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An integrated approach to classifying neuronal phenotypes

Nature Reviews Neuroscience volume 6, pages 810–818 (2005)Cite this article

Abstract

Characterizing the functional phenotypes of neurons is essential for understanding how genotypes can be related to the neural basis of behaviour. Traditional classifications of neurons by single features (such as morphology or firing behaviour) are increasingly inadequate for reflecting functional phenotypes, as they do not integrate functions across different neuronal types. Here, we describe a set of rules for identifying and predicting functional phenotypes that combine morphology, intrinsic ion channel species and their distributions in dendrites, and functional properties. This more comprehensive neuronal classification should be an improvement on traditional classifications for relating genotype to functional phenotype.

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Figure 1: Basic phenotypic categories of cells with thick dendrites and high dendritic Na+ channel density, and cells with thin dendrites and low dendritic Na+ channel density.
Figure 2: Cells with thick dendrites and high dendritic Na+ channel density are further subcategorized by back-propagating action potentials and modulation by I h currents.
Figure 3: Cells with thick dendrites and high dendritic Na+ channels have a second 'unmodulated' subcategory characterized by back-propagating action potentials but no I h.
Figure 4: Cells in the category of thin dendrites and low dendritic Na+ channels, with limited back-propagating action potentials and complex firing because of Ih.
Figure 5: Cells belonging to a slow integration phenotype, characterized by thin dendrites and low dendritic Na+ channels, which make up a simple firing subcategory because they have no Ih.
Figure 6: Schema for the differentiation of neuronal phenotypes.

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Acknowledgements

We are grateful for support from the National Institutes of Health, the Human Brain Project (funded by the National Institute of Deafness and Other Communication Disorders, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, and the National Institute on Aging) and the Office of Naval Research (Multi-university Research Initiative). We thank W. Chen, T. Morse, D. Willhite and M. Hines for valuable discussions.

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  1. Department of Neurobiology, Yale University School of Medicine, P.O. BOX 208001, New Haven, 06520-8001, Connecticut, USA

    Michele Migliore & Gordon M. Shepherd

  2. the Institute of Biophysics, National Research Council, via U. La Malfa 153, Palermo, 90146, Italy

    Michele Migliore

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Migliore, M., Shepherd, G. An integrated approach to classifying neuronal phenotypes. Nat Rev Neurosci 6, 810–818 (2005). https://doi.org/10.1038/nrn1769

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