Jacob-induced transcriptional inactivation of CREB promotes Aβ-induced synapse loss in Alzheimer's disease

Synaptic dysfunction caused by soluble β-amyloid peptide (Aβ) is a hallmark of early-stage Alzheimer's disease (AD), and is tightly linked to cognitive decline. By yet unknown mechanisms, Aβ suppresses the transcriptional activity of cAMP-responsive element-binding protein (CREB), a master regulator of cell survival and plasticity-related gene expression. Here, we report that Aβ elicits nucleocytoplasmic trafficking of Jacob, a protein that connects a NMDA-receptor-derived signalosome to CREB, in AD patient brains and mouse hippocampal neurons. Aβ-regulated trafficking of Jacob induces transcriptional inactivation of CREB leading to impairment and loss of synapses in mouse models of AD. The small chemical compound Nitarsone selectively hinders the assembly of a Jacob/LIM-only 4 (LMO4)/ Protein phosphatase 1 (PP1) signalosome and thereby restores CREB transcriptional activity. Nitarsone prevents impairment of synaptic plasticity as well as cognitive decline in mouse models of AD. Collectively, the data suggest targeting Jacob protein-induced CREB shutoff as a therapeutic avenue against early synaptic dysfunction in AD.

Neuronal Cell Types in the Spinal Trigeminal Nucleus of the Camel Brain

Neurons in the spinal trigeminal nucleus of a camel were morphologically studied by the Golgi impregnation method. The neurons were classified based on the size and shape of their cell bodies, the density of their dendritic trees, and the morphology and distribution of their appendages. At least 12 morphological types of neurons were found in the camel spinal trigeminal nucleus, including the following: stalked, islets, octopus-like, lobulated, boat-like, pyramidal, multipolar, round, oval, and elongated neurons. These neurons exhibited large numbers of various forms of appendages that arise not only from their dendrites but also from their cell bodies. Moreover, neurons with unique large dilatations especially at their dendritic branching points were also reported. The neurons reported in this study displayed an array of different sizes and shapes and featured various forms of appendages arising from cell bodies and dendrites. Such morphologically distinctive neuronal cell types might indicate an evolutionary adaptation to pain and temperature processing pathways at the level of the spinal trigeminal nucleus in camels, which traditionally live in a very harsh climatic environment and are frequently exposed to painful stimuli.

Postnatal development of inner lamina II interneurons of the rat medullary dorsal horn

ABSTRACT

Pain processing in young mammals is immature. Despite the central role of the medullary dorsal horn (MDH) in processing orofacial sensory information, the maturation of the neurons within the MDH has been largely overlooked. Combining in vitro electrophysiological recordings and 3D morphological analysis over the first postnatal month in rats, we investigated the age-dependent development of the neurons within the inner lamina II (IIi) of the MDH. We show the lamina IIi neuronal population transition into a more hyperpolarized state, with modification of the action potential waveform, and a shift from single spiking, at early postnatal ages, to tonic firing and initial bursting at later stages. These physiological changes are associated with a strong structural remodelling of the neuronal morphology with most of the modifications occurring after the third postnatal week. Among the lamina IIi neuronal population, the subpopulation of interneurons expressing the γ isoform of the protein kinase C (PKCγ+) are key elements for the circuits underlying facial mechanical allodynia. How do they develop from the rest of the lamina IIi constitute an important question that remained to be addressed. Here, we show that PKCγ+ interneurons display electrophysiological changes over time comparable with the PKCγ- population. However, they show a distinctive increase of the soma volume and primary branches length, as opposed to the PKCγ- population. Together, our data demonstrate a novel pattern of late postnatal maturation of lamina IIi interneurons, with a spotlight on PKCγ+ interneurons, that may be relevant for the development of orofacial sensitivity.

Layer-Specific Inhibitory Microcircuits of Layer 6 Interneurons in Rat Prefrontal Cortex

GABAergic interneurons in different cortical areas play important roles in diverse higher-order cognitive functions. The heterogeneity of interneurons is well characterized in different sensory cortices, in particular in primary somatosensory and visual cortex. However, the structural and functional properties of the medial prefrontal cortex (mPFC) interneurons have received less attention. In this study, a cluster analysis based on axonal projection patterns revealed four distinct clusters of L6 interneurons in rat mPFC: Cluster 1 interneurons showed axonal projections similar to Martinotti-like cells extending to layer 1, cluster 2 displayed translaminar projections mostly to layer 5, and cluster 3 interneuron axons were confined to the layer 6, whereas those of cluster 4 interneurons extend also into the white matter. Correlations were found between neuron location and axonal distribution in all clusters. Moreover, all cluster 1 L6 interneurons showed a monotonically adapting firing pattern with an initial high-frequency burst. All cluster 2 interneurons were fast-spiking, while neurons in cluster 3 and 4 showed heterogeneous firing patterns. Our data suggest that L6 interneurons that have distinct morphological and physiological characteristics are likely to innervate different targets in mPFC and thus play differential roles in the L6 microcircuitry and in mPFC-associated functions.

Axonal Tree Morphology and Signal Propagation Dynamics Improve Interneuron Classification

Neurons are diverse and can be differentiated by their morphological, electrophysiological, and molecular properties. Current morphology-based classification approaches largely rely on the dendritic tree structure or on the overall axonal projection layout. Here, we use data from public databases of neuronal reconstructions and membrane properties to study the characteristics of the axonal and dendritic trees for interneuron classification. We show that combining signal propagation patterns observed by biophysical simulations of the activity along ramified axonal trees with morphological parameters of the axonal and dendritic trees, significantly improve classification results compared to previous approaches. The classification schemes introduced here can be utilized for robust neuronal classification. Our work paves the way for understanding and utilizing form-function principles in realistic neuronal reconstructions.

Anatomical Correlates of Local, Translaminar, and Transcolumnar Inhibition by Layer 6 GABAergic Interneurons in Somatosensory Cortex

In the vibrissal area of rodent somatosensory cortex, information on whisker stimulation is processed by neuronal networks in a corresponding cortical column. To understand how sensory stimuli are represented in a column, it is essential to identify cell types constituting these networks. Layer 6 (L6) comprises 25% of all neurons in a column. In rats, 430 of these are inhibitory interneurons (INs). Little is known about the axon projection of L6 INs with reference to columnar and laminar organization. We quantified axonal projections of L6 INs (n = 68) with reference to columns and layers in somatosensory cortex of rats. We found distinct projection types differentially targeting layers of a cortical column. The majority of L6 INs did not show a column-specific innervation, densely projecting to neighboring columns as well as the home column. However, a small fraction targeted granular and supragranular layers, where axon projections were confined to the home column. We also quantified putative innervation of pyramidal cells as a functional correlate of axonal distribution. Electrophysiological properties were not correlated to axon projection. The quantitative data on axonal projections and electrophysiological properties of L6 INs can guide future studies investigating cortical processing of sensory information at the single cell level.

Morphological and Functional Characterization of Non-fast-Spiking GABAergic Interneurons in Layer 4 Microcircuitry of Rat Barrel Cortex

GABAergic interneurons are notorious for their heterogeneity, despite constituting a small fraction of the neuronal population in the neocortex. Classification of interneurons is crucial for understanding their widespread cortical functions as they provide a complex and dynamic network, balancing excitation and inhibition. Here, we investigated different types of non-fast-spiking (nFS) interneurons in Layer 4 (L4) of rat barrel cortex using whole-cell patch-clamp recordings with biocytin-filling. Based on a quantitative analysis on a combination of morphological and electrophysiological parameters, we identified 5 distinct types of L4 nFS interneurons: 1) trans-columnar projecting interneurons, 2) locally projecting non-Martinotti-like interneurons, 3) supra-granular projecting Martinotti-like interneurons, 4) intra-columnar projecting VIP-like interneurons, and 5) locally projecting neurogliaform-like interneurons. Trans-columnar projecting interneurons are one of the most striking interneuron types, which have not been described so far in Layer 4. They feature extensive axonal collateralization not only in their home barrel but also in adjacent barrels. Furthermore, we identified that most of the L4 nFS interneurons express somatostatin, while few are positive for the transcription factor Prox1. The morphological and electrophysiological characterization of different L4 nFS interneuron types presented here provides insights into their synaptic connectivity and functional role in cortical information processing.

Cortical Circuits of Callosal GABAergic Neurons

Anatomical studies have shown that the majority of callosal axons are glutamatergic. However, a small proportion of callosal axons are also immunoreactive for glutamic acid decarboxylase, an enzyme required for gamma-aminobutyric acid (GABA) synthesis and a specific marker for GABAergic neurons. Here, we test the hypothesis that corticocortical parvalbumin-expressing (CC-Parv) neurons connect the two hemispheres of multiple cortical areas, project through the corpus callosum, and are a functional part of the local cortical circuit. Our investigation of this hypothesis takes advantage of viral tracing and optogenetics to determine the anatomical and electrophysiological properties of CC-Parv neurons of the mouse auditory, visual, and motor cortices. We found a direct inhibitory pathway made up of parvalbumin-expressing (Parv) neurons which connects corresponding cortical areas (CC-Parv neurons → contralateral cortex). Like other Parv cortical neurons, these neurons provide local inhibition onto nearby pyramidal neurons and receive thalamocortical input. These results demonstrate a previously unknown long-range inhibitory circuit arising from a genetically defined type of GABAergic neuron that is engaged in interhemispheric communication.

Local oxygen homeostasis during various neuronal network activity states in the mouse hippocampus

Cortical information processing comprises various activity states emerging from timed synaptic excitation and inhibition. However, the underlying energy metabolism is widely unknown. We determined the cerebral metabolic rate of oxygen (CMRO2) along a tissue depth of <0.3 mm in the hippocampal CA3 region during various network activities, including gamma oscillations and sharp wave-ripples that occur during wakefulness and sleep. These physiological states associate with sensory perception and memory formation, and critically depend on perisomatic GABA inhibition. Moreover, we modelled vascular oxygen delivery based on quantitative microvasculature analysis. (1) Local CMRO2 was highest during gamma oscillations (3.4 mM/min), medium during sharp wave-ripples, asynchronous activity and isoflurane application (2.0-1.6 mM/min), and lowest during tetrodotoxin application (1.4 mM/min). (2) Energy expenditure of axonal and synaptic signaling accounted for >50% during gamma oscillations. (3) CMRO2 positively correlated with number and synchronisation of activated synapses, and neural multi-unit activity. (4) The median capillary distance was 44 µm. (5) The vascular oxygen partial pressure of 33 mmHg was needed to sustain oxidative phosphorylation during gamma oscillations. We conclude that gamma oscillations featuring high energetics require a hemodynamic response to match oxygen consumption of respiring mitochondria, and that perisomatic inhibition significantly contributes to the brain energy budget.

Towards a supervised classification of neocortical interneuron morphologies

BACKGROUND

The challenge of classifying cortical interneurons is yet to be solved. Data-driven classification into established morphological types may provide insight and practical value.

RESULTS

We trained models using 217 high-quality morphologies of rat somatosensory neocortex interneurons reconstructed by a single laboratory and pre-classified into eight types. We quantified 103 axonal and dendritic morphometrics, including novel ones that capture features such as arbor orientation, extent in layer one, and dendritic polarity. We trained a one-versus-rest classifier for each type, combining well-known supervised classification algorithms with feature selection and over- and under-sampling. We accurately classified the nest basket, Martinotti, and basket cell types with the Martinotti model outperforming 39 out of 42 leading neuroscientists. We had moderate accuracy for the double bouquet, small and large basket types, and limited accuracy for the chandelier and bitufted types. We characterized the types with interpretable models or with up to ten morphometrics.

CONCLUSION

Except for large basket, 50 high-quality reconstructions sufficed to learn an accurate model of a type. Improving these models may require quantifying complex arborization patterns and finding correlates of bouton-related features. Our study brings attention to practical aspects important for neuron classification and is readily reproducible, with all code and data available online.

Mining Big Neuron Morphological Data

The advent of automatic tracing and reconstruction technology has led to a surge in the number of neurons 3D reconstruction data and consequently the neuromorphology research. However, the lack of machine-driven annotation schema to automatically detect the types of the neurons based on their morphology still hinders the development of this branch of science. Neuromorphology is important because of the interplay between the shape and functionality of neurons and the far-reaching impact on the diagnostics and therapeutics in neurological disorders. This survey paper provides a comprehensive research in the field of automatic neurons classification and presents the existing challenges, methods, tools, and future directions for automatic neuromorphology analytics. We summarize the major automatic techniques applicable in the field and propose a systematic data processing pipeline for automatic neuron classification, covering data capturing, preprocessing, analyzing, classification, and retrieval. Various techniques and algorithms in machine learning are illustrated and compared to the same dataset to facilitate ongoing research in the field.

Secretagogin is Expressed by Developing Neocortical GABAergic Neurons in Humans but not Mice and Increases Neurite Arbor Size and Complexity

The neocortex of primates, including humans, contains more abundant and diverse inhibitory neurons compared with rodents, but the molecular foundations of these observations are unknown. Through integrative gene coexpression analysis, we determined a consensus transcriptional profile of GABAergic neurons in mid-gestation human neocortex. By comparing this profile to genes expressed in GABAergic neurons purified from neonatal mouse neocortex, we identified conserved and distinct aspects of gene expression in these cells between the species. We show here that the calcium-binding protein secretagogin (SCGN) is robustly expressed by neocortical GABAergic neurons derived from caudal ganglionic eminences (CGE) and lateral ganglionic eminences during human but not mouse brain development. Through electrophysiological and morphometric analyses, we examined the effects of SCGN expression on GABAergic neuron function and form. Forced expression of SCGN in CGE-derived mouse GABAergic neurons significantly increased total neurite length and arbor complexity following transplantation into mouse neocortex, revealing a molecular pathway that contributes to morphological differences in these cells between rodents and primates.

Layer 5 Callosal Parvalbumin-Expressing Neurons: A Distinct Functional Group of GABAergic Neurons

Previous studies have shown that parvalbumin-expressing neurons (CC-Parv neurons) connect the two hemispheres of motor and sensory areas via the corpus callosum, and are a functional part of the cortical circuit. Here we test the hypothesis that layer 5 CC-Parv neurons possess anatomical and molecular mechanisms which dampen excitability and modulate the gating of interhemispheric inhibition. In order to investigate this hypothesis we use viral tracing to determine the anatomical and electrophysiological properties of layer 5 CC-Parv and parvalbumin-expressing (Parv) neurons of the mouse auditory cortex (AC). Here we show that layer 5 CC-Parv neurons had larger dendritic fields characterized by longer dendrites that branched farther from the soma, whereas layer 5 Parv neurons had smaller dendritic fields characterized by shorter dendrites that branched nearer to the soma. The layer 5 CC-Parv neurons are characterized by delayed action potential (AP) responses to threshold currents, lower firing rates, and lower instantaneous frequencies compared to the layer 5 Parv neurons. Kv1.1 containing K⁺ channels are the main source of the AP repolarization of the layer 5 CC-Parv and have a major role in determining both the spike delayed response, firing rate and instantaneous frequency of these neurons.

Inhibitory interneurons and their circuit motifs in the many layers of the barrel cortex

Recent years have seen substantial progress in studying the structural and functional properties of GABAergic interneurons and their roles in the neuronal networks of barrel cortex. Although GABAergic interneurons represent only about 12% of the total number of neocortical neurons, they are extremely diverse with respect to their structural and functional properties. It has become clear that barrel cortex interneurons not only serve the maintenance of an appropriate excitation/inhibition balance but also are directly involved in sensory processing. In this review we present different interneuron types and their axonal projection pattern framework in the context of the laminar and columnar organization of the barrel cortex. The main focus is here on the most prominent interneuron types, i.e. basket cells, chandelier cells, Martinotti cells, bipolar/bitufted cells and neurogliaform cells, but interneurons with more unusual axonal domains will also be mentioned. We describe their developmental origin, their classification with respect to molecular, morphological and intrinsic membrane and synaptic properties. Most importantly, we will highlight the most prominent circuit motifs these interneurons are involved in and in which way they serve feed-forward inhibition, feedback inhibition and disinhibition. Finally, this will be put into context to their functional roles in sensory signal perception and processing in the whisker system and beyond.

Morphological Neuron Classification Using Machine Learning

Classification and quantitative characterization of neuronal morphologies from histological neuronal reconstruction is challenging since it is still unclear how to delineate a neuronal cell class and which are the best features to define them by. The morphological neuron characterization represents a primary source to address anatomical comparisons, morphometric analysis of cells, or brain modeling. The objectives of this paper are (i) to develop and integrate a pipeline that goes from morphological feature extraction to classification and (ii) to assess and compare the accuracy of machine learning algorithms to classify neuron morphologies. The algorithms were trained on 430 digitally reconstructed neurons subjectively classified into layers and/or m-types using young and/or adult development state population of the somatosensory cortex in rats. For supervised algorithms, linear discriminant analysis provided better classification results in comparison with others. For unsupervised algorithms, the affinity propagation and the Ward algorithms provided slightly better results.

Inhibitory Circuits in Cortical Layer 5

Inhibitory neurons play a fundamental role in cortical computation and behavior. Recent technological advances, such as two photon imaging, targeted in vivo recording, and molecular profiling, have improved our understanding of the function and diversity of cortical interneurons, but for technical reasons most work has been directed towards inhibitory neurons in the superficial cortical layers. Here we review current knowledge specifically on layer 5 (L5) inhibitory microcircuits, which play a critical role in controlling cortical output. We focus on recent work from the well-studied rodent barrel cortex, but also draw on evidence from studies in primary visual cortex and other cortical areas. The diversity of both deep inhibitory neurons and their pyramidal cell targets make this a challenging but essential area of study in cortical computation and sensory processing.

Turtle Dorsal Cortex Pyramidal Neurons Comprise Two Distinct Cell Types with Indistinguishable Visual Responses

A detailed inventory of the constituent pieces in cerebral cortex is considered essential to understand the principles underlying cortical signal processing. Specifically, the search for pyramidal neuron subtypes is partly motivated by the hypothesis that a subtype-specific division of labor could create a rich substrate for computation. On the other hand, the extreme integration of individual neurons into the collective cortical circuit promotes the hypothesis that cellular individuality represents a smaller computational role within the context of the larger network. These competing hypotheses raise the important question to what extent the computational function of a neuron is determined by its individual type or by its circuit connections. We created electrophysiological profiles from pyramidal neurons within the sole cellular layer of turtle visual cortex by measuring responses to current injection using whole-cell recordings. A blind clustering algorithm applied to these data revealed the presence of two principle types of pyramidal neurons. Brief diffuse light flashes triggered membrane potential fluctuations in those same cortical neurons. The apparently network driven variability of the visual responses concealed the existence of subtypes. In conclusion, our results support the notion that the importance of diverse intrinsic physiological properties is minimized when neurons are embedded in a synaptic recurrent network.

A barrel-related interneuron in layer 4 of rat somatosensory cortex with a high intrabarrel connectivity

Synaptic connections between identified fast-spiking (FS), parvalbumin (PV)-positive interneurons, and excitatory spiny neurons in layer 4 (L4) of the barrel cortex were investigated using patch-clamp recordings and simultaneous biocytin fillings. Three distinct clusters of FS L4 interneurons were identified based on their axonal morphology relative to the barrel column suggesting that these neurons do not constitute a homogeneous interneuron population. One L4 FS interneuron type had an axonal domain strictly confined to a L4 barrel and was therefore named "barrel-confined inhibitory interneuron" (BIn). BIns established reliable inhibitory synaptic connections with L4 spiny neurons at a high connectivity rate of 67%, of which 69% were reciprocal. Unitary IPSPs at these connections had a mean amplitude of 0.9 ± 0.8 mV with little amplitude variation and weak short-term synaptic depression. We found on average 3.7 ± 1.3 putative inhibitory synaptic contacts that were not restricted to perisomatic areas. In conclusion, we characterized a novel type of barrel cortex interneuron in the major thalamo-recipient layer 4 forming dense synaptic networks with L4 spiny neurons. These networks constitute an efficient and powerful inhibitory feedback system, which may serve to rapidly reset the barrel microcircuitry following sensory activation.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists' classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

Novel 3D microscopic analysis of human placental villous trees reveals unexpected significance of branching angles

The villous trees of human placentas delineate the fetomaternal border and are complex three-dimensional (3D) structures. Thus far, they have primarily been analyzed as thin, two-dimensional (2D) histological sections. However, 2D sections cannot provide access to key aspects such as branching nodes and branch order. Using samples taken from 50 normal human placentas at birth, in the present study we show that analysis procedures for 3D reconstruction of neuronal dendritic trees can also be used for analyzing trees of human placentas. Nodes and their branches (e.g., branching hierarchy, branching angles, diameters, and lengths of branches) can be efficiently measured in whole-mount preparations of isolated villous trees using high-end light microscopy. Such data differ qualitatively from the data obtainable from histological sections and go substantially beyond the morphological horizon of such histological data. Unexpectedly, branching angles of terminal branches of villous trees varied inversely with the fetoplacental weight ratio, a widely used clinical parameter. Since branching angles have never before been determined in the human placenta, this result requires further detailed studies in order to fully understand its impact.

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

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

Balance between the proximal dendritic compartment and the soma determines spontaneous firing rate in midbrain dopamine neurons

Midbrain dopamine (DA) neurons are slow intrinsic pacemakers that require the elaborate composition of many ion channels in the somatodendritic compartments. Understanding the major determinants of the spontaneous firing rate (SFR) of midbrain DA neurons is important because they determine the basal DA levels in target areas, including the striatum. As spontaneous firing occurs synchronously at the soma and dendrites, the electrical coupling between the soma and dendritic compartments has been regarded as a key determinant for the SFR. However, it is not known whether this somatodendritic coupling is served by the whole dendritic compartments or only parts of them. In the rat substantia nigra pars compacta (SNc) DA neurons, we demonstrate that the balance between the proximal dendritic compartment and the soma determines the SFR. Isolated SNc DA neurons showed a wide range of soma size and a variable number of primary dendrites but preserved a quite consistent SFR. The SFR was not correlated with soma size or with the number of primary dendrites, but it was strongly correlated with the area ratios of the proximal dendritic compartments to the somatic compartment. Tetrodotoxin puff and local Ca(2+) perturbation experiments, computer simulation, and local glutamate uncaging experiments suggest the importance of the proximal dendritic compartments in pacemaker activity. These data indicate that the proximal dendritic compartments, not the whole dendritic compartments, play a key role in the somatodendritic balance that determines the SFR in DA neurons.

Using diffusion anisotropy to characterize neuronal morphology in gray matter: the orientation distribution of axons and dendrites in the NeuroMorpho.org database

Accurate mathematical modeling is integral to the ability to interpret diffusion magnetic resonance (MR) imaging data in terms of cellular structure in brain gray matter (GM). In previous work, we derived expressions to facilitate the determination of the orientation distribution of axonal and dendritic processes from diffusion MR data. Here we utilize neuron reconstructions available in the NeuroMorpho database (www.neuromorpho.org) to assess the validity of the model we proposed by comparing morphological properties of the neurons to predictions based on diffusion MR simulations using the reconstructed neuron models. Initially, the method for directly determining neurite orientation distributions is shown to not depend on the line length used to quantify cylindrical elements. Further variability in neuron morphology is characterized relative to neuron type, species, and laboratory of origin. Subsequently, diffusion MR signals are simulated based on human neocortical neuron reconstructions. This reveals a bias in which diffusion MR data predict neuron orientation distributions to have artificially low anisotropy. This bias is shown to arise from shortcomings (already at relatively low diffusion weighting) in the Gaussian approximation of diffusion, in the presence of restrictive barriers, and data analysis methods involving higher moments of the cumulant expansion are shown to be capable of reducing the magnitude of the observed bias.

Beyond the frontiers of neuronal types

Cortical neurons and, particularly, inhibitory interneurons display a large diversity of morphological, synaptic, electrophysiological, and molecular properties, as well as diverse embryonic origins. Various authors have proposed alternative classification schemes that rely on the concomitant observation of several multimodal features. However, a broad variability is generally observed even among cells that are grouped into a same class. Furthermore, the attribution of specific neurons to a single defined class is often difficult, because individual properties vary in a highly graded fashion, suggestive of continua of features between types. Going beyond the description of representative traits of distinct classes, we focus here on the analysis of atypical cells. We introduce a novel paradigm for neuronal type classification, assuming explicitly the existence of a structured continuum of diversity. Our approach, grounded on the theory of fuzzy sets, identifies a small optimal number of model archetypes. At the same time, it quantifies the degree of similarity between these archetypes and each considered neuron. This allows highlighting archetypal cells, which bear a clear similarity to a single model archetype, and edge cells, which manifest a convergence of traits from multiple archetypes.

Digital morphometry of rat cerebellar climbing fibers reveals distinct branch and bouton types

Cerebellar climbing fibers (CFs) provide powerful excitatory input to Purkinje cells (PCs), which represent the sole output of the cerebellar cortex. Recent discoveries suggest that CFs have information-rich signaling properties important for cerebellar function, beyond eliciting the well known all-or-none PC complex spike. CF morphology has not been quantitatively analyzed at the same level of detail as its biophysical properties. Because morphology can greatly influence function, including the capacity for information processing, it is important to understand CF branching structure in detail, as well as its variability across and within arbors. We have digitally reconstructed 68 rat CFs labeled using biotinylated dextran amine injected into the inferior olive and comprehensively quantified their morphology. CF structure was considerably diverse even within the same anatomical regions. Distinctly identifiable primary, tendril, and distal branches could be operationally differentiated by the relative size of the subtrees at their initial bifurcations. Additionally, primary branches were more directed toward the cortical surface and had fewer and less pronounced synaptic boutons, suggesting they prioritize efficient and reliable signal propagation. Tendril and distal branches were spatially segregated and bouton dense, indicating specialization in signal transmission. Furthermore, CFs systematically targeted molecular layer interneuron cell bodies, especially at terminal boutons, potentially instantiating feedforward inhibition on PCs. This study offers the most detailed and comprehensive characterization of CF morphology to date. The reconstruction files and metadata are publicly distributed at NeuroMorpho.org.

3D reconstruction and standardization of the rat vibrissal cortex for precise registration of single neuron morphology

The three-dimensional (3D) structure of neural circuits is commonly studied by reconstructing individual or small groups of neurons in separate preparations. Investigation of structural organization principles or quantification of dendritic and axonal innervation thus requires integration of many reconstructed morphologies into a common reference frame. Here we present a standardized 3D model of the rat vibrissal cortex and introduce an automated registration tool that allows for precise placement of single neuron reconstructions. We (1) developed an automated image processing pipeline to reconstruct 3D anatomical landmarks, i.e., the barrels in Layer 4, the pia and white matter surfaces and the blood vessel pattern from high-resolution images, (2) quantified these landmarks in 12 different rats, (3) generated an average 3D model of the vibrissal cortex and (4) used rigid transformations and stepwise linear scaling to register 94 neuron morphologies, reconstructed from in vivo stainings, to the standardized cortex model. We find that anatomical landmarks vary substantially across the vibrissal cortex within an individual rat. In contrast, the 3D layout of the entire vibrissal cortex remains remarkably preserved across animals. This allows for precise registration of individual neuron reconstructions with approximately 30 µm accuracy. Our approach could be used to reconstruct and standardize other anatomically defined brain areas and may ultimately lead to a precise digital reference atlas of the rat brain.

Emergence in the central nervous system

"Emergence" is an idea that has received much attention in consciousness literature, but it is difficult to find characterizations of that concept which are both specific and useful. I will precisely define and characterize a type of epistemic ("weak") emergence and show that it is a property of some neural circuits throughout the CNS, on micro-, meso- and macroscopic levels. I will argue that possession of this property can result in profoundly altered neural dynamics on multiple levels in cortex and other systems. I will first describe emergent neural entities (ENEs) abstractly. I will then show how ENEs function specifically and concretely, and demonstrate some implications of this type of emergence for the CNS.

A hierarchical structure of cortical interneuron electrical diversity revealed by automated statistical analysis

Although the diversity of cortical interneuron electrical properties is well recognized, the number of distinct electrical types (e-types) is still a matter of debate. Recently, descriptions of interneuron variability were standardized by multiple laboratories on the basis of a subjective classification scheme as set out by the Petilla convention (Petilla Interneuron Nomenclature Group, PING). Here, we present a quantitative, statistical analysis of a database of nearly five hundred neurons manually annotated according to the PING nomenclature. For each cell, 38 features were extracted from responses to suprathreshold current stimuli and statistically analyzed to examine whether cortical interneurons subdivide into e-types. We showed that the partitioning into different e-types is indeed the major component of data variability. The analysis suggests refining the PING e-type classification to be hierarchical, whereby most variability is first captured within a coarse subpartition, and then subsequently divided into finer subpartitions. The coarse partition matches the well-known partitioning of interneurons into fast spiking and adapting cells. Finer subpartitions match the burst, continuous, and delayed subtypes. Additionally, our analysis enabled the ranking of features according to their ability to differentiate among e-types. We showed that our quantitative e-type assignment is more than 90% accurate and manages to catch several human errors.

Morphology and physiology of excitatory neurons in layer 6b of the somatosensory rat barrel cortex

Neocortical lamina 6B (L6B) is a largely unexplored layer with a very heterogeneous cellular composition. To date, only little is known about L6B neurons on a systematic and quantitative basis. We investigated the morphological and electrophysiological properties of excitatory L6B neurons in the rat somatosensory barrel cortex using whole-cell patch-clamp recordings and simultaneous biocytin fillings. Subsequent histological processing and computer-assisted 3D reconstructions provided the basis for a classification of excitatory L6B neurons according to their structural and functional characteristics. Three distinct clusters of excitatory L6B neurons were identified: (C1) pyramidal neurons with an apical dendrite pointing towards the pial surface, (C2) neurons with a prominent, “apical”-like dendrite not oriented towards the pia, and (C3) multipolar spiny neurons without any preferential dendritic orientation. The second group could be further subdivided into three categories termed inverted, “tangentially” oriented and “horizontally” oriented neurons. Furthermore, based on the axonal domain two subcategories of L6B pyramidal cells were identified that had either a more barrel-column confined or an extended axonal field. The classification of excitatory L6B neurons provided here may serve as a basis for future studies on the structure, function, and synaptic connectivity of L6B neurons.

Comparison between supervised and unsupervised classifications of neuronal cell types: a case study

In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 71–82, 2011

Three-dimensional axon morphologies of individual layer 5 neurons indicate cell type-specific intracortical pathways for whisker motion and touch

The cortical output layer 5 contains two excitatory cell types, slender- and thick-tufted neurons. In rat vibrissal cortex, slender-tufted neurons carry motion and phase information during active whisking, but remain inactive after passive whisker touch. In contrast, thick-tufted neurons reliably increase spiking preferably after passive touch. By reconstructing the 3D patterns of intracortical axon projections from individual slender- and thick-tufted neurons, filled in vivo with biocytin, we were able to identify cell type-specific intracortical circuits that may encode whisker motion and touch. Individual slender-tufted neurons showed elaborate and dense innervation of supragranular layers of large portions of the vibrissal area (total length, 86.8 ± 5.5 mm). During active whisking, these long-range projections may modulate and phase-lock the membrane potential of dendrites in layers 2 and 3 to the whisking cycle. Thick-tufted neurons with soma locations intermingling with those of slender-tufted ones display less dense intracortical axon projections (total length, 31.6 ± 14.3 mm) that are primarily confined to infragranular layers. Based on anatomical reconstructions and previous measurements of spiking, we put forward the hypothesis that thick-tufted neurons in rat vibrissal cortex receive input of whisker motion from slender-tufted neurons onto their apical tuft dendrites and input of whisker touch from thalamic neurons onto their basal dendrites. During tactile-driven behavior, such as object location, near-coincident input from these two pathways may result in increased spiking activity of thick-tufted neurons and thus enhanced signaling to their subcortical targets.

Increased excitability of cortical neurons induced by associative learning: an ex vivo study

In adult mice, classical conditioning in which whisker stimulation is paired with an electric shock to the tail results in a decrease in the frequency of head movements, induces expansion of the cortical representation of stimulated vibrissae and enhances inhibitory synaptic interactions within the 'trained' barrels. We investigated whether such a simple associative learning paradigm also induced changes in neuronal excitability. Using whole-cell recordings from ex vivo slices of the barrel cortex we found that layer IV excitatory cells located in the cortical representation of the 'trained' row of vibrissae had a higher frequency of spikes recorded at threshold potential than neurons from the 'untrained' row and than cells from control animals. Additionally, excitatory cells within the 'trained' barrels were characterized by increased gain of the input-output function, lower amplitudes of fast after-hyperpolarization and decreased effect of blocking of BK channels by iberiotoxin. These findings provide new insight into the possible mechanism for enhanced intrinsic excitability of layer IV excitatory neurons. In contrast, the fast spiking inhibitory cells recorded in the same barrels did not change their intrinsic excitability after the conditioning procedure. The increased excitability of excitatory neurons within the 'trained' barrels may represent the counterpart of homeostatic plasticity, which parallels enhanced synaptic inhibition described previously. Together, the two mechanisms would contribute to increase the input selectivity within the conditioned cortical network.

Quantitative classification of somatostatin-positive neocortical interneurons identifies three interneuron subtypes

Deciphering the circuitry of the neocortex requires knowledge of its components, making a systematic classification of neocortical neurons necessary. GABAergic interneurons contribute most of the morphological, electrophysiological and molecular diversity of the cortex, yet interneuron subtypes are still not well defined. To quantitatively identify classes of interneurons, 59 GFP-positive interneurons from a somatostatin-positive mouse line were characterized by whole-cell recordings and anatomical reconstructions. For each neuron, we measured a series of physiological and morphological variables and analyzed these data using unsupervised classification methods. PCA and cluster analysis of morphological variables revealed three groups of cells: one comprised of Martinotti cells, and two other groups of interneurons with short asymmetric axons targeting layers 2/3 and bending medially. PCA and cluster analysis of electrophysiological variables also revealed the existence of these three groups of neurons, particularly with respect to action potential time course. These different morphological and electrophysiological characteristics could make each of these three interneuron subtypes particularly suited for a different function within the cortical circuit.

Distinctive classes of GABAergic interneurons provide layer-specific phasic inhibition in the anterior piriform cortex

The primary olfactory (or piriform) cortex is a trilaminar paleocortex that is seen increasingly as an attractive model system for the study of cortical sensory processing. Recent findings highlight the importance of γ-amino butyric acid (GABA)-releasing interneurons for the function of the piriform cortex (PC), yet little is known about the different types of interneurons in the PC. Here, we provide the first detailed functional characterization of the major classes of GABAergic interneurons in the anterior piriform cortex (aPC) and show how these classes differentially engage in phasic synaptic inhibition. By measuring the electrical properties of interneurons and combining this with information about their morphology, laminar location, and expression of molecular markers, we have identified 5 major classes in the aPC of the mouse. Each layer contains at least one class of interneuron that is tuned to fire either earlier or later in a train of stimuli resembling the input received by the PC in vivo during olfaction. This suggests that the different subtypes of interneuron are specialized for providing synaptic inhibition at different phases of the sniff cycle. Thus, our results suggest mechanisms by which classes of interneurons play specific roles in the processing performed by the PC in order to recognize odors.

Grouping and classifying electrophysiologically-defined classes of neocortical neurons by single cell, whole-genome expression profiling

The diversity of neuronal cell types and how to classify them are perennial questions in neuroscience. The advent of global gene expression analysis raised the possibility that comprehensive transcription profiling will resolve neuronal cell types into groups that reflect some or all aspects of their phenotype. This approach has been successfully used to compare gene expression between groups of neurons defined by a common property. Here we extend this approach to ask whether single neuron gene expression profiling can prospectively resolve neuronal subtypes into groups, independent of any phenotypic information, and whether those groups reflect meaningful biological properties of those neurons. We applied methods we have developed to compare gene expression among single neural stem cells to study global gene expression in 18 randomly picked neurons from layer II/III of the early postnatal mouse neocortex. Cells were selected by morphology and by firing characteristics and electrical properties, enabling the definition of each cell as either fast- or regular-spiking, corresponding to a class of inhibitory interneurons or excitatory pyramidal cells. Unsupervised clustering of young neurons by global gene expression resolved the cells into two groups and those broadly corresponded with the two groups of fast- and regular-spiking neurons. Clustering of the entire, diverse group of 18 neurons of different developmental stages also successfully grouped neurons in accordance with the electrophysiological phenotypes, but with more cells misassigned among groups. Genes specifically enriched in regular spiking neurons were identified from the young neuron expression dataset. These results provide a proof of principle that single-cell gene expression profiling may be used to group and classify neurons in a manner reflecting their known biological properties and may be used to identify cell-specific transcripts.

Serotonin 3A receptor subtype as an early and protracted marker of cortical interneuron subpopulations

To identify neocortical neurons expressing the type 3 serotonergic receptor, here we used transgenic mice expressing the enhanced green fluorescent protein (GFP) under the control of the 5-HT_3A promoter (5-HT_3A:GFP mice). By means of whole-cell patch-clamp recordings, biocytin labeling, and single-cell reversed-transcriptase polymerase chain reaction on acute brain slices of 5-HT_3A:GFP mice, we identified 2 populations of 5-HT_3A-expressing interneurons within the somatosensory cortex. The first population was characterized by the frequent expression of the vasoactive intestinal peptide and a typical bipolar/bitufted morphology, whereas the second population expressed predominantly the neuropeptide Y and exhibited more complex dendritic arborizations. Most interneurons of this second group appeared very similar to neurogliaform cells according to their electrophysiological, molecular, and morphological properties. The combination of 5-bromo-2-deoxyuridine injections with 5-HT_3A mRNA detection showed that cortical 5-HT_3A interneurons are generated around embryonic day 14.5. Although at this stage the 5-HT_3A receptor subunit is expressed in both the caudal ganglionic eminence and the entopeduncular area, homochronic in utero grafts experiments revealed that cortical 5-HT_3A interneurons are mainly generated in the caudal ganglionic eminence. This protracted expression of the 5-HT_3A subunit allowed us to study specific cortical interneuron populations from their birth to their final functional phenotype.

Classification of NPY-expressing neocortical interneurons

Neuropeptide Y (NPY) is an abundant neuropeptide of the neocortex involved in numerous physiological and pathological processes. Because of the large electrophysiological, molecular, and morphological diversity of NPY-expressing neurons their precise identity remains unclear. To define distinct populations of NPY neurons we characterized, in acute slices of rat barrel cortex, 200 cortical neurons of layers I-IV by means of whole-cell patch-clamp recordings, biocytin labeling, and single-cell reverse transcriptase-PCR designed to probe for the expression of well established molecular markers for cortical neurons. To classify reliably cortical NPY neurons, we used and compared different unsupervised clustering algorithms based on laminar location and electrophysiological and molecular properties. These classification schemes confirmed that NPY neurons are nearly exclusively GABAergic and consistently disclosed three main types of NPY-expressing interneurons. (1) Neurogliaform-like neurons exhibiting a dense axonal arbor, were the most frequent and superficial, and substantially expressed the neuronal isoform of nitric oxide synthase. (2) Martinotti-like cells characterized by an ascending axon ramifying in layer I coexpressed somatostatin and were the most excitable type. (3) Among fast-spiking and parvalbumin-positive basket cells, NPY expression was correlated with pronounced spike latency. By clarifying the diversity of cortical NPY neurons, this study establishes a basis for future investigations aiming at elucidating their physiological roles.

Efficient recruitment of layer 2/3 interneurons by layer 4 input in single columns of rat somatosensory cortex

Interneurons in layers 2/3 are excited by pyramidal cells within the same layer (Reyes et al., 1998; Gupta et al., 2000), but little is known about translaminar innervation of these interneurons by spiny neurons in the main cortical input layer 4 (L4). Here, we investigated (1) how efficiently L4 spiny neurons excite L2/3 interneurons via monosynaptic connections, (2) whether glutamate release from axon terminals of L4 spiny neurons depends on the identity of the postsynaptic interneuron, and (3) how L4-to-L2/3 interneuron connections compare with L4-to-L2/3 pyramidal neuron connections. We recorded from pairs of L4 spiny neurons and L2/3 interneurons in acute slices of rat barrel cortex of postnatal day 20 (P20) to P29 rats. The L4-to-L2/3 interneuron connections had an average unitary EPSP of 1.2 +/- 1.1 mV. We found an average of 2.3 +/- 0.8 contacts per connection, and the L4-to-L2/3 interneuron innervation domains were mostly column restricted. Unitary EPSP amplitudes and paired-pulse ratios in the L4-to-L2/3 interneuron connections depended on the "group" of the postsynaptic interneuron. Averaged over all L4-to-L2/3 interneuron connections, unitary EPSP amplitudes were 1.8-fold higher than in the translaminar L4-to-L2/3 pyramidal cell connections. Our results suggest that L4 spiny neurons may more efficiently recruit L2/3 interneurons than L2/3 pyramidal neurons, and that glutamate release from translaminar boutons of L4 spiny neuron axons is target cell specific.