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Multiscale and multimodal reconstruction of cortical structure and function

Turner, N. L.; Macrina, T.; Bae, J. A.; Yang, R.; Wilson, A. M.; Schneider-Mizell, C.; Lee, K.; Lu, R.; Wu, J.; Bodor, A. L.; Bleckert, A. A.; Brittain, D.; Froudarakis, E.; Dorkenwald, S.; Collman, F.; Kemnitz, N.; Ih, D.; Silversmith, W. M.; Zung, J.; Zlateski, A.; Tartavull, I.; Yu, S.-c.; Popovych, S.; Mu, S.; Wong, W.; Jordan, C. S.; Castro, M.; Buchanan, J.; Bumbarger, D. J.; Takeno, M.; Torres, R.; Mahalingam, G.; Elabbady, L.; Li, Y.; Cobos, E.; Zhou, P.; Suckow, S.; Becker, L.; Paninski, L.; Polleux, F.; Reimer, J.; Tolias, A. S.; Reid, R. C.; Macarico da Costa, N.; Seung, H. S.

2020-10-14 neuroscience
10.1101/2020.10.14.338681 bioRxiv
Show abstract

We 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 resources utility for relating structure and function of cortical circuits as well as for neuronal cell biology.

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