Kanari L Ramaswamy S Shi Y Morand S Meystre J Perin R Abdellah M Wang Y Hess K Markram H 2019 A consensus on the number of morphologically different types of pyramidal cells (PCs) in the neocortex has not yet been reached, despite over a century of anatomical studies, due to the lack of agreement on the subjective classifications of neuron types, which is based on expert analyses of neuronal morphologies. Even for neurons that are visually distinguishable, there is no common ground to consistently define morphological types. The objective classification of PCs can be achieved with methods from algebraic topology, and the dendritic arborization is sufficient for the reliable identification of distinct types of cortical PCs. Therefore, we objectively identify 17 types of PCs in the rat somatosensory cortex. In addition, we provide a solution to the challenging problem of whether 2 similar neurons belong to different types or to a continuum of the same type. Our topological classification does not require expert input, is stable, and helps settle the long-standing debate on whether cell-types are discrete or continuous morphological variations of each other. https://sonar.ch/global/documents/211427 eng info:eu-repo/semantics/altIdentifier/doi/10.1093/cercor/bhy339 info:eu-repo/semantics/altIdentifier/pmid/30715238 Cerebral cortex (New York, N.Y. : 1991). - 2019 neuronal classification neuronal morphology pyramidal cells rat somatosensory cortex topological data analysis Animals Imaging, Three-Dimensional Lysine Neocortex Pattern Recognition, Automated Pyramidal Cells Rats Somatosensory Cortex Supervised Machine Learning Objective Morphological Classification of Neocortical Pyramidal Cells. http://purl.org/coar/resource_type/c_6501