Systematic errors in connectivity inferred from activity in strongly recurrent networks-Reference-Cited by-同舟云学术

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Systematic errors in connectivity inferred from activity in strongly recurrent networks

Published:2020-09-07 Issue:10 Volume:23 Page:1286-1296
ISSN:1097-6256
Container-title:Nature Neuroscience
language:en
Short-container-title:Nat Neurosci

Author:

Das Abhranil^ORCID,Fiete Ila R.^ORCID

Funder

Howard Hughes Medical Institute

Simons Foundation

ONR; HHMI through the Faculty Scholars program; Simons Collaboration on the Global Brain through the Simons Foundation

Publisher

Springer Science and Business Media LLC

Subject

General Neuroscience

Link

https://www.nature.com/articles/s41593-020-0699-2.pdf

Reference55 articles.

1. Burns, R., et al. The Open Connectome Project data cluster: scalable analysis and vision for high-throughput neuroscience. In Proceedings of the 25th International Conference on Scientific and Statistical Database Management, 1–11 (Association for Computing Machinery, 2013).

2. Xu, C. S. et al. A connectome of the adult Drosophila central brain. Preprint at bioRxiv https://doi.org/10.1101/2020.01.21.911859 (2020).

3. Helmstaedter, M. et al. Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168 (2013).

4. Takemura, S.-Y. et al. A visual motion detection circuit suggested by Drosophila connectomics. Nature 500, 175–181 (2013).

5. Lee, W.-C. A. et al. Anatomy and function of an excitatory network in the visual cortex. Nature 532, 370–374 (2016).

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