Dendritic Size of Pyramidal Neurons Differs among Mouse Cortical Regions

Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy

Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain.

Single-neuron analysis of dendrites and axons reveals the network organization in mouse prefrontal cortex

The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here we report the complete dendrite and axon morphology of nearly 2,000 neurons in mouse prefrontal cortex (PFC). We identified morphological variations of somata, dendrites and axons across laminar layers and PFC subregions and the general rules of somatodendritic scaling with cytoarchitecture. We uncovered 24 morphologically distinguishable dendrite subtypes in 1,515 pyramidal projection neurons and 405 atypical pyramidal projection neurons and spiny stellate neurons with unique axon projection patterns. Furthermore, correspondence analysis among dendrites, local axons and long-range axons revealed coherent morphological changes associated with electrophysiological phenotypes. Finally, integrative dendrite-axon analysis uncovered the organization of potential intra-column, inter-hemispheric and inter-column connectivity among projection neuron types in PFC. Together, our study provides a comprehensive structural repertoire for the reconstruction and analysis of PFC neural network.

Topological Sholl descriptors for neuronal clustering and classification

Neuronal morphology is a fundamental factor influencing information processing within neurons and networks. Dendritic morphology in particular can widely vary among cell classes, brain regions, and animal species. Thus, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. Current robust and unbiased computational methods that characterize groups of neurons are scarce. In this work, we introduce a novel technique to study dendritic morphology, complementing and advancing many of the existing techniques. Our approach is to conceptualize the notion of a Sholl descriptor and associate, for each morphological feature, and to each neuron, a function of the radial distance from the soma, taking values in a metric space. Functional distances give rise to pseudo-metrics on sets of neurons which are then used to perform the two distinct tasks of clustering and classification. To illustrate the use of Sholl descriptors, four datasets were retrieved from the large public repository https://neuromorpho.org/ comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional morphometric techniques (L-Measure metrics) in several of the tested datasets. Therefore, we offer a novel and effective approach to the analysis of diverse neuronal cell types, and provide a toolkit for researchers to cluster and classify neurons.

Single-Neuron Labeling in Fixed Tissue and Targeted Volume Electron Microscopy

The structural complexity of nervous tissue makes it very difficult to unravel the connectivity between neural elements at different scales. Numerous methods are available to trace long-range projections at the light microscopic level, and to identify the actual synaptic connections at the electron microscopic level. However, correlating mesoscopic and nanoscopic scales in the same cell, cell population or brain region is a problematic, laborious and technically demanding task. Here we present an effective method for the 3D reconstruction of labeled subcellular structures at the ultrastructural level, after single-neuron labeling in fixed tissue. The brain is fixed by intracardial perfusion of aldehydes and thick vibratome sections (250 μm) are obtained. Single cells in these vibratome sections are intracellularly injected with horseradish peroxidase (HRP), so that the cell body and its processes can be identified. The thick sections are later flat-embedded in epoxy resin and re-sectioned into a series of thinner (7 μm) sections. The sections containing the regions of interest of the labeled cells are then imaged with automated focused ion beam milling and scanning electron microscopy (FIB-SEM), acquiring long series of high-resolution images that can be reconstructed, visualized, and analyzed in 3D. With this methodology, we can accurately select any cellular segment at the light microscopic level (e.g., proximal, intermediate or distal dendrites, collateral branches, axonal segments, etc.) and analyze its synaptic connections at the electron microscopic level, along with other ultrastructural features. Thus, this method not only facilitates the mapping of the synaptic connectivity of single-labeled neurons, but also the analysis of the surrounding neuropil. Since the labeled processes can be located at different layers or subregions, this method can also be used to obtain data on the differences in local synaptic organization that may exist at different portions of the labeled neurons.

Microanatomical study of pyramidal neurons in the contralesional somatosensory cortex after experimental ischemic stroke

At present, many studies support the notion that after stroke, remote regions connected to the infarcted area are also affected and may contribute to functional outcome. In the present study, we have analyzed possible microanatomical alterations in pyramidal neurons from the contralesional hemisphere after induced stroke. We performed intracellular injections of Lucifer yellow in pyramidal neurons from layer III in the somatosensory cortex of the contralesional hemisphere in an ischemic stroke mouse model. A detailed 3-dimensional analysis of the neuronal complexity and morphological alterations of dendritic spines was then performed. Our results demonstrate that pyramidal neurons from layer III in the somatosensory cortex of the contralesional hemisphere show selective changes in their dendritic arbors, namely, less dendritic complexity of the apical dendritic arbor-but no changes in the basal dendritic arbor. In addition, we found differences in spine morphology in both apical and basal dendrites comparing the contralesional hemisphere with the lesional hemisphere. Our results show that pyramidal neurons of remote areas connected to the infarct zone exhibit a series of selective changes in neuronal complexity and morphological distribution of dendritic spines, supporting the hypothesis that remote regions connected to the peri-infarcted area are also affected after stroke.

Dendritic Architecture Predicts in vivo Firing Pattern in Mouse Ventral Tegmental Area and Substantia Nigra Dopaminergic Neurons

The firing activity of ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) dopaminergic (DA) neurons is an important factor in shaping DA release and its role in motivated behavior. Dendrites in DA neurons are the main postsynaptic compartment and, along with cell body and axon initial segment, contribute to action potential generation and firing pattern. In this study, the organization of the dendritic domain in individual VTA and SNc DA neurons of adult male mice, and their relationship to in vivo spontaneous firing, are described. In comparison with dorsal VTA DA neurons, ventrally located VTA neurons (as measured by cell body location) possess a shorter total dendritic length and simpler dendritic architecture, and exhibit the most irregular in vivo firing patterns among DA neurons. In contrast, for DA neurons in the SNc, the higher irregularity of firing was related to a smaller dendritic domain, as measured by convex hull volumes. However, firing properties were also related to the specific regional distribution of the dendritic tree. Thus, VTA DA neurons with a larger extension of their dendritic tree within the parabrachial pigmented (PBP) nucleus fired more regularly compared with those with relatively more dendrites extending outside the PBP. For DA neurons in the SNc, enhanced firing irregularity was associated with a smaller proportion of dendrites penetrating the substantia nigra pars reticulata. These results suggest that differences in dendritic morphology contribute to the in vivo firing properties of individual DA neurons, and that the existence of region-specific synaptic connectivity rules that shape firing diversity.

α-Synuclein-induced dysregulation of neuronal activity contributes to murine dopamine neuron vulnerability

Pathophysiological damages and loss of function of dopamine neurons precede their demise and contribute to the early phases of Parkinson's disease. The presence of aberrant intracellular pathological inclusions of the protein α-synuclein within ventral midbrain dopaminergic neurons is one of the cardinal features of Parkinson's disease. We employed molecular biology, electrophysiology, and live-cell imaging to investigate how excessive α-synuclein expression alters multiple characteristics of dopaminergic neuronal dynamics and dopamine transmission in cultured dopamine neurons conditionally expressing GCaMP6f. We found that overexpression of α-synuclein in mouse (male and female) dopaminergic neurons altered neuronal firing properties, calcium dynamics, dopamine release, protein expression, and morphology. Moreover, prolonged exposure to the D2 receptor agonist, quinpirole, rescues many of the alterations induced by α-synuclein overexpression. These studies demonstrate that α-synuclein dysregulation of neuronal activity contributes to the vulnerability of dopaminergic neurons and that modulation of D2 receptor activity can ameliorate the pathophysiology. These findings provide mechanistic insights into the insidious changes in dopaminergic neuronal activity and neuronal loss that characterize Parkinson's disease progression with significant therapeutic implications.

Differential Structure of Hippocampal CA1 Pyramidal Neurons in the Human and Mouse

Pyramidal neurons are the most common cell type and are considered the main output neuron in most mammalian forebrain structures. In terms of function, differences in the structure of the dendrites of these neurons appear to be crucial in determining how neurons integrate information. To further shed light on the structure of the human pyramidal neurons we investigated the geometry of pyramidal cells in the human and mouse CA1 region-one of the most evolutionary conserved archicortical regions, which is critically involved in the formation, consolidation, and retrieval of memory. We aimed to assess to what extent neurons corresponding to a homologous region in different species have parallel morphologies. Over 100 intracellularly injected and 3D-reconstructed cells across both species revealed that dendritic and axonal morphologies of human cells are not only larger but also have structural differences, when compared to mouse. The results show that human CA1 pyramidal cells are not a stretched version of mouse CA1 cells. These results indicate that there are some morphological parameters of the pyramidal cells that are conserved, whereas others are species-specific.

Wiring of higher-order cortical areas: Spatiotemporal development of cortical hierarchy

A hierarchical development of cortical areas was suggested over a century ago, but the diversity and complexity of cortical hierarchy properties have so far prevented a formal demonstration. The aim of this review is to clarify the similarities and differences in the developmental processes underlying cortical development of primary and higher-order areas. We start by recapitulating the historical and recent advances underlying the biological principle of cortical hierarchy in adults. We then revisit the arguments for a hierarchical maturation of cortical areas, and further integrate the principles of cortical areas specification during embryonic and postnatal development. We highlight how the dramatic expansion in cortical size might have contributed to the increased number of association areas sustaining cognitive complexification in evolution. Finally, we summarize the recent observations of an alteration of cortical hierarchy in neuropsychiatric disorders and discuss their potential developmental origins.

A Closer Look to the Evolution of Neurons in Humans and Apes Using Stem-Cell-Derived Model Systems

The cellular, molecular and functional comparison of neurons from closely related species is crucial in evolutionary neurobiology. The access to living tissue and post-mortem brains of humans and non-human primates is limited and the state of the tissue might not allow recapitulating important species-specific differences. A valid alternative is offered by neurons derived from induced pluripotent stem cells (iPSCs) obtained from humans and non-human apes and primates. We will review herein the contribution of iPSCs-derived neuronal models to the field of evolutionary neurobiology, focusing on species-specific aspects of neuron’s cell biology and timing of maturation. In addition, we will discuss the use of iPSCs for the study of ancient human traits.

Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks

Pyramidal neurons are the most common neurons in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. We compared human temporal cortex and mouse visual cortex pyramidal neurons from the Allen Cell Types Database in terms of their electrophysiology and dendritic morphology. We found that, among other differences, human pyramidal neurons had a higher action potential threshold voltage, a lower input resistance, and larger dendritic arbors. We learned Gaussian Bayesian networks from the data in order to identify correlations and conditional independencies between the variables and compare them between the species. We found strong correlations between electrophysiological and morphological variables in both species. In human cells, electrophysiological variables were correlated even with morphological variables that are not directly related to dendritic arbor size or diameter, such as mean bifurcation angle and mean branch tortuosity. Cortical depth was correlated with both electrophysiological and morphological variables in both species, and its effect on electrophysiology could not be explained in terms of the morphological variables. For some variables, the effect of cortical depth was opposite in the two species. Overall, the correlations among the variables differed strikingly between human and mouse neurons. Besides identifying correlations and conditional independencies, the learned Bayesian networks might be useful for probabilistic reasoning regarding the morphology and electrophysiology of pyramidal neurons.

A community-based transcriptomics classification and nomenclature of neocortical cell types

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Atypical Neocortical Development in the Cited2 Conditional Knockout Leads to Behavioral Deficits Associated with Neurodevelopmental Disorders

The mammalian neocortex develops from a single layer of neuroepithelial cells to form a six-layer heterogeneous mosaic of differentiated neurons and glial cells. This process requires a complex choreography of temporally and spatially restricted transcription factors and epigenetic regulators. Even subtle disruptions in this regulation can alter the way the neocortex forms and functions, leading to a neurodevelopmental disorder. One epigenetic regulator that is essential for the precise development of the neocortex is CITED2 (CBP/p300 Interacting Transactivator with ED-rich termini). Cited2 is highly expressed by intermediate progenitor cells in the subventricular zone during the generation of the superficial layers of the neocortex. A forebrain-specific conditional knockout of Cited2 (cKO) exhibits reduced proliferation of intermediate progenitor cells embryonically, leading to reduced thickness of the superficial layers and reduced corpus callosum (CC) volume postnatally. Further, the Cited2 cKO display disruptions in balanced neocortical arealization, with a specific reduction in the somatosensory neocortical length, and dysregulation of precise, area-specific neuronal connectivity. Here, we explore the behavioral consequences resulting from this aberrant neocortical development. We demonstrate that Cited2 cKO mice display decreased maternal separation-induced ultrasonic vocalizations (USVs) as neonates, and an increase in rearing behavior and lack of habituation following repeated acoustic startle as adults. They do not display alterations in anxiety-like behavior, overall locomotor activity, or social interactions. Together with the morphological, molecular, and connectivity disruptions, these results identify the Cited2 cKO neocortex as an ideal system to study mechanisms underlying neurodevelopmental and neuroanatomical disruptions with relevance to human neurodevelopmental disorders.

Comparing basal dendrite branches in human and mouse hippocampal CA1 pyramidal neurons with Bayesian networks

Pyramidal neurons are the most common cell type in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. A recent study provided a unique set of human and mouse pyramidal neurons of the CA1 region of the hippocampus, and used it to compare the morphology of apical and basal dendritic branches of the two species. The study found inter-species differences in the magnitude of the morphometrics and similarities regarding their variation with respect to morphological determinants such as branch type and branch order. We use the same data set to perform additional comparisons of basal dendrites. In order to isolate the heterogeneity due to intrinsic differences between species from the heterogeneity due to differences in morphological determinants, we fit multivariate models over the morphometrics and the determinants. In particular, we use conditional linear Gaussian Bayesian networks, which provide a concise graphical representation of the independencies and correlations among the variables. We also extend the previous study by considering additional morphometrics and by formally testing whether a morphometric increases or decreases with the distance from the soma. This study introduces a multivariate methodology for inter-species comparison of morphology.

Measurements of neuronal morphological variation across the rat neocortex

Neuron morphology is highly variable across the mammalian brain. It is thought that these attributes of neuronal cell shape, such as soma surface area and branching frequency, are determined by biological function and information processing. In this study, a large data set of neurons across the rat neocortex were clustered by their anatomical characters for evidence of distinctiveness among neocortical regions and the somatosensory layers. This data set of neuronal morphologies was compiled from 31 different lab sources with a validation procedure so that data records are potentially comparable across research studies. With this large set of heterogeneous data and by clustering analysis, this study shows that neuronal morphological traits overlap among neocortical and somatosensory regions. In the context of past neuroanatomical studies, this result is not congruent with tissue level analysis and strongly suggests further sampling of neuronal data to lessen the effect of confounding factors, such as the influence of different methodologies from use of heterogeneous samples of neuronal data.

Effect of Phosphorylated Tau on Cortical Pyramidal Neuron Morphology during Hibernation

The dendritic spines of pyramidal cells are the main postsynaptic target of excitatory glutamatergic synapses. Morphological alterations have been described in hippocampal dendritic spines during hibernation-a state of inactivity and metabolic depression that occurs via a transient neuronal tau hyperphosphorylation. Here, we have used the hibernating Syrian hamster to investigate the effect of hyperphosphorylated tau regarding neocortical neuronal structure. In particular, we examined layer Va pyramidal neurons. Our results indicate that hibernation does not promote significant changes in dendritic spine density. However, tau hyperphosphorylated neurons show a decrease in complexity, an increase in the tortuosity of the apical dendrites, and an increase in the diameter of the basal dendrites. Tau protein hyperphosphorylation and aggregation have been associated with loss or alterations of dendritic spines in neurodegenerative diseases, such as Alzheimer's disease (AD). Our results may shed light on the correlation between tau hyperphosphorylation and the neuropathological processes in AD. Moreover, we observed changes in the length and area of the apical and basal dendritic spines during hibernation regardless of tau hyperphosphorylation. The morphological changes observed here also suggest region specificity, opening up debate about a possible relationship with the differential brain activity registered in these regions in previous studies.

Spatial control of membrane traffic in neuronal dendrites

Neuronal dendrites are highly branched and specialized compartments with distinct structures and secretory organelles (e.g., spines, Golgi outposts), and a unique cytoskeletal organization that includes microtubules of mixed polarity. Dendritic membranes are enriched with proteins, which specialize in the formation and function of the post-synaptic membrane of the neuronal synapse. How these proteins partition preferentially in dendrites, and how they traffic in a manner that is spatiotemporally accurate and regulated by synaptic activity are long-standing questions of neuronal cell biology. Recent studies have shed new insights into the spatial control of dendritic membrane traffic, revealing new classes of proteins (e.g., septins) and cytoskeleton-based mechanisms with dendrite-specific functions. Here, we review these advances by revisiting the fundamental mechanisms that control membrane traffic at the levels of protein sorting and motor-driven transport on microtubules and actin filaments. Overall, dendrites possess unique mechanisms for the spatial control of membrane traffic, which might have specialized and co-evolved with their highly arborized morphology.

NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity

Neuron shape and connectivity affect function. Modern imaging methods have proven successful at extracting morphological information. One potential path to achieve analysis of this morphology is through graph theory. Encoding by graphs enables the use of high throughput informatic methods to extract and infer brain function. However, the application of graph-theoretic methods to neuronal morphology comes with certain challenges in term of complex subgraph matching and the difficulty in computing intermediate shapes in between two imaged temporal samples. Here we report a novel, efficacious graph-theoretic method that rises to the challenges. The morphology of a neuron, which consists of its overall size, global shape, local branch patterns, and cell-specific biophysical properties, can vary significantly with the cell's identity, location, as well as developmental and physiological state. Various algorithms have been developed to customize shape based statistical and graph related features for quantitative analysis of neuromorphology, followed by the classification of neuron cell types using the features. Unlike the classical feature extraction based methods from imaged or 3D reconstructed neurons, we propose a model based on the rooted path decomposition from the soma to the dendrites of a neuron and extract morphological features from each constituent path. We hypothesize that measuring the distance between two neurons can be realized by minimizing the cost of continuously morphing the set of all rooted paths of one neuron to another. To validate this claim, we first establish the correspondence of paths between two neurons using a modified Munkres algorithm. Next, an elastic deformation framework that employs the square root velocity function is established to perform the continuous morphing, which, as an added benefit, provides an effective visualization tool. We experimentally show the efficacy of NeuroPath2Path, NeuroP2P, over the state of the art.

Regional Specialization of Pyramidal Neuron Morphology and Physiology in the Tree Shrew Neocortex

The mammalian cerebral cortex is divided into different areas according to their function and pattern of connections. Studies comparing primary visual (V1) and prefrontal cortex (PFC) of primates have demonstrated striking pyramidal neuron (PN) specialization not present in comparable areas of the mouse neocortex. To better understand PFC evolution and regional PN specialization, we studied the tree shrew, a species with a close phylogenetic relationship to primates. We defined the tree shrew PFC based on cytoarchitectonic borders, thalamic connectivity and characterized the morphology and electrophysiology of layer II/III PNs in V1 and PFC. Similar to primates, the PFC PNs in the tree shrew fire with a regular spiking pattern and have larger dendritic tree and spines than those in V1. However, V1 PNs showed strikingly large basal dendritic arbors with high spine density, firing at higher rates and in a more varied pattern than PFC PNs. Yet, unlike in the mouse and unreported in the primate, medial prefrontal PN are more easily recruited than either the dorsolateral or V1 neurons. This specialization of PN morphology and physiology is likely to be a significant factor in the evolution of cortex, contributing to differences in the computational capacities of individual cortical areas.

Neuronal Morphology and Synapse Count in the Nematode Worm

The somatic nervous system of the nematode worm Caenorhabditis elegans is a model for understanding the physical characteristics of the neurons and their interconnections. Its neurons show high variation in morphological attributes. This study investigates the relationship of neuronal morphology to the number of synapses per neuron. Morphology is also examined for any detectable association with neuron cell type or ganglion membership.

Quantifying How Staining Methods Bias Measurements of Neuron Morphologies

The process through which neurons are labeled is a key methodological choice in measuring neuron morphology. However, little is known about how this choice may bias measurements. To quantify this bias we compare the extracted morphology of neurons collected from the same rodent species, experimental condition, gender distribution, age distribution, brain region and putative cell type, but obtained with 19 distinct staining methods. We found strong biases on measured features of morphology. These were largest in features related to the coverage of the dendritic tree (e.g., the total dendritic tree length). Understanding measurement biases is crucial for interpreting morphological data.

Multimodal gradients across mouse cortex

The primate cerebral cortex displays a hierarchy that extends from primary sensorimotor to association areas, supporting increasingly integrated function underpinned by a gradient of heterogeneity in the brain's microcircuits. The extent to which these hierarchical gradients are unique to primate or may reflect a conserved mammalian principle of brain organization remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1-weighted:T2-weighted (T1w:T2w) magnetic resonance imaging map as a common spatial reference for comparison across species, we report interspecies agreement in a range of large-scale cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex, as well as notable interspecies differences. Our results support the view of systematic structural variation across cortical areas as a core organizational principle that may underlie hierarchical specialization in mammalian brains.

Scanless volumetric imaging by selective access multifocal multiphoton microscopy

Simultaneous, high-resolution imaging across a large number of synaptic and dendritic sites is critical for understanding how neurons receive and integrate signals. Yet, functional imaging that targets a large number of submicrometer-sized synaptic and dendritic locations poses significant technical challenges. We demonstrate a new parallelized approach to address such questions, increasing the signal-to-noise ratio by an order of magnitude compared to previous approaches. This selective access multifocal multiphoton microscopy uses a spatial light modulator to generate multifocal excitation in three dimensions (3D) and a Gaussian-Laguerre phase plate to simultaneously detect fluorescence from these spots throughout the volume. We test the performance of this system by simultaneously recording Ca2+ dynamics from cultured neurons at 98-118 locations distributed throughout a 3D volume. This is the first demonstration of 3D imaging in a "single shot" and permits synchronized monitoring of signal propagation across multiple different dendrites.

Cross-Regional Gradient of Dendritic Morphology in Isochronically-Sourced Mouse Supragranular Pyramidal Neurons

Architectonic heterogeneity in neurons is thought to be important for equipping the mammalian cerebral cortex with an adaptable network that can organize the manifold totality of information it receives. To this end, the dendritic arbors of supragranular pyramidal neurons, even those of the same class, are known to vary substantially. This diversity of dendritic morphology appears to have a rostrocaudal configuration in some brain regions of various species. For example, in humans and non-human primates, neurons in more rostral visual association areas (e.g., V4) tend to have more complex dendritic arbors than those in the caudal primary visual cortex. A rostrocaudal configuration is not so clear in any region of the mouse, which is increasingly being used as a model for neurodevelopmental disorders that arise from dysfunctional cerebral cortical circuits. Therefore, in this study we investigated the complexity of dendritic arbors of neurons distributed throughout a broad area of the mouse cerebral cortex. We reduced selection bias by labeling neurons restricted to become supragranular pyramidal neurons using in utero electroporation. While we observed that the simple rostrocaudal position, cortical depth, or even functional region of a neuron was not directly related to its dendritic morphology, a model that instead included a caudomedial-to-rostrolateral gradient accounted for a significant amount of the observed dendritic morphological variance. In other words, rostrolateral neurons from our data set were generally more complex when compared to caudomedial neurons. Furthermore, dividing the cortex into a visual area and a non-visual area maintained the power of the relationship between caudomedial-to-rostrolateral position and dendritic complexity. Our observations therefore support the idea that dendritic morphology of mouse supragranular excitatory pyramidal neurons across much of the tangential plane of the cerebral cortex is partly shaped by a developmental gradient spanning several functional regions.

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

While PTEN-induced kinase 1 (PINK1) is well characterized for its role in mitochondrial homeostasis, much less is known concerning its ability to prevent synaptodendritic degeneration. Using unbiased proteomic methods, we identified valosin-containing protein (VCP) as a major PINK1-interacting protein. RNAi studies demonstrate that both VCP and its cofactor NSFL1C/p47 are necessary for the ability of PINK1 to increase dendritic complexity. Moreover, PINK1 regulates phosphorylation of p47, but not the VCP co-factor UFD1. Although neither VCP nor p47 interact directly with PKA, we found that PINK1 binds and phosphorylates the catalytic subunit of PKA at T197 [PKAcat(pT197)], a site known to activate the PKA holoenzyme. PKA in turn phosphorylates p47 at a novel site (S176) to regulate dendritic complexity. Given that PINK1 physically interacts with both the PKA holoenzyme and the VCP-p47 complex to promote dendritic arborization, we propose that PINK1 scaffolds a novel PINK1-VCP-PKA-p47 signaling pathway to orchestrate dendritogenesis in neurons. These findings highlight an important mechanism by which proteins genetically implicated in Parkinson's disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.

A Segmentation Scheme for Complex Neuronal Arbors and Application to Vibration Sensitive Neurons in the Honeybee Brain

The morphology of a neuron is strongly related to its physiological properties, application of logical product and thus to information processing functions. Optical microscope images are widely used for extracting the structure of neurons. Although several approaches have been proposed to trace and extract complex neuronal structures from microscopy images, available methods remain prone to errors. In this study, we present a practical scheme for processing confocal microscope images and reconstructing neuronal structures. We evaluated this scheme using image data samples and associated “gold standard” reconstructions from the BigNeuron Project. In these samples, dendritic arbors belonging to multiple projection branches of the same neuron overlapped in space, making it difficult to automatically and accurately trace their structural connectivity. Our proposed scheme, which combines several software tools for image masking and filtering with an existing tool for dendritic segmentation and tracing, outperformed state-of-the-art automatic methods in reconstructing such neuron structures. For evaluating our scheme, we applied it to a honeybee local interneuron, DL-Int-1, which has complex arbors and is considered to be a critical neuron for encoding the distance information indicated in the waggle dance of the honeybee.

Parallel Development of Chromatin Patterns, Neuron Morphology, and Connections: Potential for Disruption in Autism

The phenotype of neurons and their connections depend on complex genetic and epigenetic processes that regulate the expression of genes in the nucleus during development and throughout life. Here we examined the distribution of nuclear chromatin patters in relation to the epigenetic landscape, phenotype and connections of neurons with a focus on the primate cerebral cortex. We show that nuclear patterns of chromatin in cortical neurons are related to neuron size and cortical connections. Moreover, we point to evidence that reveals an orderly sequence of events during development, linking chromatin and gene expression patterns, neuron morphology, function, and connections across cortical areas and layers. Based on this synthesis, we posit that systematic studies of changes in chromatin patterns and epigenetic marks across cortical areas will provide novel insights on the development and evolution of cortical networks, and their disruption in connectivity disorders of developmental origin, like autism. Achieving this requires embedding and interpreting genetic, transcriptional, and epigenetic studies within a framework that takes into consideration distinct types of neurons, local circuit interactions, and interareal pathways. These features vary systematically across cortical areas in parallel with laminar structure and are differentially affected in disorders. Finally, based on evidence that autism-associated genetic polymorphisms are especially prominent in excitatory neurons and connectivity disruption affects mostly limbic cortices, we employ this systematic approach to propose novel, targeted studies of projection neurons in limbic areas to elucidate the emergence and time-course of developmental disruptions in autism.

Neural stem cell differentiation into mature neurons: Mechanisms of regulation and biotechnological applications

The abilities of stem cells to self-renew and form different mature cells expand the possibilities of applications in cell-based therapies such as tissue recomposition in regenerative medicine, drug screening, and treatment of neurodegenerative diseases. In addition to stem cells found in the embryo, various adult organs and tissues have niches of stem cells in an undifferentiated state. In the central nervous system of adult mammals, neurogenesis occurs in two regions: the subventricular zone and the dentate gyrus in the hippocampus. The generation of the different neural lines originates in adult neural stem cells that can self-renew or differentiate into astrocytes, oligodendrocytes, or neurons in response to specific stimuli. The regulation of the fate of neural stem cells is a finely controlled process relying on a complex regulatory network that extends from the epigenetic to the translational level and involves extracellular matrix components. Thus, a better understanding of the mechanisms underlying how the process of neurogenesis is induced, regulated, and maintained will provide elues for development of novel for strategies for neurodegenerative therapies. In this review, we focus on describing the mechanisms underlying the regulation of the neuronal differentiation process by transcription factors, microRNAs, and extracellular matrix components.

Caveolin1 Identifies a Specific Subpopulation of Cerebral Cortex Callosal Projection Neurons (CPN) Including Dual Projecting Cortical Callosal/Frontal Projection Neurons (CPN/FPN)

The neocortex is composed of many distinct subtypes of neurons that must form precise subtype-specific connections to enable the cortex to perform complex functions. Callosal projection neurons (CPN) are the broad population of commissural neurons that connect the cerebral hemispheres via the corpus callosum (CC). Currently, how the remarkable diversity of CPN subtypes and connectivity is specified, and how they differentiate to form highly precise and specific circuits, are largely unknown. We identify in mouse that the lipid-bound scaffolding domain protein Caveolin 1 (CAV1) is specifically expressed by a unique subpopulation of Layer V CPN that maintain dual ipsilateral frontal projections to premotor cortex. CAV1 is expressed by over 80% of these dual projecting callosal/frontal projection neurons (CPN/FPN), with expression peaking early postnatally as axonal and dendritic targets are being reached and refined. CAV1 is localized to the soma and dendrites of CPN/FPN, a unique population of neurons that shares information both between hemispheres and with premotor cortex, suggesting function during postmitotic development and refinement of these neurons, rather than in their specification. Consistent with this, we find that Cav1 function is not necessary for the early specification of CPN/FPN, or for projecting to their dual axonal targets. CPN subtype-specific expression of Cav1 identifies and characterizes a first molecular component that distinguishes this functionally unique projection neuron population, a population that expands in primates, and is prototypical of additional dual and higher-order projection neuron subtypes.

A Laminar Organization for Selective Cortico-Cortical Communication

The neocortex is central to mammalian cognitive ability, playing critical roles in sensory perception, motor skills and executive function. This thin, layered structure comprises distinct, functionally specialized areas that communicate with each other through the axons of pyramidal neurons. For the hundreds of such cortico-cortical pathways to underlie diverse functions, their cellular and synaptic architectures must differ so that they result in distinct computations at the target projection neurons. In what ways do these pathways differ? By originating and terminating in different laminae, and by selectively targeting specific populations of excitatory and inhibitory neurons, these “interareal” pathways can differentially control the timing and strength of synaptic inputs onto individual neurons, resulting in layer-specific computations. Due to the rapid development in transgenic techniques, the mouse has emerged as a powerful mammalian model for understanding the rules by which cortical circuits organize and function. Here we review our understanding of how cortical lamination constrains long-range communication in the mammalian brain, with an emphasis on the mouse visual cortical network. We discuss the laminar architecture underlying interareal communication, the role of neocortical layers in organizing the balance of excitatory and inhibitory actions, and highlight the structure and function of layer 1 in mouse visual cortex.

Basal tree complexity shapes functional pathways in the prefrontal cortex

While the morphology of basal dendritic trees in cortical pyramidal neurons varies, the functional implications of this diversity are just starting to emerge. In layer 5 pyramidal neurons of the prefrontal cortex, for example, increased basal tree complexity determines the recruitment of these neurons into functional circuits. Here, we use a modeling approach to investigate whether and how the morphology of the basal tree mediates the functional output of neurons. We implemented 57 basal tree morphologies of layer 5 prefrontal pyramidal neurons of the rat and identified morphological types that were characterized by different response features, forming distinct functional types. These types were robust to a wide range of manipulations (distribution of active ionic mechanisms, NMDA conductance, somatic and apical tree morphology, or the number of activated synapses) and supported different temporal coding schemes at both the single neuron and the microcircuit level. We predict that the basal tree morphological diversity among neurons of the same class mediates their segregation into distinct functional pathways. Extension of our approach/findings to other cortical areas and/or layers or under pathological conditions may provide a generalized role of the basal trees for neuronal function.NEW & NOTEWORTHY Our results suggest that the segregation of neurons to different functional types based on their basal tree morphology is in large part independent of the distribution of active ionic mechanisms, NMDA conductance, somatic and apical tree morphology, and the number of activated synapses; different functional types support distinct temporal coding schemes. This can be exploited to create networks with diverse coding characteristics, thus contributing to the functional heterogeneity within the same layer and area.

Cited2 Regulates Neocortical Layer II/III Generation and Somatosensory Callosal Projection Neuron Development and Connectivity

The neocortex contains hundreds to thousands of distinct subtypes of precisely connected neurons, allowing it to perform remarkably complex tasks of high-level cognition. Callosal projection neurons (CPN) connect the cerebral hemispheres via the corpus callosum, integrating cortical information and playing key roles in associative cognition. CPN are a strikingly diverse set of neuronal subpopulations, and development of this diversity requires precise control by a complex, interactive set of molecular effectors. We have found that the transcriptional coregulator Cited2 regulates and refines two stages of CPN development. Cited2 is expressed broadly by progenitors in the embryonic day 15.5 subventricular zone, during the peak of superficial layer CPN birth, with a progressive postmitotic refinement in expression, becoming restricted to CPN of the somatosensory cortex postnatally. We generated progenitor-stage and postmitotic forebrain-specific Cited2 conditional knock-out mice, using the Emx1-Cre and NEX-Cre mouse lines, respectively. We demonstrate that Cited2 functions in progenitors, but is not necessary postmitotically, to regulate both (1) broad generation of layer II/III CPN and (2) acquisition of precise area-specific molecular identity and axonal/dendritic connectivity of somatosensory CPN. This novel CPN subtype-specific and area-specific control from progenitor action of Cited2 adds yet another layer of complexity to the multistage developmental regulation of neocortical development.

SIGNIFICANCE STATEMENT

This study identifies Cited2 as a novel subtype-specific and area-specific control over development of distinct subpopulations within the broad population of callosal projection neurons (CPN), whose axons connect the two cerebral hemispheres via the corpus callosum (CC). Currently, how the remarkable diversity of CPN subtypes is specified, and how they differentiate to form highly precise and specific circuits, are largely unknown. We found that Cited2 functions within subventricular zone progenitors to both broadly regulate generation of superficial layer CPN throughout the neocortex, and to refine precise area-specific development and connectivity of somatosensory CPN. Gaining insight into molecular development and heterogeneity of CPN will advance understanding of both diverse functions of CPN and of the remarkable range of neurodevelopmental deficits correlated with CPN/CC development.

Modulating STDP Balance Impacts the Dendritic Mosaic

The ability for cortical neurons to adapt their input/output characteristics and information processing capabilities ultimately relies on the interplay between synaptic plasticity, synapse location, and the nonlinear properties of the dendrite. Collectively, they shape both the strengths and spatial arrangements of convergent afferent inputs to neuronal dendrites. Recent experimental and theoretical studies support a clustered plasticity model, a view that synaptic plasticity promotes the formation of clusters or hotspots of synapses sharing similar properties. We have previously shown that spike timing-dependent plasticity (STDP) can lead to synaptic efficacies being arranged into spatially segregated clusters. This effectively partitions the dendritic tree into a tessellated imprint which we have called a dendritic mosaic. Here, using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and STDP learning, we investigated the impact of altered STDP balance on forming such a spatial organization. We show that cluster formation and extend depend on several factors, including the balance between potentiation and depression, the afferents' mean firing rate and crucially on the dendritic morphology. We find that STDP balance has an important role to play for this emergent mode of spatial organization since any imbalances lead to severe degradation- and in some case even destruction- of the mosaic. Our model suggests that, over a broad range of of STDP parameters, synaptic plasticity shapes the spatial arrangement of synapses, favoring the formation of clustered efficacy engrams.

Area-Specific Features of Pyramidal Neurons-a Comparative Study in Mouse and Rhesus Monkey

A principal challenge of systems neuroscience is to understand the unique characteristics of cortical neurons and circuits that enable area- and species-specific sensory encoding, motor function, cognition, and behavior. To address this issue, we compared properties of layer 3 pyramidal neurons in 2 cortical areas that span a broad range of cortical function-primary sensory (V1), to cognitive (frontal)-in the mouse and the rhesus monkey. Hierarchical clustering and discriminant analyses of 15 physiological and 25 morphological variables revealed 2 fundamental principles. First, V1 and frontal neurons are remarkably similar with regard to nearly every property in the mouse, while the opposite is true in the monkey, with V1 and frontal neurons exhibiting significant differences in nearly every property assessed. Second, neurons within visual and frontal areas differ significantly between the mouse and the monkey. Neurons in mouse and monkey V1 are the same size, but differ in nearly every other way; mouse frontal cortical neurons are smaller than those in the monkey and also differ substantially with regard to most other properties. These findings have broad implications for understanding the differential contributions of heterogeneous neuronal types in construction of cortical microcircuitry in diverse brain areas and species.

Rat-strain dependent changes of dendritic and spine morphology in the hippocampus after cocaine self-administration

We previously showed that cocaine self-administration increases spine density in CA1 hippocampal neurons in Lewis (LEW) but not in Fischer 344 (F344) rats. Dendritic spine morphology is intimately related to its function. Thus, we conducted a 3D morphological analysis of CA1 dendrites and dendritic spines in these two strains of rats. Strain-specific differences were observed prior to cocaine self-administration: LEW rats had significantly larger dendritic diameters but lower spine density than the F344 strain. After cocaine self-administration, proximal dendritic volume, dendritic surface area and spine density were increased in LEW rats, where a higher percentage of larger spines were also observed. In addition, we found a strong positive correlation between dendritic volume and spine morphology, and a moderate correlation between dendritic volume and spine density in cocaine self-administered LEW rats, an effect that was not evident in any other condition. By contrast, after cocaine self-administration, F334 rats showed decreased spine head volumes. Our findings suggest that genetic differences could play a key role in the structural plasticity induced by cocaine in CA1 pyramidal neurons. These cocaine-induced alterations could be related to differences in the memory processing of drug reward cues that could potentially explain differential individual vulnerability to cocaine addiction.

Dendritic-branching angles of pyramidal neurons of the human cerebral cortex

In this article, we analyze branching angles of the basal dendrites of pyramidal neurons of layers III and V of the human temporal cortex. For this, we use a novel probability directional statistical distribution called truncated von Mises distribution that is able to describe more accurately the dendritic-branching angles than the previous proposals. Then, we perform comparative studies using this statistical method to determine similarities and/or differences between branches and branching angles that belong to different cortical layers and regions. Using this methodology, we found that common design principles exist and govern the patterns found in the different branches that compose the basal dendrites of human pyramidal cells of the temporal cortex. However, particular differences were found between supra and infragranular cells. Furthermore, we compared the branching angles of human layer III pyramidal neurons with data obtained in the previous studies in layer III of both the rat somatosensory cortex and of several cortical areas of the mouse. Finally, we study the branching angle differences between the humans that compose our data.

Effects of Swimming Exercise on Limbic and Motor Cortex Neurogenesis in the Kainate-Lesion Model of Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is a common neurological disease and antiseizure medication is often inadequate for preventing apoptotic cell death. Aerobic swimming exercise (EX) augments neurogenesis in rats when initiated immediately in the postictal period. This study tests the hypothesis that aerobic exercise also augments neurogenesis over the long term. Male Wistar rats (age of 4 months) were subjected to chemical lesioning using KA and to an EX intervention consisting of a 30 d period of daily swimming for 15 min, in one experiment immediately after KA lesioning (immediate exposure) and in a second experiment after a 60 d period of normal activity (delayed exposure). Morphometric counting of neuron numbers (NN) and dendritic branch points and intersections (DDBPI) was performed in the CA1, CA3, and dentate regions of hippocampus, in basolateral nucleus of amygdala, and in several areas of motor cortex. EX increased NN and DDBPI in the normal control and the KA-lesioned rats in all four limbic and motor cortex areas studied, after both immediate and 60 d delayed exposures to exercise. These findings suggest that, after temporal lobe epileptic seizures in rats, swimming exercise may improve neural plasticity in areas of the brain involved with emotional regulation and motor coordination, even if the exercise treatment is delayed.

Dendritic branching angles of pyramidal cells across layers of the juvenile rat somatosensory cortex

The characterization of the structural design of cortical microcircuits is essential for understanding how they contribute to function in both health and disease. Since pyramidal neurons represent the most abundant neuronal type and their dendritic spines constitute the major postsynaptic elements of cortical excitatory synapses, our understanding of the synaptic organization of the neocortex largely depends on the available knowledge regarding the structure of pyramidal cells. Previous studies have identified several apparently common rules in dendritic geometry. We study the dendritic branching angles of pyramidal cells across layers to further shed light on the principles that determine the geometric shapes of these cells. We find that the dendritic branching angles of pyramidal cells from layers II-VI of the juvenile rat somatosensory cortex suggest common design principles, despite the particular morphological and functional features that are characteristic of pyramidal cells in each cortical layer. J. Comp. Neurol. 524:2567-2576, 2016. © 2016 Wiley Periodicals, Inc.

Laminar Differences in Dendritic Structure of Pyramidal Neurons in the Juvenile Rat Somatosensory Cortex

Pyramidal cell structure varies between different cortical areas and species, indicating that the cortical circuits that these cells participate in are likely to be characterized by different functional capabilities. Structural differences between cortical layers have been traditionally reported using either the Golgi method or intracellular labeling, but the structure of pyramidal cells has not previously been systematically analyzed across all cortical layers at a particular age. In the present study, we investigated the dendritic architecture of complete basal arbors of pyramidal neurons in layers II, III, IV, Va, Vb, and VI of the hindlimb somatosensory cortical region of postnatal day 14 rats. We found that the characteristics of basal dendritic morphologies are statistically different in each cortical layer. The variations in size and branching pattern that exist between pyramidal cells of different cortical layers probably reflect the particular functional properties that are characteristic of the cortical circuit in which they participate. This new set of complete basal dendritic arbors of 3D-reconstructed pyramidal cell morphologies across each cortical layer will provide new insights into interlaminar information processing in the cerebral cortex.

Molecular Biomarkers for Embryonic and Adult Neural Stem Cell and Neurogenesis

The procedure of neurogenesis has made numerous achievements in the past decades, during which various molecular biomarkers have been emerging and have been broadly utilized for the investigation of embryonic and adult neural stem cell (NSC). Nevertheless, there is not a consistent and systematic illustration to depict the functional characteristics of the specific markers expressed in distinct cell types during the different stages of neurogenesis. Here we gathered and generalized a series of NSC biomarkers emerging during the procedures of embryonic and adult neural stem cell, which may be used to identify the subpopulation cells with distinguishing characters in different timeframes of neurogenesis. The identifications of cell patterns will provide applications to the detailed investigations of diverse developmental cell stages and the extents of cell differentiation, which will facilitate the tracing of cell time-course and fate determination of specific cell types and promote the further and literal discoveries of embryonic and adult neurogenesis. Meanwhile, via the utilization of comprehensive applications under the aiding of the systematic knowledge framework, researchers may broaden their insights into the derivation and establishment of novel technologies to analyze the more detailed process of embryogenesis and adult neurogenesis.

Life-time expression of the proteins peroxiredoxin, beta-synuclein, PARK7/DJ-1, and stathmin in the primary visual and primary somatosensory cortices in rats

Four distinct proteins are regulated in the aging neuroretina and may be regulated in the cerebral cortex, too: peroxiredoxin, beta-synuclein, PARK[Parkinson disease(autosomal recessive, early onset)]7/DJ-1, and Stathmin. Thus, we performed a comparative analysis of these proteins in the the primary somatosensory cortex (S1) and primary visual cortex (V1) in rats, in order to detect putative common development-, maturation- and age-related changes. The expressions of peroxiredoxin, beta-synuclein, PARK[Parkinson disease (autosomal recessive, early onset)]7/DJ-1, and Stathmin were compared in the newborn, juvenile, adult, and aged S1 and V1. Western blot (WB), quantitative reverse-transcription polymerase chain reaction (qRT-PCR), and immunohistochemistry (IHC) analyses were employed to determine whether the changes identified by proteomics were verifiable at the cellular and molecular levels. All of the proteins were detected in both of the investigated cortical areas. Changes in the expressions of the four proteins were found throughout the life-time of the rats. Peroxiredoxin expression remained unchanged over life-time. Beta-Synuclein expression was massively increased up to the adult stage of life in both the S1 and V1. PARK[Parkinson disease (autosomal recessive, early onset)]7/DJ-1 exhibited a massive up-regulation in both the S1 and V1 at all ages. Stathmin expression was massively down regulated after the neonatal period in both the S1 and V1. The detected protein alterations were analogous to their retinal profiles. This study is the first to provide evidence that peroxiredoxin, beta-synuclein, PARK[Parkinson disease (autosomal recessive, early onset)]7/DJ-1, and Stathmin are associated with postnatal maturation and aging in both the S1 and V1 of rats. These changes may indicate their involvement in key functional pathways and may account for the onset or progression of age-related pathologies.

Classifying GABAergic interneurons with semi-supervised projected model-based clustering

OBJECTIVES

A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names. We sought to automatically classify digitally reconstructed interneuronal morphologies according to this scheme. Simultaneously, we sought to discover possible subtypes of these types that might emerge during automatic classification (clustering). We also investigated which morphometric properties were most relevant for this classification.

MATERIALS AND METHODS

A set of 118 digitally reconstructed interneuronal morphologies classified into the common basket (CB), horse-tail (HT), large basket (LB), and Martinotti (MA) interneuron types by 42 of the world's leading neuroscientists, quantified by five simple morphometric properties of the axon and four of the dendrites. We labeled each neuron with the type most commonly assigned to it by the experts. We then removed this class information for each type separately, and applied semi-supervised clustering to those cells (keeping the others' cluster membership fixed), to assess separation from other types and look for the formation of new groups (subtypes). We performed this same experiment unlabeling the cells of two types at a time, and of half the cells of a single type at a time. The clustering model is a finite mixture of Gaussians which we adapted for the estimation of local (per-cluster) feature relevance. We performed the described experiments on three different subsets of the data, formed according to how many experts agreed on type membership: at least 18 experts (the full data set), at least 21 (73 neurons), and at least 26 (47 neurons).

RESULTS

Interneurons with more reliable type labels were classified more accurately. We classified HT cells with 100% accuracy, MA cells with 73% accuracy, and CB and LB cells with 56% and 58% accuracy, respectively. We identified three subtypes of the MA type, one subtype of CB and LB types each, and no subtypes of HT (it was a single, homogeneous type). We got maximum (adapted) Silhouette width and ARI values of 1, 0.83, 0.79, and 0.42, when unlabeling the HT, CB, LB, and MA types, respectively, confirming the quality of the formed cluster solutions. The subtypes identified when unlabeling a single type also emerged when unlabeling two types at a time, confirming their validity. Axonal morphometric properties were more relevant that dendritic ones, with the axonal polar histogram length in the [π, 2π) angle interval being particularly useful.

CONCLUSIONS

The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heterogeneous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones for distinguishing among the CB, HT, LB, and MA interneuron types.

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.

The effects of postnatal exposure to low-dose bisphenol-A on activity-dependent plasticity in the mouse sensory cortex

Bisphenol-A (BPA) is a monomer used in the production of polycarbonate plastics, epoxies and resins and is present in many common household objects ranging from water bottles, can linings, baby bottles, and dental resins. BPA exposure has been linked to numerous negative health effects throughout the body, although the mechanisms of BPA action on the developing brain are still poorly understood. In this study, we sought to investigate whether low dose BPA exposure during a developmental phase when brain connectivity is being organized can cause long-term deleterious effects on brain function and plasticity that outlast the BPA exposure. Lactating dams were orally exposed to 25 μg/kg/day of BPA (one half the U.S. Environmental Protection Agency's 50 μg/kg/day rodent dose reference) or vehicle alone from postnatal day (P)5 to P21. Pups exposed to BPA in their mother's milk exhibited deficits in activity-dependent plasticity in the visual cortex during the visual critical period (P28). To determine the possible mechanisms underlying BPA action, we used immunohistochemistry to examine histological markers known to impact cortical maturity and developmental plasticity and quantified cortical dendritic spine density, morphology, and dynamics. While we saw no changes in parvalbumin neuron density, myelin basic protein expression or microglial density in BPA-exposed animals, we observed increases in spine density on apical dendrites in cortical layer five neurons but no significant alterations in other morphological parameters. Taken together our results suggest that exposure to very low levels of BPA during a critical period of brain development can have profound consequences for the normal wiring of sensory circuits and their plasticity later in life.

Evo-devo and the primate isocortex: the central organizing role of intrinsic gradients of neurogenesis

Spatial gradients in the initiation and termination of basic processes, such as cytogenesis, cell-type specification and dendritic maturation, are ubiquitous in developing nervous systems. Such gradients can produce a niche adaptation in a particular species. For example, the high density of photoreceptors and neurons in the 'area centralis' of some vertebrate retinas result from the early maturation of its center relative to its periphery. Across species, regularities in allometric scaling of brain regions can derive from conserved spatial gradients: longer neurogenesis in the alar versus the basal plate of the neural tube is associated with relatively greater expansion of alar plate derivatives in larger brains. We describe gradients of neurogenesis within the isocortex and their effects on adult cytoarchitecture within and across species. Longer duration of neurogenesis in the caudal isocortex is associated with increased neuron number and density per column relative to the rostral isocortex. Later-maturing features of single neurons, such as soma size and dendritic spine numbers reflect this gradient. Considering rodents and primates, the longer the duration of isocortical neurogenesis in each species, the greater the rostral-to-caudal difference in neuron number and density per column. Extended developmental duration produces substantial, predictable changes in the architecture of the isocortex in larger brains, and presumably a progressively changed functional organization, the properties of which we do not yet fully understand. Many features of isocortical architecture previously viewed as species- or niche-specific adaptations can now be integrated as the natural outcomes of spatiotemporal gradients that are deployed in larger brains.

Spiny neurons of amygdala, striatum, and cortex use dendritic plateau potentials to detect network UP states

Spiny neurons of amygdala, striatum, and cerebral cortex share four interesting features: (1) they are the most abundant cell type within their respective brain area, (2) covered by thousands of thorny protrusions (dendritic spines), (3) possess high levels of dendritic NMDA conductances, and (4) experience sustained somatic depolarizations in vivo and in vitro (UP states). In all spiny neurons of the forebrain, adequate glutamatergic inputs generate dendritic plateau potentials (“dendritic UP states”) characterized by (i) fast rise, (ii) plateau phase lasting several hundred milliseconds, and (iii) abrupt decline at the end of the plateau phase. The dendritic plateau potential propagates toward the cell body decrementally to induce a long-lasting (longer than 100 ms, most often 200–800 ms) steady depolarization (∼20 mV amplitude), which resembles a neuronal UP state. Based on voltage-sensitive dye imaging, the plateau depolarization in the soma is precisely time-locked to the regenerative plateau potential taking place in the dendrite. The somatic plateau rises after the onset of the dendritic voltage transient and collapses with the breakdown of the dendritic plateau depolarization. We hypothesize that neuronal UP states in vivo reflect the occurrence of dendritic plateau potentials (dendritic UP states). We propose that the somatic voltage waveform during a neuronal UP state is determined by dendritic plateau potentials. A mammalian spiny neuron uses dendritic plateau potentials to detect and transform coherent network activity into a ubiquitous neuronal UP state. The biophysical properties of dendritic plateau potentials allow neurons to quickly attune to the ongoing network activity, as well as secure the stable amplitudes of successive UP states.

Pyramidal cell development: postnatal spinogenesis, dendritic growth, axon growth, and electrophysiology

Here we review recent findings related to postnatal spinogenesis, dendritic and axon growth, pruning and electrophysiology of neocortical pyramidal cells in the developing primate brain. Pyramidal cells in sensory, association and executive cortex grow dendrites, spines and axons at different rates, and vary in the degree of pruning. Of particular note is the fact that pyramidal cells in primary visual area (V1) prune more spines than they grow during postnatal development, whereas those in inferotemporal (TEO and TE) and granular prefrontal cortex (gPFC; Brodmann's area 12) grow more than they prune. Moreover, pyramidal cells in TEO, TE and the gPFC continue to grow larger dendritic territories from birth into adulthood, replete with spines, whereas those in V1 become smaller during this time. The developmental profile of intrinsic axons also varies between cortical areas: those in V1, for example, undergo an early proliferation followed by pruning and local consolidation into adulthood, whereas those in area TE tend to establish their territory and consolidate it into adulthood with little pruning. We correlate the anatomical findings with the electrophysiological properties of cells in the different cortical areas, including membrane time constant, depolarizing sag, duration of individual action potentials, and spike-frequency adaptation. All of the electrophysiological variables ramped up before 7 months of age in V1, but continued to ramp up over a protracted period of time in area TE. These data suggest that the anatomical and electrophysiological profiles of pyramidal cells vary among cortical areas at birth, and continue to diverge into adulthood. Moreover, the data reveal that the “use it or lose it” notion of synaptic reinforcement may speak to only part of the story, “use it but you still might lose it” may be just as prevalent in the cerebral cortex.

Brain scaling in mammalian evolution as a consequence of concerted and mosaic changes in numbers of neurons and average neuronal cell size

Enough species have now been subject to systematic quantitative analysis of the relationship between the morphology and cellular composition of their brain that patterns begin to emerge and shed light on the evolutionary path that led to mammalian brain diversity. Based on an analysis of the shared and clade-specific characteristics of 41 modern mammalian species in 6 clades, and in light of the phylogenetic relationships among them, here we propose that ancestral mammal brains were composed and scaled in their cellular composition like modern afrotherian and glire brains: with an addition of neurons that is accompanied by a decrease in neuronal density and very little modification in glial cell density, implying a significant increase in average neuronal cell size in larger brains, and the allocation of approximately 2 neurons in the cerebral cortex and 8 neurons in the cerebellum for every neuron allocated to the rest of brain. We also propose that in some clades the scaling of different brain structures has diverged away from the common ancestral layout through clade-specific (or clade-defining) changes in how average neuronal cell mass relates to numbers of neurons in each structure, and how numbers of neurons are differentially allocated to each structure relative to the number of neurons in the rest of brain. Thus, the evolutionary expansion of mammalian brains has involved both concerted and mosaic patterns of scaling across structures. This is, to our knowledge, the first mechanistic model that explains the generation of brains large and small in mammalian evolution, and it opens up new horizons for seeking the cellular pathways and genes involved in brain evolution.

Branching angles of pyramidal cell dendrites follow common geometrical design principles in different cortical areas

Unraveling pyramidal cell structure is crucial to understanding cortical circuit computations. Although it is well known that pyramidal cell branching structure differs in the various cortical areas, the principles that determine the geometric shapes of these cells are not fully understood. Here we analyzed and modeled with a von Mises distribution the branching angles in 3D reconstructed basal dendritic arbors of hundreds of intracellularly injected cortical pyramidal cells in seven different cortical regions of the frontal, parietal, and occipital cortex of the mouse. We found that, despite the differences in the structure of the pyramidal cells in these distinct functional and cytoarchitectonic cortical areas, there are common design principles that govern the geometry of dendritic branching angles of pyramidal cells in all cortical areas.

Novel tools, classic techniques: evolutionary studies using primate pluripotent stem cells

Recent applications of genomic tools on the analysis of alterations unique to our species coupled with a growing number of neuroanatomical studies across primates provide an unprecedented opportunity to compile different levels of human brain evolution into a complex whole. Applications of induced pluripotent stem cell (iPSC) technology, capable of reprogramming somatic tissue of different species and generating species-specific neuronal phenotypes, for the first time offer an opportunity to test specific evolutionary hypotheses in a field of inquiry that has been long plagued by the limited availability of research specimens. In this review, we will focus specifically on the experimental role of iPSC technology as applied to the analysis of neocortical pyramidal neurons. Pyramidal neurons emerge as particularly suitable for testing evolutionary scenarios, since they form the most common morphological class of neurons in the cortex, display morphological variations across different cortical areas and cortical layers that appear species-specific, and express unique molecular signatures. Human and nonhuman primate iPSC-derived neurons may represent a unique biological resource to elucidate the phenotypic differences between humans and other hominids. As the typical morphology of pyramidal neurons tends to be compromised in neurological disorders, application of iPSC technology to the analysis of pyramidal neurons could not only bring new insights into human adaptation but also offer opportunities to link biomedical research with studies of the origins of the human species.