TY  - JOUR
AU  - DeFelipe, Javier
AU  - López-Cruz, Pedro L.
AU  - Benavides-Piccione, Ruth
AU  - Bielza, Concha
AU  - Larrañaga, Pedro
AU  - Anderson, Stewart
AU  - Burkhalter, Andreas
AU  - Cauli, Bruno
AU  - Fairén, Alfonso
AU  - Feldmeyer, Dirk
AU  - Fishell, Gord
AU  - Fitzpatrick, David
AU  - Freund, Tamás F.
AU  - González-Burgos, Guillermo
AU  - Hestrin, Shaul
AU  - Hill, Sean
AU  - Hof, Patrick R.
AU  - Huang, Josh
AU  - Jones, Edward G.
AU  - Kawaguchi, Yasuo
AU  - Kisvárday, Zoltán
AU  - Kubota, Yoshiyuki
AU  - Lewis, David A.
AU  - Marín, Oscar
AU  - Markram, Henry
AU  - McBain, Chris J.
AU  - Meyer, Hanno S.
AU  - Monyer, Hannah
AU  - Nelson, Sacha B.
AU  - Rockland, Kathleen
AU  - Rossier, Jean
AU  - Rubenstein, John L. R.
AU  - Rudy, Bernardo
AU  - Scanziani, Massimo
AU  - Shepherd, Gordon M.
AU  - Sherwood, Chet C.
AU  - Staiger, Jochen F.
AU  - Tamás, Gábor
AU  - Thomson, Alex
AU  - Wang, Yun
AU  - Yuste, Rafael
AU  - Ascoli, Giorgio A.
TI  - New insights into the classification and nomenclature of cortical GABAergic interneurons
JO  - Nature reviews / Neuroscience
VL  - 14
IS  - 3
SN  - 1471-0048
CY  - London
PB  - Nature Publishing Group, a division of Macmillan Publishers Ltd
M1  - FZJ-2013-01417
SP  - 202 - 216
PY  - 2013
AB  - 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.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000315704600014
C6  - pmid:23385869
DO  - DOI:10.1038/nrn3444
UR  - https://juser.fz-juelich.de/record/132186
ER  -