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  Large-scale automated histology in the pursuit of connectomes

Kleinfeld, D., Bharioke, A., Blinder, P., Bock, D. D., Briggman, K., Chklovskii, D. B., et al. (2011). Large-scale automated histology in the pursuit of connectomes. The Journal of Neuroscience, 31(45), 16125-16138. doi:10.1523/JNEUROSCI.4077-11.2011.

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Genre: Journal Article
Alternative Title : Large-scale automated histology in the pursuit of connectomes

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 Creators:
Kleinfeld, David, Author
Bharioke, Arjun, Author
Blinder, Pablo, Author
Bock, Davi D., Author
Briggman, Kevin1, Author           
Chklovskii, Dmitri B., Author
Denk, Winfried1, Author           
Helmstaedter, Moritz1, 2, Author           
Kaufhold, John P., Author
Lee, Wei−Chung Allen, Author
Meyer, Hanno S., Author
Micheva, Kristina D., Author
Oberlaender, Marcel2, Author           
Prohaska, Steffen, Author
Reid, R. Clay, Author
Smith, Stephen J., Author
Takemura, Shinya, Author
Tsai, Philbert S., Author
Sakmann, Bert2, Author           
Affiliations:
1Department of Biomedical Optics, Max Planck Institute for Medical Research, Max Planck Society, ou_1497699              
2Department of Cell Physiology, Max Planck Institute for Medical Research, Max Planck Society, ou_1497701              

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 Abstract: How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity

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Language(s): eng - English
 Dates: 2011-11-09
 Publication Status: Issued
 Pages: 14
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: eDoc: 664451
DOI: 10.1523/JNEUROSCI.4077-11.2011
Other: 7727
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Title: The Journal of Neuroscience
  Other : The Journal of Neuroscience: the Official Journal of the Society for Neuroscience
  Abbreviation : J. Neurosci.
Source Genre: Journal
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Publ. Info: Washington, DC : Society of Neuroscience
Pages: - Volume / Issue: 31 (45) Sequence Number: - Start / End Page: 16125 - 16138 Identifier: ISSN: 0270-6474
CoNE: https://pure.mpg.de/cone/journals/resource/954925502187_1