Thalamocortical input onto layer 5 pyramidal neurons measured using quantitative large-scale array tomography
Authors: Jong-Cheol Rah
Yuriy Mishchenko
Karel Svoboda
Bill Karsh
Richard D Fetter
Dmitri B Chklovskii
Eugene W Myers
Jennifer Colonell
Timothy D Harris
John T R Isaac
Erhan Bas
Journal: Frontiers in Neural Circuits (2013)
Discipline: NEUROSCIENCE & BEHAVIOR
Keywords: array tomography; barrel cortex; dendritic integration; electron microscopy; neural circuits
Affiliations: Howard Hughes Medical Institute, Janelia Farm Research Campus Ashburn, VA, USA ; Developmental Synaptic Plasticity Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health Bethesda, MD, USA.

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 × 0.83 × 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. 

Retracted: No

PubPeer comments:
 image duplication ![file] Disclaimer: These potential image duplications have been detected automatically using ImageTwin http: dx.doi.org 10.1145 3019612.3019875 Although results have been curated, the automatic algorithm may have generated false positive results and cannot take into account all scientific explanations for apparent duplications like stripped and reprobed blots, time series, serial sections and reused controls. , 
 #1 This robot is flagging  duplications with zero consideration of experimental context. Here (Fig 6), panels C1 - C5 are close-ups of the field shown in panel C, zooming in to emphasize distinct features evident in the larger field, which are denoted by the numbered and differently-colored arrowheads. There is absolutely nothing wrong, problematic, or misleading here. The only problem is the posting of raw algorithm results without assessment of the scientific context. , 
 #2 Leucanella Acutissima What has happened is that a single presynaptic element (blue synaptophysin labelling) contacts two different postsynaptic spines (green). So they are technically separate example synapses, but it might have been worth mentioning the unusual situation and it might have been simpler to show two arrows on the same panel. I guess you could say that the two panels are worth 1.5 synapses rather than two? , 
 #3 Epizoanthus, (a) Thanks for the additional input on the content of the images. (b) The point I was making is that #1 is flagging  duplications without any effort to examine the scientific context. In principle, #1 could flag every one of the panels in C1-C5 as a partial  duplication of the image in panel C. But of course that would be ridiculous. These are close-ups of various parts of panel C, and they are labeled as such in the legend; moreover, this fact is implicit in the sub-panel nomenclature (i.e., C1-C5 are five parts of C). So, the initial post in #1 is simply pointless. ,