New insights into the classification and nomenclature of cortical GABAergic interneurons
Open accessAbstract
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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Chandelier interneurons are the most morphologically recognizable interneurons due to candlestick-like synaptic terminal arrays targeting the axon initial segment of pyramidal cells.
“Chandelier INs, also known as axo-axonic neurons, are the most recognizable INs in terms of morphology (DeFelipe et al., 2013) due to the unique candlestick-like synaptic terminal arrays they form to specifically target the axon initial segment of pyramidal cells.”
From GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits (2016) · cites this paper as DeFelipe et al., 2013
The Historical overview (page unavailable) says chandelier cells are readily distinguished by clear morphological attributes, but it does not rank them as the most recognizable interneurons. The Anatomical section (page unavailable) identifies chandelier cells as axo-axonic cells targeting the axon initial segment of pyramidal cells; the cited passages do not describe candlestick-like terminal arrays. (LLM, conf=0.82)
Experimental — accuracy not yet measuredA systematic attempt to classify neocortical interneurons by morphology alone showed too many ambiguities for experts to agree on most subtype identities.
“an attempt to produce a systematic classification of neocortical INs based on morphological features alone by a large number of investigators showed that there are too many ambiguities for “experts” to agree on the identity of most IN subtypes when strictly relying on morphological data”
From GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits (2016) · cites this paper as DeFelipe et al., 2013
The definition of a cell type in the brain remains controversial.
“the definition of a cell type in the brain remains controversial20,21”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [21]
The field has not readily converged on a consensus number or definition of neuronal cell types.
“the field has not readily converged on a consensus number, or even definition, of neuronal cell types”
From Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells (2020) · cites this paper as DeFelipe et al., 2013
In V1 L4 of adult mice, seven inhibitory types of neurons were identified using whole-cell recordings with morphological recovery.
“Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1).”
From Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas (2019) · cites this paper as [41]
Rigorous, quantitative and scalable analysis of interneuron morphology remains difficult.
“A century after Ramon y Cajal described ‘short axon cells’, rigorous, quantitative and scalable analysis of interneuron morphology remains difficult11.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [11]
The issue of interneuron diversity remains contentious.
“Consequently, the issue of interneuron diversity remains contentious11.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [11]
Differences in morphology among neurons of one class can look continuous and hard to parse, yet they might correspond to more precise, discrete wiring patterns between particular pre- and postsynaptic partners.
“Similarly, morphological variations between neurons of the same class may seem continuous and intractable11 but may belie the more specific and discrete connectivity patterns between certain presynaptic and postsynaptic elements56,67.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [11]
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- Authors
- DeFelipe, J., López-Cruz, P. L., Benavides-Piccione, R., Bielza, C., Larrañaga, P., Anderson, S., Burkhalter, A., Cauli, B., Fairén, A., Feldmeyer, D., Fishell, G., Fitzpatrick, D., Freund, T. F., González-Burgos, G., Hestrin, S., Hill, S., Hof, P. R., Huang, J., Jones, E. G., Kawaguchi, Y., Kisvárday, Z., Kubota, Y., Lewis, D. A., Marín, O., Markram, H., McBain, C. J., Meyer, H. S., Monyer, H., Nelson, S. B., Rockland, K., Rossier, J., Rubenstein, J. L. R., Rudy, B., Scanziani, M., Shepherd, G. M., Sherwood, C. C., Staiger, J. F., Tamás, G., Thomson, A., Wang, Y., Yuste, R., & Ascoli, G. A.
- Affiliations
- Universidad Politécnica de Madrid (ES)
- Children's Hospital of Philadelphia (US)
- Washington University in St. Louis (US)
- Centre National de la Recherche Scientifique (FR)
- Instituto de Neurociencias (ES)
- Forschungszentrum Jülich (DE)
- NYU Langone Health (US)
- Max Planck Florida Institute for Neuroscience (US)
- HUN-REN Institute of Experimental Medicine (HU)
- Stanford Medicine (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Icahn School of Medicine at Mount Sinai (US)
- National Institute for Physiological Sciences (JP)
- University of Debrecen (HU)
- University of Pittsburgh (US)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (US)
- Technical University of Munich (DE)
- German Cancer Research Center (DE)
- Brandeis University (US)
- Boston University (US)
- Inserm (FR)
- University of California, San Francisco (US)
- New York University (US)
- Howard Hughes Medical Institute (US)
- Yale University (US)
- George Washington University (US)
- University of Göttingen (DE)
- University of Szeged (HU)
- UCL School of Pharmacy (GB)
- Wenzhou Medical University (CN)
- George Mason University (US)
- Corresponding author
- DeFelipe, Javier
- Larrañaga, Pedro
- Ascoli, Giorgio A.
- ORCID
- DeFelipe, Javier
- Bielza, Concha
- Larrañaga, Pedro
- Anderson, Stewart
- Burkhalter, Andreas
- Cauli, Bruno
- Feldmeyer, Dirk
- Fishell, Gord
- Freund, Tamás F.
- Hill, Sean
- Hof, Patrick R.
- Jones, Edward G.
- Kawaguchi, Yasuo
- Kisvárday, Zoltán
- Kubota, Yoshiyuki
- Lewis, David A.
- Markram, Henry
- McBain, Chris J.
- Meyer, Hanno S.
- Monyer, Hannah
- Nelson, Sacha B.
- Rockland, Kathleen
- Rossier, Jean
- Rubenstein, John L. R.
- Rudy, Bernardo
- Scanziani, Massimo
- Shepherd, Gordon M.
- Sherwood, Chet C.
- Staiger, Jochen F.
- Tamás, Gábor
- Yuste, Rafael
- Ascoli, Giorgio A.
- Venue
- Nature Reviews Neuroscience
- Published
- 2013-02-06
- Volume
- 14
- Issue
- 3
- Pages
- 202-216
- ISSN
- 1471-003X (ISSN-L)
- 1471-0048
- PMC
- PMC3619199
- OpenAlex
- W1995031373
- Cited by
- 833
- References
- 40
- Citations by year
- 2026: 23 · 2025: 44 · 2024: 48 · 2023: 57 · 2022: 62 · 2021: 56 · 2020: 72 · 2019: 71 · 2018: 63 · 2017: 72 · 2016: 67 · 2015: 86 · 2014: 79 · 2013: 33
- FWCI
- 8.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature reviews. Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- JuSER (Forschungszentrum Jülich) (publishedVersion)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- HAL (submittedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- University of Debrecen Electronic Archive (University of Debrecen) (submittedVersion, other-oa)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Archivo Digital UPM (Universidad Politécnica de Madrid) (submittedVersion, cc-by-nc-nd)
- GRO (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- École Polytechnique Fédérale de Lausanne
- Ministerio de Economía y Competitividad (C04-04, TIN2010-20900-C04-04)
- National Institutes of Health (5r01ns030989-22)
- U.S. Public Health Service (R01-39600)
- Japan Society for the Promotion of Science (21240030)
- National Institute of Mental Health (R01MH043784)
- National Eye Institute (R01EY012114, R01EY011787)
- National Institute on Deafness and Other Communication Disorders (R01DC009977, P01DC004732)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK063720)
- National Institute of Neurological Disorders and Stroke (R01-NS030989, R01NS039600, R01NS075007)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- GABAergic interneurons, cortical interneurons, neuron classification, cerebral cortex, neuronal morphology, Bayesian analysis, clustering algorithms, supervised classification, community consensus, taxonomy
- MeSH terms
- Algorithms, Animals, Bayes Theorem, Cerebral Cortex, gamma-Aminobutyric Acid, Humans, Interneurons, Terminology as Topic, Cluster Analysis
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