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  Computational methods and challenges for large-scale circuit mapping

Helmstaedter, M., & Mitra, P. P. (2012). Computational methods and challenges for large-scale circuit mapping. Current Opinion in Neurobiology, 22(1), 162-169. doi:10.1016/j.conb.2011.11.010.

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Alternative Title : Computational methods and challenges for large-scale circuit mapping

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CurrOpinNeurobiol_22_2012_162.pdf (Any fulltext), 2MB
 
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Helmstaedter, Moritz1, Author           
Mitra, Partha P, Author
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1Department of Biomedical Optics, Max Planck Institute for Medical Research, Max Planck Society, ou_1497699              

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 Abstract: The connectivity architecture of neuronal circuits is essential to understand how brains work, yet our knowledge about the neuronal wiring diagrams remains limited and partial. Technical breakthroughs in labeling and imaging methods starting more than a century ago have advanced knowledge in the field. However, the volume of data associated with imaging a whole brain or a significant fraction thereof, with electron or light microscopy, has only recently become amenable to digital storage and analysis. A mouse brain imaged at light−microscopic resolution is about a terabyte of data, and 1mm(3) of the brain at EM resolution is about half a petabyte. This has given rise to a new field of research, computational analysis of large−scale neuroanatomical data sets, with goals that include reconstructions of the morphology of individual neurons as well as entire circuits. The problems encountered include large data management, segmentation and 3D reconstruction, computational geometry and workflow management allowing for hybrid approaches combining manual and algorithmic processing. Here we review this growing field of neuronal data analysis with emphasis on reconstructing neurons from EM data cubes

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Title: Current Opinion in Neurobiology
  Other : Curr. Opin.Neurobiol.
Source Genre: Journal
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Publ. Info: New York, NY : Elsevier Current Trends
Pages: - Volume / Issue: 22 (1) Sequence Number: - Start / End Page: 162 - 169 Identifier: ISSN: 0959-4388
CoNE: https://pure.mpg.de/cone/journals/resource/954925578066