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Extracellular space preservation aids the connectomic analysis of neural circuits.

Pallotto M, Watkins PV, Fubara B, Singer JH, Briggman KL - Elife (2015)

Bottom Line: Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data.ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates.We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

View Article: PubMed Central - PubMed

Affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.

ABSTRACT
Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

No MeSH data available.


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Simple measures of contact geometry do not predict gap junctions.(A) Surface area and the volume of the convex hull bounding each contact are plotted for cleft contacts (gray), AII amacrine cell tight contacts (blue) and cone bipolar cell tight contacts (green).DOI:http://dx.doi.org/10.7554/eLife.08206.022
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fig4s1: Simple measures of contact geometry do not predict gap junctions.(A) Surface area and the volume of the convex hull bounding each contact are plotted for cleft contacts (gray), AII amacrine cell tight contacts (blue) and cone bipolar cell tight contacts (green).DOI:http://dx.doi.org/10.7554/eLife.08206.022

Mentions: We then asked whether the tight contacts were actually indicative of gap junctions (electrical synapses) onto the AII amacrine cell. Of the 21 tight contacts we annotated, 4 were formed with a neighboring AII amacrine cell and 17 were formed with ON cone bipolar cell terminals (Figure 4E,F). Thus, in every instance, the tight contact was formed with a cell type known to be electrically coupled to the AII amacrine cell indicating that tight contacts in ECS preserved data are consistent with gap junctions. Moreover, AII-AII gap junctions were found in sublamina 5 of the IPL, and AII-ON cone bipolar gap junctions were found in sublaminae 3 and 4, as previously reported (Strettoia et al., 1992). We noted that the gap junctions were not identifiable based on contact geometry measurements, such as surface area, alone (Figure 4—figure supplement 1). The preservation of ECS therefore enabled the identification of gap junctions due to the relative scarcity of contacts amongst cells and the simple segregation of contacts into tight versus cleft categories.


Extracellular space preservation aids the connectomic analysis of neural circuits.

Pallotto M, Watkins PV, Fubara B, Singer JH, Briggman KL - Elife (2015)

Simple measures of contact geometry do not predict gap junctions.(A) Surface area and the volume of the convex hull bounding each contact are plotted for cleft contacts (gray), AII amacrine cell tight contacts (blue) and cone bipolar cell tight contacts (green).DOI:http://dx.doi.org/10.7554/eLife.08206.022
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4764589&req=5

fig4s1: Simple measures of contact geometry do not predict gap junctions.(A) Surface area and the volume of the convex hull bounding each contact are plotted for cleft contacts (gray), AII amacrine cell tight contacts (blue) and cone bipolar cell tight contacts (green).DOI:http://dx.doi.org/10.7554/eLife.08206.022
Mentions: We then asked whether the tight contacts were actually indicative of gap junctions (electrical synapses) onto the AII amacrine cell. Of the 21 tight contacts we annotated, 4 were formed with a neighboring AII amacrine cell and 17 were formed with ON cone bipolar cell terminals (Figure 4E,F). Thus, in every instance, the tight contact was formed with a cell type known to be electrically coupled to the AII amacrine cell indicating that tight contacts in ECS preserved data are consistent with gap junctions. Moreover, AII-AII gap junctions were found in sublamina 5 of the IPL, and AII-ON cone bipolar gap junctions were found in sublaminae 3 and 4, as previously reported (Strettoia et al., 1992). We noted that the gap junctions were not identifiable based on contact geometry measurements, such as surface area, alone (Figure 4—figure supplement 1). The preservation of ECS therefore enabled the identification of gap junctions due to the relative scarcity of contacts amongst cells and the simple segregation of contacts into tight versus cleft categories.

Bottom Line: Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data.ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates.We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

View Article: PubMed Central - PubMed

Affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.

ABSTRACT
Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

No MeSH data available.


Related in: MedlinePlus