Emergence of Small-World Anatomical Networks in Self-Organizing Clustered Neuronal Cultures

Santos Sierra, Daniel de; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A.; Anava, Sarit; Ayali, Amir; Papo, David y Boccaletti, Stefano (2014). Emergence of Small-World Anatomical Networks in Self-Organizing Clustered Neuronal Cultures. "Plos One", v. 9 (n. 1); pp. 1-8. ISSN 1932-6203. https://doi.org/10.1371/journal.pone.0085828.

Descripción

Título: Emergence of Small-World Anatomical Networks in Self-Organizing Clustered Neuronal Cultures
Autor/es:
  • Santos Sierra, Daniel de
  • Sendiña-Nadal, Irene
  • Leyva, Inmaculada
  • Almendral, Juan A.
  • Anava, Sarit
  • Ayali, Amir
  • Papo, David
  • Boccaletti, Stefano
Tipo de Documento: Artículo
Título de Revista/Publicación: Plos One
Fecha: Enero 2014
Volumen: 9
Materias:
Escuela: Centro de Domótica Integral (CeDInt) (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations.

Más información

ID de Registro: 38713
Identificador DC: http://oa.upm.es/38713/
Identificador OAI: oai:oa.upm.es:38713
Identificador DOI: 10.1371/journal.pone.0085828
URL Oficial: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0085828
Depositado por: Memoria Investigacion
Depositado el: 15 Jun 2017 07:18
Ultima Modificación: 15 Jun 2017 07:18
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