpolarization-activated cyclic nucleotide (HCN)-gated channels found in cell-attached patches or by immunostaining for the HCN channel isoform HCN1. Thus an age-dependent increase in apical dendritic HCN channel density ensures that L5 pyramidal neurons develop from compact temporal integrators to compartmentalized integrators of basal and apical dendritic synaptic input.

Synaptic interactions between forelimb-related motor cortex neurons in behaving primates

We investigated the synaptic interactions between neighboring motor cortex cells in monkeys generating isometric ramp-and-hold torques about the wrist. For pairs of cortical cells the response patterns were determined in response-aligned averages and their synaptic interactions were identified by cross-correlation histograms. Cross-correlograms were compiled for 215 cell pairs and 84 (39%) showed significant features. The most frequently found feature (65/84 = 77%) was a central peak, straddling the origin and representing a source of common synaptic input to both cells. One third of these also had superimposed lagged peaks, indicative of a serial excitatory connection. Pure lagged peaks and lagged troughs, indicative of serial excitatory or inhibitory linkages, respectively, both occurred in 5% of the correlograms with features. A central trough appeared in 13% of the correlograms. The magnitude of the synaptic linkage was measured as the normalized area of the correlogram feature. Plotting the strength of synaptic interaction against response similarity during alternating wrist torques revealed a positive relationship for the correlated cell pairs. A linear fit yielded a positive slope: the pairs with excitatory interactions tended to covary more often than countervary. This linear fit had a positive offset, reflecting a tendency for both covarying and countervarying cells to have excitatory common input. Plotting the cortical location of the cell pairs showed that the strongest interactions occurred between cells separated by <400 microns. The correlational linkages between cells of different cortical layers showed a large proportion of common input to cells in layer V.

Synaptic output of individual layer 4 neurons in guinea pig visual cortex

More than 90% of geniculocortical axons from the dorsal lateral geniculate nucleus of the thalamus innervate layer 4 (L4) of V1 (primary visual cortex). Excitatory neurons, which comprise >80% of the neuronal population in L4, synapse mainly onto adjacent L4 neurons and layer 2/3 (L2/3) neurons. It has been suggested that intralaminar L4-L4 connections contribute to amplifying and refining thalamocortical signals before routing to L2/3. To unambiguously probe the properties of the synaptic outputs from these L4 excitatory neurons, we used multiple simultaneous whole-cell patch-clamp recording and stimulation from two to four neighboring L4 neurons. We recorded uEPSCs (evoked unitary synaptic currents) in response to pairs of action potentials elicited in single presynaptic L4 neurons for 102 L4 cell pairs and found that their properties are more diverse than previously described. Averaged unitary synaptic response peak amplitudes spanned almost three orders of magnitude, from 0.42 to 192.92 pA. Although connections were, on average, reliable (average failure rate, 25%), we recorded a previously unknown subset of unreliable (failure rates from 30 to 100%) and weak (averaged response amplitudes, <5 pA) connections. Reliable connections with high probability of neurotransmitter release responded to paired presynaptic pulses with depression, whereas unreliable connections underwent paired-pulse facilitation. Recordings from interconnected sets of L4 triplets revealed that synaptic response amplitudes and reliability were equally variable between independent cell pairs and those that shared a common presynaptic or postsynaptic cell, suggesting local perisynaptic influences on the development and/or state of synaptic function.

The probability of neurotransmitter release: variability and feedback control at single synapses

Information transfer at chemical synapses occurs when vesicles fuse with the plasma membrane and release neurotransmitter. This process is stochastic and its likelihood of occurrence is a crucial factor in the regulation of signal propagation in neuronal networks. The reliability of neurotransmitter release can be highly variable: experimental data from electrophysiological, molecular and imaging studies have demonstrated that synaptic terminals can individually set their neurotransmitter release probability dynamically through local feedback regulation. This local tuning of transmission has important implications for current models of single-neuron computation.

Thermodynamic constraints on neural dimensions, firing rates, brain temperature and size

There have been suggestions that heat caused by cerebral metabolic activity may constrain mammalian brain evolution, architecture, and function. This article investigates physical limits on brain wiring and corresponding changes in brain temperature that are imposed by thermodynamics of heat balance determined mainly by Na(+)/K(+)-ATPase, cerebral blood flow, and heat conduction. It is found that even moderate firing rates cause significant intracellular Na(+) build-up, and the ATP consumption rate associated with pumping out these ions grows nonlinearly with frequency. Surprisingly, the power dissipated by the Na(+)/K(+) pump depends biphasically on frequency, which can lead to the biphasic dependence of brain temperature on frequency as well. Both the total power of sodium pumps and brain temperature diverge for very small fiber diameters, indicating that too thin fibers are not beneficial for thermal balance. For very small brains blood flow is not a sufficient cooling mechanism deep in the brain. The theoretical lower bound on fiber diameter above which brain temperature is in the operational regime is strongly frequency dependent but finite due to synaptic depression. For normal neurophysiological conditions this bound is at least an order of magnitude smaller than average values of empirical fiber diameters, suggesting that neuroanatomy of the mammalian brains operates in the thermodynamically safe regime. Analytical formulas presented can be used to estimate average firing rates in mammals, and relate their changes to changes in brain temperature, which can have important practical applications. In general, activity in larger brains is found to be slower than in smaller brains.

Rapid neocortical dynamics: cellular and network mechanisms

The highly interconnected local and large-scale networks of the neocortical sheet rapidly and dynamically modulate their functional connectivity according to behavioral demands. This basic operating principle of the neocortex is mediated by the continuously changing flow of excitatory and inhibitory synaptic barrages that not only control participation of neurons in networks but also define the networks themselves. The rapid control of neuronal responsiveness via synaptic bombardment is a fundamental property of cortical dynamics that may provide the basis of diverse behaviors, including sensory perception, motor integration, working memory, and attention.

Presynaptic NMDA receptors: newly appreciated roles in cortical synaptic function and plasticity

Many aspects of synaptic development, plasticity, and neurotransmission are critically influenced by NMDA-type glutamate receptors (NMDARs). Moreover, dysfunction of NMDARs has been implicated in a broad array of neurological disorders, including schizophrenia, stroke, epilepsy, and neuropathic pain. Classically, NMDARs were thought to be exclusively postsynaptic. However, substantial evidence in the past 10 years demonstrates that NMDARs also exist presynaptically and that presynaptic NMDA receptors (preNMDARs) modulate synapse function and have critical roles in plasticity at many synapses. Here the authors review current knowledge of the role of preNMDARs in synaptic transmission and plasticity, focusing on the neocortex. They discuss the prevalence, function, and development of these receptors, and their potential modification by experience and in brain pathology.

3D structural imaging of the brain with photons and electrons

Recent technological developments have renewed the interest in large-scale neural circuit reconstruction. To resolve the structure of entire circuits, thousands of neurons must be reconstructed and their synapses identified. Reconstruction techniques at the light microscopic level are capable of following sparsely labeled neurites over long distances, but fail with densely labeled neuropil. Electron microscopy provides the resolution required to resolve densely stained neuropil, but is challenged when data for volumes large enough to contain complete circuits need to be collected. Both photon-based and electron-based imaging methods will ultimately need highly automated data analysis, because the manual tracing of most networks of interest would require hundreds to tens of thousands of years in human labor.

Polysynaptic subcircuits in the neocortex: spatial and temporal diversity

Inhibitory pathways in the neocortex display a variety of temporal and spatial patterns, maintaining a dynamic balance with excitatory synaptic activity. Recent studies have revealed prevalent polysynaptic subcircuits within the neocortical microcircuitry. These subcircuits involve excitatory and inhibitory connections that are activated by neurons both in supragranular and infragranular cortical layers and mediated by different mechanisms. Interestingly, in these subcircuits inhibition is induced by discharge of pyramidal cells, and excitation is caused by specific types of GABAergic interneurons. The different polysynaptic subcircuits are discussed with respect to their spatial and temporal properties and their possible functional role in cortical processing.

Synaptic clustering by dendritic signalling mechanisms

Dendritic signal integration is one of the fundamental building blocks of information processing in the brain. Dendrites are endowed with mechanisms of nonlinear summation of synaptic inputs leading to regenerative dendritic events including local sodium, NMDA and calcium spikes. The generation of these events requires distinct spatio-temporal activation patterns of synaptic inputs. We hypothesise that the recent findings on dendritic spikes and local synaptic plasticity rules suggest clustering of common inputs along a subregion of a dendritic branch. These clusters may enable dendrites to separately threshold groups of functionally similar inputs, thus allowing single neurons to act as a superposition of many separate integrate and fire units. Ultimately, these properties expand our understanding about the computational power of neuronal networks.

Small voltage changes at nerve terminals travel up axons to affect action potential initiation

Nerve terminals are generally considered the destination points for electrical signals, which propagate unidirectionally from the soma to nerve terminals. Here, we demonstrate that small hyperpolarizations or depolarizations (~10 mV), generated under physiological conditions in rat nerve terminals, backpropagate up the axon (~400 – 800 µm), and change the threshold for initiating action potentials and thus firing patterns. These results suggest a novel mechanism for information processing in neurons and neuronal circuits.

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

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