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Grant support

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. 785907 (HBP SGA2), by the German Federal Ministry of Education and Research grant 01GQ1406, and by the German Research Foundation grant CU217/2-1. 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 Strungmann Institute (ESI) for Neuroscience. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Analysis of institutional authors

Anton-Sanchez, LauraCorresponding AuthorBielza, ConchaAuthorLarranaga, PedroAuthor

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Article

A regularity index for dendrites - local statistics of a neuron's input space

Publicated to:Plos Computational Biology. 14 (11): e1006593- - 2018-11-01 14(11), DOI: 10.1371/journal.pcbi.1006593

Authors: Anton-Sanchez, L; Effenberger, F; Bielza, C; Larrañaga, P; Cuntz, H

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Abstract

Neurons collect their inputs from other neurons by sending out arborized dendritic structures. However, the relationship between the shape of dendrites and the precise organization of synaptic inputs in the neural tissue remains unclear. Inputs could be distributed in tight clusters, entirely randomly or else in a regular grid-like manner. 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. We find that the distributions of these points depend strongly on cell types, indicating possible fundamental differences in synaptic input organization. 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 then use morphological models based on optimal wiring principles to study the relation between input distributions and dendritic branching structures. 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 validate these model predictions with connectome data. Finally, we find that in spatial input distributions with increasing regularity, characteristic scaling relationships between branching features are altered significantly. 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.

Keywords

AnimalsCell sizeCellsCircuitComputational biologyComputer simulationConnectivityConnectomeDendritesDipteraImage processing, computer-assistedModels, neurologicalMosaicsNeuronal plasticityNeuronsPattern recognition, automatedPoint pattern-analysisSoftwareSynapses

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Plos Computational Biology due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2018, it was in position 5/59, thus managing to position itself as a Q1 (Primer Cuartil), in the category Mathematical & Computational Biology. Notably, the journal is positioned above the 90th percentile.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 1.13, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions May 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-05-31, the following number of citations:

  • WoS: 3
  • Scopus: 3
  • Google Scholar: 4
  • OpenCitations: 5

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-31:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 28.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 28 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.
  • The number of mentions on the social network X (formerly Twitter): 3 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Germany.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (ANTON SANCHEZ, LAURA) .

the author responsible for correspondence tasks has been ANTON SANCHEZ, LAURA.