| Autor: |
Russel Torres, Adam Bleckert, Alyssa Wilson, William Wong, Derrick Brittain, Nicholas L. Turner, Chris S. Jordan, Franck Polleux, Shang Mu, Forrest Collman, J. Alexander Bae, Liam Paninski, R. Clay Reid, Manuel Castro, Aleksandar Zlateski, Gayathri Mahalingam, Jonathan Zung, William Silversmith, Ran Lu, Sven Dorkenwald, Casey M Schneider-Mizell, Nuno Maçarico da Costa, H. Sebastian Seung, JoAnn Buchanan, Jacob Reimer, Pengcheng Zhou, Shelby Suckow, Nico Kemnitz, Yang Li, Marc Takeno, Jingpeng Wu, Erick Cobos, Szi-chieh Yu, Agnes L. Bodor, Dodam Ih, Runzhe Yang, Kisuk Lee, Sergiy Popovych, Daniel J. Bumbarger, Lynne Becker, Andreas S. Tolias, Leila Elabbady, Ignacio Tartavull, Thomas Macrina, Emmanouil Froudarakis |
| Rok vydání: |
2020 |
| Předmět: |
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| Popis: |
SummaryWe present a semi-automated reconstruction of L2/3 mouse primary visual cortex from 3 million cubic microns of electron microscopic images, including pyramidal and inhibitory neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are being made publicly available, along with tools for programmatic and 3D interactive access. The density of synaptic inputs onto inhibitory neurons varies across cell classes and compartments. We uncover a compartment-specific correlation between mitochondrial coverage and synapse density. Frequencies of connectivity motifs in the graph of pyramidal cells are predicted quite accurately from node degrees using the configuration model of random graphs. Cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. These example findings illustrate the resource’s utility for relating structure and function of cortical circuits as well as for neuronal cell biology. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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