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New insights into the classification and nomenclature of cortical GABAergic interneurons

Nature Reviews Neuroscience volume 14, pages 202–216 (2013)Cite this article

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Key Points

  • A feature-based classification and agreed-upon nomenclature of GABAergic interneurons of the cerebral cortex is much needed but currently lacking.

  • We designed a web-based interactive system that allowed 42 neuroscience experts to classify a representative sample of 320 cortical neurons and a selected set of simple morphology features based on reconstructions of their axonal arbors.

  • The consensus on and usefulness of these features and neuron names were investigated using agreement analysis, clustering algorithms, Bayesian networks and supervised classification on the resulting data.

  • The results quantitatively confirm the impression that different investigators use their own, mutually inconsistent classification schemes based on morphological criteria. However, the analyses also demonstrate that the community may be reaching consensus for a practical approach to the naming of certain anatomical terms that are useful for neuronal characterization and classification.

  • State-of-the-art machine learning approaches were shown to achieve discrimination capability equivalent to or better than human performance, opening the possibility of creating an objective computer tool for automatic classification of neurons, a Neuroclassifier.

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.

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Figure 1: The web-based interactive system.
Figure 2: Schematics of the morphological features.
Figure 3: Agreement analysis.
Figure 4: Examples of inter-expert agreement and disagreement.
Figure 5: Clustering of neurons considering all features.
Figure 6: Examples of Bayesian networks.

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Acknowledgements

We thank the experts who took part in testing neuron classification using the web-based interactive system (in addition to the authors of the article), in alphabetical order: L. Alonso-Nanclares, C. Dávid, H. Geoffroy, M. Inan, V. Garcia-Marín, Á. Merchán-Pérez, L. McGarry, A. Muñoz, C. Palazzetti, N. Povysheva, D. Rotaru, R. Scott, R. Tremblay and A. Zaitsev. This work was supported by funding from the Spanish Ministry of Economy and Competitiveness (grants TIN2010-20900-C04-04 (to P.L.), SAF2009-09394 (to J.DF.) and the Cajal Blue Brain Project, Spanish partner of the Blue Brain Project initiative from EPFL (to J.DF. and P.L.)) and the National Institutes of Health under Grant R01-39600 (to G.A.A.).

Author information

Authors and Affiliations

  1. Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica (CTB), Universidad Politécnica de Madrid, Campus Montegancedo S/N, Pozuelo de Alarcón, Madrid, 28223, Spain

    Javier DeFelipe & Ruth Benavides-Piccione

  2. Instituto Cajal (CSIC), Avenida Doctor Arce 37, Madrid, 28002, Spain

    Javier DeFelipe & Ruth Benavides-Piccione

  3. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, Boadilla del Monte, Madrid, 28660, Spain

    Pedro L. López-Cruz, Concha Bielza & Pedro Larrañaga

  4. and Plasticity Molecular Neuroscience Department, Center for Neural Informatics, Structure, Krasnow Institute for Advanced Study MS2A1, George Mason University, Fairfax, 22030-4444, Virginia, USA

    Giorgio A. Ascoli

  5. Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, ARC 517, 3615 Civic Center Boulevard, Philadelphia, Pennsylvania, 19104-5127, USA

    Stewart Anderson

  6. Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, 63110, Missouri, USA

    Andreas Burkhalter

  7. Réseau Cortical et Couplage Neurovasculaire, Laboratoire de Neurobiologie des Processus Adaptatifs UMR 7102 CNRS-UPMC, 9 Quai Saint-Bernard, Paris, 75 005, France

    Bruno Cauli

  8. Instituto de Neurociencias, CSIC & Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, 03550, Spain

    Alfonso Fairén & Oscar Marín

  9. Research Centre Juelich, Institute of Neuroscience and Medicine, INM-2, Function of Neuronal Microcircuits Group, Leo-Brandt-Strasse, Juelich, D-52425, Germany

    Dirk Feldmeyer

  10. Department of Psychiatry and Psychotherapy, Rheinisch-Westfaelische Technische Hochschule, Aachen University, Pauwelsstr. 30, Aachen, D-52074, Germany

    Dirk Feldmeyer

  11. NYU Neuroscience Institute Department of Physiology and Neuroscience, New York University Langone Medical Center, 10016, New York, New York, USA

    Gord Fishell

  12. Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, 33468, Florida, USA

    David Fitzpatrick

  13. Hungarian Academy of Sciences, Institute of Experimental Medicine, Szigony u. 43, Budapest, H-1083, Hungary

    Tamás F. Freund

  14. Department of Psychiatry, University of Pittsburgh School of Medicine, Biomedical Science Tower, 200 Lothrop Street, Pittsburgh, Pennsylvania, 15261, USA

    Guillermo González-Burgos & David A. Lewis

  15. Department of Comparative Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Edwards 312/314, Stanford, 94305, California, USA

    Shaul Hestrin

  16. Brain Mind Institute Ecole Polytechnique, Fédérale de Lausanne, Lausanne, CH-1015, Switzerland

    Sean Hill & Henry Markram

  17. Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA

    Patrick R. Hof

  18. Beckman Building, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, 11724, New York, USA

    Josh Huang

  19. Division of Cerebral Circuitry, National Institute for Physiological Sciences, Myodaiji, Okazaki, 444-8787, Japan

    Yasuo Kawaguchi & Yoshiyuki Kubota

  20. Department of Anatomy, Histology and Embryology, University of Debrecen, Debrecen, Hungary

    Zoltán Kisvárday

  21. Eunice Kennedy Shriver National Institute of Child Health and Human Development, 35 Lincoln Drive, Bethesda, 20892-3715, Maryland, USA

    Chris J. McBain

  22. Department of Neurosurgery, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany

    Hanno S. Meyer

  23. Department of Clinical Neurobiology University Hospital and German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, 69120, Germany

    Hannah Monyer

  24. Department of Biology and Center for Behavioral Genomics, Brandeis University, Waltham, 02454, Massachusetts, USA

    Sacha B. Nelson

  25. Department of Anatomy and Neurobiology, Boston University School of Medicine, 72 East Concord Street, Boston, 02118, Massachusetts, USA

    Kathleen Rockland

  26. CPN INSERM U894, Hôpital Sainte Anne, 2 ter rue d'Alésia, Paris, 75014, France

    Jean Rossier

  27. Genetics, Development and Behavioral Sciences Building, 1550 4th Street

    John L. R. Rubenstein

  28. University of California, San Francisco, 94143-2611, California, USA

    John L. R. Rubenstein

  29. New York University, 522 First Avenue, Smilow Research Building, New York, 10016, New York, USA

    Bernardo Rudy

  30. Division of Biology, Howard Hughes Medical Institute, University of California, San Diego, Neurobiology Section 0634, 9500 Gilman Drive, La Jolla, 92093-0634, California, USA

    Massimo Scanziani

  31. Department of Neuroscience, Yale University School of Medicine, New Haven, 06520-8001, Connecticut, USA

    Gordon M. Shepherd

  32. Department of Anthropology, Center for the Advanced Study of Hominid Paleobiology and GW Institute for Neuroscience, The George Washington University, 20052, Washington, DC, USA

    Chet C. Sherwood

  33. Abteilung Neuroanatomie, Georg-August-Universität Göttingen – Zentrum Anatomie, Kreuzbergring 36, Göttingen, D-37075, Germany

    Jochen F. Staiger

  34. Department of Physiology, Anatomy and Neuroscience. University of Szeged, Szeged, H-6726, Hungary

    Gábor Tamás

  35. Department of Pharmacology, University College of London School of Pharmacy, London, WC1N 1AX, UK

    Alex Thomson

  36. School of Optometry and Ophthalmology, Wenzhou Medical College, Wenzhou, 325027, Zhejiang, China

    Yun Wang

  37. Steward St. Elizabeth's Medical Center. Tufts Medical School, Boston, 02135, Massachusetts, USA

    Yun Wang

  38. Howard Hughes Medical Institute, Columbia University, Biological Sciences, 550 West 120th Street, New York, 10027, New York, USA

    Rafael Yuste

  39. In memory of Ted Jones,

    Edward G. Jones

Authors
  1. Javier DeFelipe
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  2. Pedro L. López-Cruz
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  7. Andreas Burkhalter
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  8. Bruno Cauli
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  9. Alfonso Fairén
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  10. Dirk Feldmeyer
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  11. Gord Fishell
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  12. David Fitzpatrick
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  13. Tamás F. Freund
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  14. Guillermo González-Burgos
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  15. Shaul Hestrin
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  16. Sean Hill
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  17. Patrick R. Hof
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  18. Josh Huang
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  19. Edward G. Jones
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  20. Yasuo Kawaguchi
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  21. Zoltán Kisvárday
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  22. Yoshiyuki Kubota
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  23. David A. Lewis
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  24. Oscar Marín
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  25. Henry Markram
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  26. Chris J. McBain
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  27. Hanno S. Meyer
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  28. Hannah Monyer
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  29. Sacha B. Nelson
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  30. Kathleen Rockland
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  31. Jean Rossier
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  32. John L. R. Rubenstein
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  33. Bernardo Rudy
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  34. Massimo Scanziani
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  35. Gordon M. Shepherd
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  36. Chet C. Sherwood
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  37. Jochen F. Staiger
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  38. Gábor Tamás
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  39. Alex Thomson
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  40. Yun Wang
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  41. Rafael Yuste
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  42. Giorgio A. Ascoli
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Corresponding authors

Correspondence to Javier DeFelipe, Pedro Larrañaga or Giorgio A. Ascoli.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information S1

A set of experts on cortical interneurons from different laboratories were asked to classify morphological reconstructions of interneurons (http://cajalbbp.cesvima.upm.es/gardenerclassification). (PDF 474 kb)

Supplementary Information S2

Analysis of raw data (PDF 3589 kb)

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FURTHER INFORMATION

Gardener Classification

ICNF Program on Ontologies of Neural Structures

NeuroLex

NeuroMorpho

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DeFelipe, J., López-Cruz, P., Benavides-Piccione, R. et al. New insights into the classification and nomenclature of cortical GABAergic interneurons. Nat Rev Neurosci 14, 202–216 (2013). https://doi.org/10.1038/nrn3444

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