@article {6674, title = {Thalamocortical input onto layer 5 pyramidal neurons measured using quantitative large-scale array tomography.}, journal = {Frontiers in Neural Circuits}, volume = {7}, year = {2013}, month = {2013}, pages = {177}, abstract = {

The subcellular locations of synapses on pyramidal neurons strongly influences dendritic integration and synaptic plasticity. Despite this, there is little quantitative data on spatial distributions of specific types of synaptic input. Here we use array tomography (AT), a high-resolution optical microscopy method, to examine thalamocortical (TC) input onto layer 5 pyramidal neurons. We first verified the ability of AT to identify synapses using parallel electron microscopic analysis of TC synapses in layer 4. We then use large-scale array tomography (LSAT) to measure TC synapse distribution on L5 pyramidal neurons in a 1.00 {\texttimes} 0.83 {\texttimes} 0.21 mm(3) volume of mouse somatosensory cortex. We found that TC synapses primarily target basal dendrites in layer 5, but also make a considerable input to proximal apical dendrites in L4, consistent with previous work. Our analysis further suggests that TC inputs are biased toward certain branches and, within branches, synapses show significant clustering with an excess of TC synapse nearest neighbors within 5-15 μm compared to a random distribution. Thus, we show that AT is a sensitive and quantitative method to map specific types of synaptic input on the dendrites of entire neurons. We anticipate that this technique will be of wide utility for mapping functionally-relevant anatomical connectivity in neural circuits.

}, issn = {1662-5110}, doi = {10.3389/fncir.2013.00177}, author = {Rah, Jong-Cheol and Bas, Erhan and Colonell, Jennifer and Mishchenko, Yuriy and Karsh, Bill and Fetter, Richard D and Myers, Eugene W and Chklovskii, Dmitri B and Svoboda, Karel and Harris, Timothy D and Isaac, John T R} } @article {1235, title = {Ultrastructural analysis of hippocampal neuropil from the connectomics perspective.}, journal = {Neuron}, volume = {67}, year = {2010}, month = {2010 Sep 23}, pages = {1009-20}, abstract = {

Complete reconstructions of vertebrate neuronal circuits on the synaptic level require new approaches. Here, serial section transmission electron microscopy was automated to densely reconstruct four volumes, totaling 670 μm(3), from the rat hippocampus as proving grounds to determine when axo-dendritic proximities predict synapses. First, in contrast with Peters{\textquoteright} rule, the density of axons within reach of dendritic spines did not predict synaptic density along dendrites because the fraction of axons making synapses was variable. Second, an axo-dendritic touch did not predict a synapse; nevertheless, the density of synapses along a hippocampal dendrite appeared to be a universal fraction, 0.2, of the density of touches. Finally, the largest touch between an axonal bouton and spine indicated the site of actual synapses with about 80\% precision but would miss about half of all synapses. Thus, it will be difficult to predict synaptic connectivity using data sets missing ultrastructural details that distinguish between axo-dendritic touches and bona fide synapses.

}, keywords = {Animals, Automatic Data Processing, Axons, Dendrites, Electron, Hippocampus, Long-Evans, Male, Microscopy, Neuropil, Newborn, Rats, Synapses, Transmission}, issn = {1097-4199}, doi = {10.1371/journal.pcbi.1001066}, author = {Mishchenko, Yuriy and Hu, Tao and Spacek, Josef and Mendenhall, John and Harris, Kristen M and Chklovskii, Dmitri B} } @article {4276, title = {Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs.}, journal = {Journal of Neuroscience Methods}, volume = {176}, year = {2009}, month = {2009 Jan 30}, pages = {276-89}, abstract = {

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.

}, keywords = {Animals, Automation, Axons, Electron, Imaging, Microscopy, Neurons, Three-Dimensional, Transmission}, issn = {0165-0270}, doi = {10.1016/j.jneumeth.2008.09.006}, author = {Mishchenko, Yuriy} }