作者
Javier DeFelipe,Pedro L. López-Cruz,Ruth Benavides‐Piccione,Concha Bielza,Pedro Larrañaga,Stewart A. Anderson,Andreas Burkhalter,Bruno Cauli,Alfonso Fairén,Dirk Feldmeyer,Gord Fishell,David Fitzpatrick,Tamás F. Freund,Guillermo González‐Burgos,Bruno Cauli,Sean Hill,Oscar Marı́n,Z. Josh Huang,Edward G. Jones,Yasuo Kawaguchi,Zoltán F. Kisvárday,Yoshiyuki Kubota,David A. Lewis,Oscar Marı́n,Z. Josh Huang,Chris J. McBain,Hanno S. Meyer,Hannah Monyer,Sacha B. Nelson,Kathleen S. Rockland,Oscar Marı́n,John L. R. Rubenstein,Bernardo Rudy,Hanno S. Meyer,Gordon M. Shepherd,Chet C. Sherwood,Kathleen S. Rockland,Gábor Tamás,Alex Thomson,Bernardo Rudy,Rafael Yuste,Giorgio A. Ascoli
摘要
The classification of cortical neurons, including interneurons, remains a thorny issue in neuroscience. This Analysis article presents and tests a possible taxonomical solution for classifying cortical GABAergic interneurons based on a web-based interactive system that allows experts to classify neurons with pre-determined morphological criteria. 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.