Extracellular space preservation aids the connectomic analysis of neural circuits
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 segmen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2015-12-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/08206 |
| _version_ | 1811227887066415104 |
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| author | Marta Pallotto Paul V Watkins Boma Fubara Joshua H Singer Kevin L Briggman |
| author_facet | Marta Pallotto Paul V Watkins Boma Fubara Joshua H Singer Kevin L Briggman |
| author_sort | Marta Pallotto |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T09:49:25Z |
| format | Article |
| id | doaj.art-0088c1359cb84b7394cbe6c221052f75 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T09:49:25Z |
| publishDate | 2015-12-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-0088c1359cb84b7394cbe6c221052f752022-12-22T03:37:52ZengeLife Sciences Publications LtdeLife2050-084X2015-12-01410.7554/eLife.08206Extracellular space preservation aids the connectomic analysis of neural circuitsMarta Pallotto0https://orcid.org/0000-0001-7694-0398Paul V Watkins1Boma Fubara2Joshua H Singer3Kevin L Briggman4Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United StatesCircuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United StatesCircuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United StatesDepartment of Biology, University of Maryland, College Park, United StatesCircuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States; Department of Biomedical Optics, Max Planck Institute for Medical Research, Heidelberg, GermanyDense 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.https://elifesciences.org/articles/08206connectomicsextracellular spacemachine learninggap junctiontissue fixation |
| spellingShingle | Marta Pallotto Paul V Watkins Boma Fubara Joshua H Singer Kevin L Briggman Extracellular space preservation aids the connectomic analysis of neural circuits eLife connectomics extracellular space machine learning gap junction tissue fixation |
| title | Extracellular space preservation aids the connectomic analysis of neural circuits |
| title_full | Extracellular space preservation aids the connectomic analysis of neural circuits |
| title_fullStr | Extracellular space preservation aids the connectomic analysis of neural circuits |
| title_full_unstemmed | Extracellular space preservation aids the connectomic analysis of neural circuits |
| title_short | Extracellular space preservation aids the connectomic analysis of neural circuits |
| title_sort | extracellular space preservation aids the connectomic analysis of neural circuits |
| topic | connectomics extracellular space machine learning gap junction tissue fixation |
| url | https://elifesciences.org/articles/08206 |
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