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In the present study, we have used focused ion beam/scanning electron microscopy (FIB/SEM) to perform a study of the synaptic organization of layer III of Brodmann's area 21 in human tissue samples obtained from autopsies and biopsies. We analyzed the synaptic density, 3D spatial distribution, and type (asymmetric/symmetric), as well as the size and shape of each synaptic junction of 4945 synapses that were fully reconstructed in 3D. Significant differences in the mean synaptic density between autopsy and biopsy samples were found (0.49 and 0.66 synapses/μm3, respectively). However, in both types of samples (autopsy and biopsy), the asymmetric:symmetric ratio was similar (93:7) and most asymmetric synapses were established on dendritic spines (75%), while most symmetric synapses were established on dendritic shafts (85%). We also compared several electron microscopy methods and analysis tools to estimate the synaptic density in the same brain tissue. We have shown that FIB/SEM is much more reliable and robust than the majority of the other commonly used EM techniques. The present work constitutes a detailed description of the synaptic organization of cortical layer III. Further studies on the rest of the cortical layers are necessary to better understand the functional organization of this temporal cortical region., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm(3) containing ~31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ~8 million connections with ~37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies., Paperclip: VIDEO ABSTRACT., (Copyright © 2015 Elsevier Inc. All rights reserved.)

The appearance of the neocortex, its expansion, and its differentiation in mammals, represents one of the principal episodes in the evolution of the vertebrate brain. One of the fundamental questions in neuroscience is what is special about the neocortex of humans and how does it differ from that of other species? It is clear that distinct cortical areas show important differences within both the same and different species, and this has led to some researchers emphasizing the similarities whereas others focus on the differences. In general, despite of the large number of different elements that contribute to neocortical circuits, it is thought that neocortical neurons are organized into multiple, small repeating microcircuits, based around pyramidal cells and their input-output connections. These inputs originate from extrinsic afferent systems, excitatory glutamatergic spiny cells (which include other pyramidal cells and spiny stellate cells), and inhibitory GABAergic interneurons. The problem is that the neuronal elements that make up the basic microcircuit are differentiated into subtypes, some of which are lacking or highly modified in different cortical areas or species. Furthermore, the number of neurons contained in a discrete vertical cylinder of cortical tissue varies across species. Additionally, it has been shown that the neuropil in different cortical areas of the human, rat and mouse has a characteristic layer specific synaptology. These variations most likely reflect functional differences in the specific cortical circuits. The laminar specific similarities between cortical areas and between species, with respect to the percentage, length and density of excitatory and inhibitory synapses, and to the number of synapses per neuron, might be considered as the basic cortical building bricks. In turn, the differences probably indicate the evolutionary adaptation of excitatory and inhibitory circuits to particular functions.

• Automatic detection of cells is critical in neuroanatomical studies. • We present a tool for automatic segmentation that allows cell type discrimination. • This tool provides data to study the number of cells and their spatial distribution. Analyzing images to accurately estimate the number of different cell types in the brain using automatic methods is a major objective in neuroscience. The automatic and selective detection and segmentation of neurons would be an important step in neuroanatomical studies. We present a method to improve the 3D reconstruction of neuronal nuclei that allows their segmentation, excluding the nuclei of non-neuronal cell types. We have tested the algorithm on stacks of images from rat neocortex, in a complex scenario (large stacks of images, uneven staining, and three different channels to visualize different cellular markers). It was able to provide a good identification ratio of neuronal nuclei and a 3D segmentation. Comparison with Existing Methods: Many automatic tools are in fact currently available, but different methods yield different cell count estimations, even in the same brain regions, due to differences in the labeling and imaging techniques, as well as in the algorithms used to detect cells. Moreover, some of the available automated software methods have provided estimations of cell numbers that have been reported to be inaccurate or inconsistent after evaluation by neuroanatomists. It is critical to have a tool for automatic segmentation that allows discrimination between neurons, glial cells and perivascular cells. It would greatly speed up a task that is currently performed manually and would allow the cell counting to be systematic, avoiding human bias. Furthermore, the resulting 3D reconstructions of different cell types can be used to generate models of the spatial distribution of cells. [ABSTRACT FROM AUTHOR]