But it has generally been proposed that the connection probability between a dendrite and an axon can be determined by the amount of anatomical overlap between the two. Of the possible connections that a neuron could make by anatomical proximity only a small, relatively invariable number become functional synapses. Dendrites are thought to collect their inputs using the shortest amount of cable and minimizing conduction times in the circuit and they have been proposed to maximize the possible connection repertoire. Theoretical considerations have provided systematic qualitative insight into the question of how dendrite shape relates to specific connectivity. However, so far no branching statistic exists that reliably associates individual morphologies to their specific cell class, indicating that we have not yet identified the morphological features that are characteristic for the differences in how neurons connect to one another. Different cell types play distinct roles in wiring up the brain and are typically visually identifiable by the particular shape of their dendrites. The primary function of dendritic trees is to collect inputs from other neurons in the nervous tissue. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. LA-S acknowledges support from the Spanish MINECO scholarship at the Residencia de Estudiantes and from the UPM grant for the stay in the Ernst Strüngmann Institute (ESI) for Neuroscience. 785907 (HBP SGA2), by the German Federal Ministry of Education and Research grant 01GQ1406, and by the German Research Foundation grant CU217/2-1. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data are available from Version 7.0 (released on ).įunding: This work has been partially supported by the Spanish Ministry of Economy and Competitiveness through the Cajal Blue Brain (C080020-09 the Spanish partner of the EPFL’s Blue Brain initiative) and TIN2016-79684-P projects, by the Regional Government of Madrid through the S2013/ICE-2845-CASI-CAM-CM project, by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. Received: DecemAccepted: OctoPublished: November 12, 2018Ĭopyright: © 2018 Anton-Sanchez et al. PLoS Comput Biol 14(11):Įditor: Abigail Morrison, Research Center Jülich, GERMANY In summary, we conclude that local statistics of input distributions and dendrite morphology depend on each other leading to potentially cell type specific branching features.Ĭitation: Anton-Sanchez L, Effenberger F, Bielza C, Larrañaga P, Cuntz H (2018) A regularity index for dendrites - local statistics of a neuron's input space. Finally, we find that in spatial input distributions with increasing regularity, characteristic scaling relationships between branching features are altered significantly. We validate these model predictions with connectome data. Using our models, we find that branch point distributions correlate more closely with the input distributions while termination points in dendrites are generally spread out more randomly with a close to uniform distribution. We then use morphological models based on optimal wiring principles to study the relation between input distributions and dendritic branching structures. Moreover, R is independent of cell size and we find that it is only weakly correlated with other branching statistics, suggesting that it might reflect features of dendritic morphology that are not captured by commonly studied branching statistics. We find that the distributions of these points depend strongly on cell types, indicating possible fundamental differences in synaptic input organization. Here, we analyze dendritic branching structures using a regularity index R, based on average nearest neighbor distances between branch and termination points, characterizing their spatial distribution. Inputs could be distributed in tight clusters, entirely randomly or else in a regular grid-like manner. However, the relationship between the shape of dendrites and the precise organization of synaptic inputs in the neural tissue remains unclear. Neurons collect their inputs from other neurons by sending out arborized dendritic structures.
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