| Literature DB >> 23385869 |
Javier DeFelipe1, Pedro L López-Cruz, Ruth Benavides-Piccione, Concha Bielza, Pedro Larrañaga, Stewart Anderson, Andreas Burkhalter, Bruno Cauli, Alfonso Fairén, Dirk Feldmeyer, Gord Fishell, David Fitzpatrick, Tamás F Freund, Guillermo González-Burgos, Shaul Hestrin, Sean Hill, Patrick R Hof, Josh Huang, Edward G Jones, Yasuo Kawaguchi, Zoltán Kisvárday, Yoshiyuki Kubota, David A Lewis, Oscar Marín, Henry Markram, Chris J McBain, Hanno S Meyer, Hannah Monyer, Sacha B Nelson, Kathleen Rockland, Jean Rossier, John L R Rubenstein, Bernardo Rudy, Massimo Scanziani, Gordon M Shepherd, Chet C Sherwood, Jochen F Staiger, Gábor Tamás, Alex Thomson, Yun Wang, Rafael Yuste, Giorgio A Ascoli.
Abstract
A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.Entities:
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Year: 2013 PMID： 23385869 PMCID： PMC3619199 DOI： 10.1038/nrn3444
Source DB: PubMed Journal: Nat Rev Neurosci ISSN： 1471-003X Impact factor: 34.870