Anatomical and functional differentiation of glutamatergic synaptic innervation in the neocortex.

Pyramidal neurons are the principal neurons of the neocortex and their excitatory impact on other pyramidal neurons and interneurons is central to neocortical dynamics. A fundamental principal that has emerged which governs pyramidal neuron excitation of other neurons in the local circuitry of neocortical columns is differential anatomical and physiological properties of the synaptic innervation via the same axon depending on the type of neuron targeted. In this study we derive anatomical principles for divergent innervation of pyramidal neurons of the same type within the local microcircuit. We also review data providing circumstantial and direct evidence for differential synaptic transmission via the same axon from neocortical pyramidal neurons and derive some principles for differential synaptic innervation of pyramidal neurons of the same type, of pyramidal neurons and interneurons and of different types of interneurons. We conclude that differential anatomical and physiological differentiation is a fundamental property of glutamatergic axons of pyramidal neurons in the neocortex.     

A cortical attractor network with Martinotti cells driven by facilitating synapses

The population of pyramidal cells significantly outnumbers the inhibitory interneurons in the neocortex, while at the same time the diversity of interneuron types is much more pronounced. One acknowledged key role of inhibition is to control the rate and patterning of pyramidal cell firing via negative feedback, but most likely the diversity of inhibitory pathways is matched by a corresponding diversity of functional roles. An important distinguishing feature of cortical interneurons is the variability of the short-term plasticity properties of synapses received from pyramidal cells. The Martinotti cell type has recently come under scrutiny due to the distinctly facilitating nature of the synapses they receive from pyramidal cells. This distinguishes these neurons from basket cells and other inhibitory interneurons typically targeted by depressing synapses. A key aspect of the work reported here has been to pinpoint the role of this variability. We first set out to reproduce quantitatively based on in vitro data the di-synaptic inhibitory microcircuit connecting two pyramidal cells via one or a few Martinotti cells. In a second step, we embedded this microcircuit in a previously developed attractor memory network model of neocortical layers 2/3. This model network demonstrated that basket cells with their characteristic depressing synapses are the first to discharge when the network enters an attractor state and that Martinotti cells respond with a delay, thereby shifting the excitation-inhibition balance and acting to terminate the attractor state. A parameter sensitivity analysis suggested that Martinotti cells might, in fact, play a dominant role in setting the attractor dwell time and thus cortical speed of processing, with cellular adaptation and synaptic depression having a less prominent role than previously thought.     

Predicting single spikes and spike patterns with the Hindmarsh–Rose model

Most simple neuron models are only able to model traditional spiking behavior. As physiologists discover and classify different electrical phenotypes, computational neuroscientists become interested in using simple phenomenological models that can exhibit these different types of spiking patterns. The Hindmarsh–Rose model is a three-dimensional relaxation oscillator which can show both spiking and bursting patterns and has a chaotic regime. We test the predictive powers of the Hindmarsh–Rose model on two different test databases. We show that the Hindmarsh–Rose model can predict the spiking response of rat layer 5 neocortical pyramidal neurons on a stochastic input signal with a precision comparable to the best known spiking models. We also show that the Hindmarsh–Rose model can capture qualitatively the electrical footprints in a database of different types of neocortical interneurons. When the model parameters are fit from sub-threshold measurements only, the model still captures well the electrical phenotype, which suggests that the sub-threshold signals contain information about the firing patterns of the different neurons.     

Functional Integration of Human Neural Precursor Cells in Mouse Cortex

This study investigates the electrophysiological properties and functional integration of different phenotypes of transplanted human neural precursor cells (hNPCs) in immunodeficient NSG mice. Postnatal day 2 mice received unilateral injections of 100,000 GFP+ hNPCs into the right parietal cortex. Eight weeks after transplantation, 1.21% of transplanted hNPCs survived. In these hNPCs, parvalbumin (PV)-, calretinin (CR)-, somatostatin (SS)-positive inhibitory interneurons and excitatory pyramidal neurons were confirmed electrophysiologically and histologically. All GFP+ hNPCs were immunoreactive with anti-human specific nuclear protein. The proportions of PV-, CR-, and SS-positive cells among GFP+ cells were 35.5%, 15.7%, and 17.1%, respectively; around 15% of GFP+ cells were identified as pyramidal neurons. Those electrophysiologically and histological identified GFP+ hNPCs were shown to fire action potentials with the appropriate firing patterns for different classes of neurons and to display spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs and sIPSCs). The amplitude, frequency and kinetic properties of sEPSCs and sIPSCs in different types of hNPCs were comparable to host cells of the same type. In conclusion, GFP+ hNPCs produce neurons that are competent to integrate functionally into host neocortical neuronal networks. This provides promising data on the potential for hNPCs to serve as therapeutic agents in neurological diseases with abnormal neuronal circuitry such as epilepsy.     

Neuromodulatory Control of Neocortical Microcircuits with Activity-Dependent Short-Term Synaptic Depression

A biophysical model of a neocortical microcircuit system is formulated and employed in studies of neuromodulatory control of dynamics and function. The model is based on recent observations of reciprocal connections between pyramidal cells and inhibitory interneurons and incorporates a new type of activity-dependent short-term depression of synaptic couplings recently observed. The model neurons are of a low-dimensional type also accounting for neuronal adaptation, i.e. the coupling between neuronal activity and excitability, which can be regulated by various neuromodulators in the brain. The results obtained demonstrate a capacity for neuromodulatory control of dynamical mode linked to functional mode. The functional aspects considered refer to the observed resolution of multiple objects in working memory as well as the binding of different features for the perception of an object. The effects of neuromodulators displayed by the model are in accordance with many observations on neuromodulatory influence on cognitive functions and brain disorders.     

Complex events initiated by individual spikes in the human cerebral cortex

Synaptic interactions between neurons of the human cerebral cortex were not directly studied to date. We recorded the first dataset, to our knowledge, on the synaptic effect of identified human pyramidal cells on various types of postsynaptic neurons and reveal complex events triggered by individual action potentials in the human neocortical network. Brain slices were prepared from nonpathological samples of cortex that had to be removed for the surgical treatment of brain areas beneath association cortices of 58 patients aged 18 to 73 y. Simultaneous triple and quadruple whole-cell patch clamp recordings were performed testing mono- and polysynaptic potentials in target neurons following a single action potential fired by layer 2/3 pyramidal cells, and the temporal structure of events and underlying mechanisms were analyzed. In addition to monosynaptic postsynaptic potentials, individual action potentials in presynaptic pyramidal cells initiated long-lasting (37 ± 17 ms) sequences of events in the network lasting an order of magnitude longer than detected previously in other species. These event series were composed of specifically alternating glutamatergic and GABAergic postsynaptic potentials and required selective spike-to-spike coupling from pyramidal cells to GABAergic interneurons producing concomitant inhibitory as well as excitatory feed-forward action of GABA. Single action potentials of human neurons are sufficient to recruit Hebbian-like neuronal assemblies that are proposed to participate in cognitive processes.     

Interneurons of the motor region of the neocortex]

Interneurons of motor area in the brain cortex have been studied in cats and monkeys. The greatest attention has been paid to pyramidal interneurons, among which six cell types have been described according to their axonal composition. Unlike stellate interneurons, all types of pyramidal interneurons possess less developed axonal collaterals. Interneuronal contacts are situated on dendrites or cell bodies of middle and large long-axonal pyramids. Functional role of cortical interneurons seems to be different. Some of them are of inhibitory nature (basket cells and, perhaps, other types of long-axonal stellate neurons), others are exciting elements. The latter include short-axonal stellate neurons and, perhaps, pyramidal interneurons. While comparing the cortex in cats and monkeys, it is evident that the neocortex in monkeys, especially its lower layers, is rich in pyramidal interneurons.     

Hippocampal Theta Modulation of Neocortical Spike Times and Gamma Rhythm: A Biophysical Model Study

The hippocampal theta and neocortical gamma rhythms are two prominent examples of oscillatory neuronal activity. The hippocampus has often been hypothesized to influence neocortical networks by its theta rhythm, and, recently, evidence for such a direct influence has been found. We examined a possible mechanism for this influence by means of a biophysical model study using conductance-based model neurons. We found, in agreement with previous studies, that networks of fast-spiking GABA -ergic interneurons, coupled with shunting inhibition, synchronize their spike activity at a gamma frequency and are able to impose this rhythm on a network of pyramidal cells to which they are coupled. When our model was supplied with hippocampal theta-modulated input fibres, the theta rhythm biased the spike timings of both the fast-spiking and pyramidal cells. Furthermore, both the amplitude and frequency of local field potential gamma oscillations were influenced by the phase of the theta rhythm. We show that the fast-spiking cells, not pyramidal cells, are essential for this latter phenomenon, thus highlighting their crucial role in the interplay between hippocampus and neocortex.     

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.     

Enhancement of spike-timing precision by autaptic transmission in neocortical inhibitory interneurons

In vivo studies suggest that precise firing of neurons is important for correct sensory representation. Principal neocortical neurons fire imprecisely when repeatedly activated by fixed sensory stimuli or current depolarizations. Here we show that in contrast to pyramidal neurons, firing in neocortical GABAergic fast-spiking (FS) interneurons is quite precise. FS interneurons are self-innervated by powerful GABAergic autaptic connections reliably activated after each spike, suggesting that autapses strongly regulate FS-cell spike timing. Indeed, blockade of autaptic transmission degraded temporal precision in multiple ways. Under these conditions, realistic dynamic-clamp hyperpolarizing autapses restored precision of spike timing, even in the presence of synaptic noise. Furthermore, firing precision was increased in pyramidal neurons by artificial GABAergic autaptic conductances, suggesting that tightly coupled synaptic feedback inhibition regulates spike timing in principal cells. Thus, well-timed inhibition, whether autaptic or synaptic, facilitates precise spike timing and promotes synchronized cortical network oscillations relevant to several behaviors.     

Topological characterization of neuronal arbor morphology via sequence representation: II - global alignment

Background

The increasing abundance of neuromorphological data provides both the opportunity and the challenge to compare massive numbers of neurons from a wide diversity of sources efficiently and effectively. We implemented a modified global alignment algorithm representing axonal and dendritic bifurcations as strings of characters. Sequence alignment quantifies neuronal similarity by identifying branch-level correspondences between trees.

Results

The space generated from pairwise similarities is capable of classifying neuronal arbor types as well as, or better than, traditional topological metrics. Unsupervised cluster analysis produces groups that significantly correspond with known cell classes for axons, dendrites, and pyramidal apical dendrites. Furthermore, the distinguishing consensus topology generated by multiple sequence alignment of a group of neurons reveals their shared branching blueprint. Interestingly, the axons of dendritic-targeting interneurons in the rodent cortex associates with pyramidal axons but apart from the (more topologically symmetric) axons of perisomatic-targeting interneurons.

Conclusions

Global pairwise and multiple sequence alignment of neurite topologies enables detailed comparison of neurites and identification of conserved topological features in alignment-defined clusters. The methods presented also provide a framework for incorporation of additional branch-level morphological features. Moreover, comparison of multiple alignment with motif analysis shows that the two techniques provide complementary information respectively revealing global and local features.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0605-1) contains supplementary material, which is available to authorized users.     

Dense inhibitory connectivity in neocortex

The connectivity diagram of neocortical circuits is still unknown, and there are conflicting data as to whether cortical neurons are wired specifically or not. To investigate the basic structure of cortical microcircuits, we use a two-photon photostimulation technique that enables the systematic mapping of synaptic connections with single-cell resolution. We map the inhibitory connectivity between upper layers somatostatin-positive GABAergic interneurons and pyramidal cells in mouse frontal cortex. Most, and sometimes all, inhibitory neurons are locally connected to every sampled pyramidal cell. This dense inhibitory connectivity is found at both young and mature developmental ages. Inhibitory innervation of neighboring pyramidal cells is similar, regardless of whether they are connected among themselves or not. We conclude that local inhibitory connectivity is promiscuous, does not form subnetworks, and can approach the theoretical limit of a completely connected synaptic matrix.     

Differential regulation of the excitability of prefrontal cortical fast-spiking interneurons and pyramidal neurons by serotonin and fluoxetine

Serotonin exerts a powerful influence on neuronal excitability. In this study, we investigated the effects of serotonin on different neuronal populations in prefrontal cortex (PFC), a major area controlling emotion and cognition. Using whole-cell recordings in PFC slices, we found that bath application of 5-HT dose-dependently increased the firing of FS (fast spiking) interneurons, and decreased the firing of pyramidal neurons. The enhancing effect of 5-HT in FS interneurons was mediated by 5-HT₂ receptors, while the reducing effect of 5-HT in pyramidal neurons was mediated by 5-HT₁ receptors. Fluoxetine, the selective serotonin reuptake inhibitor, also induced a concentration-dependent increase in the excitability of FS interneurons, but had little effect on pyramidal neurons. In rats with chronic fluoxetine treatment, the excitability of FS interneurons was significantly increased, while pyramidal neurons remained unchanged. Fluoxetine injection largely occluded the enhancing effect of 5-HT in FS interneurons, but did not alter the reducing effect of 5-HT in pyramidal neurons. These data suggest that the excitability of PFC interneurons and pyramidal neurons is regulated by exogenous 5-HT in an opposing manner, and FS interneurons are the major target of Fluoxetine. It provides a framework for understanding the action of 5-HT and antidepressants in altering PFC network activity.     

Opinion: an integrated approach to classifying neuronal phenotypes

Characterizing the functional phenotypes of neurons is essential for understanding how genotypes can be related to the neural basis of behaviour. Traditional classifications of neurons by single features (such as morphology or firing behaviour) are increasingly inadequate for reflecting functional phenotypes, as they do not integrate functions across different neuronal types. Here, we describe a set of rules for identifying and predicting functional phenotypes that combine morphology, intrinsic ion channel species and their distributions in dendrites, and functional properties. This more comprehensive neuronal classification should be an improvement on traditional classifications for relating genotype to functional phenotype.     

Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex

Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.     

Location-dependent effects of inhibition on local spiking in pyramidal neuron dendrites

Cortical computations are critically dependent on interactions between pyramidal neurons (PNs) and a menagerie of inhibitory interneuron types. A key feature distinguishing interneuron types is the spatial distribution of their synaptic contacts onto PNs, but the location-dependent effects of inhibition are mostly unknown, especially under conditions involving active dendritic responses. We studied the effect of somatic vs. dendritic inhibition on local spike generation in basal dendrites of layer 5 PNs both in neocortical slices and in simple and detailed compartmental models, with equivalent results: somatic inhibition divisively suppressed the amplitude of dendritic spikes recorded at the soma while minimally affecting dendritic spike thresholds. In contrast, distal dendritic inhibition raised dendritic spike thresholds while minimally affecting their amplitudes. On-the-path dendritic inhibition modulated both the gain and threshold of dendritic spikes depending on its distance from the spike initiation zone. Our findings suggest that cortical circuits could assign different mixtures of gain vs. threshold inhibition to different neural pathways, and thus tailor their local computations, by managing their relative activation of soma- vs. dendrite-targeting interneurons.     

Close homolog of L1 modulates area-specific neuronal positioning and dendrite orientation in the cerebral cortex

We show that the neural cell recognition molecule Close Homolog of L1 (CHL1) is required for neuronal positioning and dendritic growth of pyramidal neurons in the posterior region of the developing mouse neocortex. CHL1 was expressed in pyramidal neurons in a high-caudal to low-rostral gradient within the developing cortex. Deep layer pyramidal neurons of CHL1-minus mice were shifted to lower laminar positions in the visual and somatosensory cortex and developed misoriented, often inverted apical dendrites. Impaired migration of CHL1-minus cortical neurons was suggested by strikingly slower rates of radial migration in cortical slices, failure to potentiate integrin-dependent haptotactic cell migration in vitro, and accumulation of migratory cells in the intermediate and ventricular/subventricular zones in vivo. The restriction of CHL1 expression and effects of its deletion in posterior neocortical areas suggests that CHL1 may regulate area-specific neuronal connectivity and, by extension, function in the visual and somatosensory cortex.     

Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z‐score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b‐high/CD10‐low/CD221‐high) and a second group clustering close to fibroblasts (CD49b‐low/CD10‐high/CD221‐low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes. J. Cell. Physiol. 225: 601–611, 2010. © 2010 Wiley‐Liss, Inc.