A biologically inspired repair mechanism for neuronal reconstructions with a focus on human dendrites.

Investigating and modelling the functionality of human neurons remains challenging due to the technical limitations, resulting in scarce and incomplete 3D anatomical reconstructions. Here we used a morphological modelling approach based on optimal wiring to repair the parts of a dendritic morphology that were lost due to incomplete tissue samples. In Drosophila, where dendritic regrowth has been studied experimentally using laser ablation, we found that modelling the regrowth reproduced a bimodal distribution between regeneration of cut branches and invasion by neighbouring branches. Interestingly, our repair model followed growth rules similar to those for the generation of a new dendritic tree. To generalise the repair algorithm from Drosophila to mammalian neurons, we artificially sectioned reconstructed dendrites from mouse and human hippocampal pyramidal cell morphologies, and showed that the regrown dendrites were morphologically similar to the original ones. Furthermore, we were able to restore their electrophysiological functionality, as evidenced by the recovery of their firing behaviour. Importantly, we show that such repairs also apply to other neuron types including hippocampal granule cells and cerebellar Purkinje cells. We then extrapolated the repair to incomplete human CA1 pyramidal neurons, where the anatomical boundaries of the particular brain areas innervated by the neurons in question were known. Interestingly, the repair of incomplete human dendrites helped to simulate the recently observed increased synaptic thresholds for dendritic NMDA spikes in human versus mouse dendrites. To make the repair tool available to the neuroscience community, we have developed an intuitive and simple graphical user interface (GUI), which is available in the TREES toolbox (www.treestoolbox.org).

Key morphological features of human pyramidal neurons.

The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.

Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex.

Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.

Variation in Pyramidal Cell Morphology Across the Human Anterior Temporal Lobe.

Pyramidal neurons are the most abundant and characteristic neuronal type in the cerebral cortex and their dendritic spines are the main postsynaptic elements of cortical excitatory synapses. Previous studies have shown that pyramidal cell structure differs across layers, cortical areas, and species. However, within the human cortex, the pyramidal dendritic morphology has been quantified in detail in relatively few cortical areas. In the present work, we performed intracellular injections of Lucifer Yellow at several distances from the temporal pole. We found regional differences in pyramidal cell morphology, which showed large inter-individual variability in most of the morphological variables measured. However, some values remained similar in all cases. The smallest and least complex cells in the most posterior temporal region showed the greatest dendritic spine density. Neurons in the temporal pole showed the greatest sizes with the highest number of spines. Layer V cells were larger, more complex, and had a greater number of dendritic spines than those in layer III. The present results suggest that, while some aspects of pyramidal structure are conserved, there are specific variations across cortical regions, and species.

Volume Electron Microscopy Study of the Relationship Between Synapses and Astrocytes in the Developing Rat Somatosensory Cortex.

In recent years, numerous studies have shown that astrocytes play an important role in neuronal processing of information. One of the most interesting findings is the existence of bidirectional interactions between neurons and astrocytes at synapses, which has given rise to the concept of "tripartite synapses" from a functional point of view. We used focused ion beam milling and scanning electron microscopy (FIB/SEM) to examine in 3D the relationship of synapses with astrocytes that were previously labeled by intracellular injections in the rat somatosensory cortex. We observed that a large number of synapses (32%) had no contact with astrocytic processes. The remaining synapses (68%) were in contact with astrocytic processes, either at the level of the synaptic cleft (44%) or with the pre- and/or post-synaptic elements (24%). Regarding synaptic morphology, larger synapses with more complex shapes were most frequently found within the population that had the synaptic cleft in contact with astrocytic processes. Furthermore, we observed that although synapses were randomly distributed in space, synapses that were free of astrocytic processes tended to form clusters. Overall, at least in the developing rat neocortex, the concept of tripartite synapse only seems to be applicable to a subset of synapses.

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.

3D morphology-based clustering and simulation of human pyramidal cell dendritic spines.

The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.

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.

New insights into the classification and nomenclature of cortical GABAergic interneurons.

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

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.

Random positions of dendritic spines in human cerebral cortex.

Dendritic spines establish most excitatory synapses in the brain and are located in Purkinje cell's dendrites along helical paths, perhaps maximizing the probability to contact different axons. To test whether spine helixes also occur in neocortex, we reconstructed >500 dendritic segments from adult human cortex obtained from autopsies. With Fourier analysis and spatial statistics, we analyzed spine position along apical and basal dendrites of layer 3 pyramidal neurons from frontal, temporal, and cingulate cortex. Although we occasionally detected helical positioning, for the great majority of dendrites we could not reject the null hypothesis of spatial randomness in spine locations, either in apical or basal dendrites, in neurons of different cortical areas or among spines of different volumes and lengths. We conclude that in adult human neocortex spine positions are mostly random. We discuss the relevance of these results for spine formation and plasticity and their functional impact for cortical circuits.

The influence of phospho-τ on dendritic spines of cortical pyramidal neurons in patients with Alzheimer's disease.

The dendritic spines on pyramidal cells represent the main postsynaptic elements of cortical excitatory synapses and they are fundamental structures in memory, learning and cognition. In the present study, we used intracellular injections of Lucifer yellow in fixed tissue to analyse over 19 500 dendritic spines that were completely reconstructed in three dimensions along the length of the basal dendrites of pyramidal neurons in the parahippocampal cortex and CA1 of patients with Alzheimer's disease. Following intracellular injection, sections were immunostained for anti-Lucifer yellow and with tau monoclonal antibodies AT8 and PHF-1, which recognize tau phosphorylated at Ser202/Thr205 and at Ser396/404, respectively. We observed that the diffuse accumulation of phospho-tau in a putative pre-tangle state did not induce changes in the dendrites of pyramidal neurons, whereas the presence of tau aggregates forming intraneuronal neurofibrillary tangles was associated with progressive alteration of dendritic spines (loss of dendritic spines and changes in their morphology) and dendrite atrophy, depending on the degree of tangle development. Thus, the presence of phospho-tau in neurons does not necessarily mean that they suffer severe and irreversible effects as thought previously but rather, the characteristic cognitive impairment in Alzheimer's disease is likely to depend on the relative number of neurons that have well developed tangles.

Age-based comparison of human dendritic spine structure using complete three-dimensional reconstructions.

Dendritic spines of pyramidal neurons are targets of most excitatory synapses in the cerebral cortex. Recent evidence suggests that the morphology of the dendritic spine could determine its synaptic strength and learning rules. However, unfortunately, there are scant data available regarding the detailed morphology of these structures for the human cerebral cortex. In the present study, we analyzed over 8900 individual dendritic spines that were completely 3D reconstructed along the length of apical and basal dendrites of layer III pyramidal neurons in the cingulate cortex of 2 male humans (aged 40 and 85 years old), using intracellular injections of Lucifer Yellow in fixed tissue. We assembled a large, quantitative database, which revealed a major reduction in spine densities in the aged case. Specifically, small and short spines of basal dendrites and long spines of apical dendrites were lost, regardless of the distance from the soma. Given the age difference between the cases, our results suggest selective alterations in spines with aging in humans and indicate that the spine volume and length are regulated by different biological mechanisms.

Human Purkinje cells outperform mouse Purkinje cells in dendritic complexity and computational capacity.

Purkinje cells in the cerebellum are among the largest neurons in the brain and have been extensively investigated in rodents. However, their morphological and physiological properties remain poorly understood in humans. In this study, we utilized high-resolution morphological reconstructions and unique electrophysiological recordings of human Purkinje cells ex vivo to generate computational models and estimate computational capacity. An inter-species comparison showed that human Purkinje cell had similar fractal structures but were larger than those of mouse Purkinje cells. Consequently, given a similar spine density (2/µm), human Purkinje cell hosted approximately 7.5 times more dendritic spines than those of mice. Moreover, human Purkinje cells had a higher dendritic complexity than mouse Purkinje cells and usually emitted 2-3 main dendritic trunks instead of one. Intrinsic electro-responsiveness was similar between the two species, but model simulations revealed that the dendrites could process ~6.5 times (n = 51 vs. n = 8) more input patterns in human Purkinje cells than in mouse Purkinje cells. Thus, while human Purkinje cells maintained spike discharge properties similar to those of rodents during evolution, they developed more complex dendrites, enhancing computational capacity.

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

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

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

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

Ex vivo, in situ perfusion protocol for human brain fixation compatible with microscopy, MRI techniques, and anatomical studies.

We present a method for human brain fixation based on simultaneous perfusion of 4% paraformaldehyde through carotids after a flush with saline. The left carotid cannula is used to perfuse the body with 10% formalin, to allow further use of the body for anatomical research or teaching. The aim of our method is to develop a vascular fixation protocol for the human brain, by adapting protocols that are commonly used in experimental animal studies. We show that a variety of histological procedures can be carried out (cyto- and myeloarchitectonics, histochemistry, immunohistochemistry, intracellular cell injection, and electron microscopy). In addition, ex vivo, ex situ high-resolution MRI (9.4T) can be obtained in the same specimens. This procedure resulted in similar morphological features to those obtained by intravascular perfusion in experimental animals, provided that the postmortem interval was under 10 h for several of the techniques used and under 4 h in the case of intracellular injections and electron microscopy. The use of intravascular fixation of the brain inside the skull provides a fixed whole human brain, perfectly fitted to the skull, with negligible deformation compared to conventional techniques. Given this characteristic of ex vivo, in situ fixation, this procedure can probably be considered the most suitable one available for ex vivo MRI scans of the brain. We describe the compatibility of the method proposed for intravascular fixation of the human brain and fixation of the donor's body for anatomical purposes. Thus, body donor programs can provide human brain tissue, while the remainder of the body can also be fixed for anatomical studies. Therefore, this method of human brain fixation through the carotid system optimizes the procurement of human brain tissue, allowing a greater understanding of human neurological diseases, while benefiting anatomy departments by making the remainder of the body available for teaching purposes.

Structural Analysis of Human and Mouse Dendritic Spines Reveals a Morphological Continuum and Differences across Ages and Species.

Dendritic spines have diverse morphologies, with a wide range of head and neck sizes, and these morphologic differences likely generate different functional properties. To explore how this morphologic diversity differs across species and ages we analyzed 3D confocal reconstructions of ∼8000 human spines and ∼1700 mouse spines, labeled by intracellular injections in fixed tissue. Using unsupervised algorithms, we computationally separated spine heads and necks and systematically measured morphologic features of spines in apical and basal dendrites from cortical pyramidal cells. Human spines had unimodal distributions of parameters, without any evidence of morphologic subtypes. Their spine necks were longer and thinner in apical than in basal spines, and spine head volumes of an 85-year-old individual were larger than those of a 40-year-old individual. Human spines had longer and thicker necks and larger head volumes than mouse spines. Our results indicate that human spines form part of a continuum, are larger and longer than those of mice, and become larger with increasing adult age. These morphologic differences in spines across species could generate functional differences in biochemical and electrical spine compartmentalization, or in synaptic properties, across species and ages.

A Deep Learning-Based Workflow for Dendritic Spine Segmentation.

The morphological analysis of dendritic spines is an important challenge for the neuroscientific community. Most state-of-the-art techniques rely on user-supervised algorithms to segment the spine surface, especially those designed for light microscopy images. Therefore, processing large dendritic branches is costly and time-consuming. Although deep learning (DL) models have become one of the most commonly used tools in image segmentation, they have not yet been successfully applied to this problem. In this article, we study the feasibility of using DL models to automatize spine segmentation from confocal microscopy images. Supervised learning is the most frequently used method for training DL models. This approach requires large data sets of high-quality segmented images (ground truth). As mentioned above, the segmentation of microscopy images is time-consuming and, therefore, in most cases, neuroanatomists only reconstruct relevant branches of the stack. Additionally, some parts of the dendritic shaft and spines are not segmented due to dyeing problems. In the context of this research, we tested the most successful architectures in the DL biomedical segmentation field. To build the ground truth, we used a large and high-quality data set, according to standards in the field. Nevertheless, this data set is not sufficient to train convolutional neural networks for accurate reconstructions. Therefore, we implemented an automatic preprocessing step and several training strategies to deal with the problems mentioned above. As shown by our results, our system produces a high-quality segmentation in most cases. Finally, we integrated several postprocessing user-supervised algorithms in a graphical user interface application to correct any possible artifacts.