On the structural connectivity of large-scale models of brain networks at cellular level

Abstract The brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model netwo...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Giuseppe Giacopelli, Domenico Tegolo, Emiliano Spera, Michele Migliore
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3789f692d92f487591ad06ce40e94f5f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3789f692d92f487591ad06ce40e94f5f
record_format	dspace
spelling	oai:doaj.org-article:3789f692d92f487591ad06ce40e94f5f2021-12-02T14:28:19ZOn the structural connectivity of large-scale models of brain networks at cellular level10.1038/s41598-021-83759-z2045-2322https://doaj.org/article/3789f692d92f487591ad06ce40e94f5f2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83759-zhttps://doaj.org/toc/2045-2322Abstract The brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.Giuseppe GiacopelliDomenico TegoloEmiliano SperaMichele MiglioreNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Giuseppe Giacopelli Domenico Tegolo Emiliano Spera Michele Migliore On the structural connectivity of large-scale models of brain networks at cellular level
description	Abstract The brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.
format	article
author	Giuseppe Giacopelli Domenico Tegolo Emiliano Spera Michele Migliore
author_facet	Giuseppe Giacopelli Domenico Tegolo Emiliano Spera Michele Migliore
author_sort	Giuseppe Giacopelli
title	On the structural connectivity of large-scale models of brain networks at cellular level
title_short	On the structural connectivity of large-scale models of brain networks at cellular level
title_full	On the structural connectivity of large-scale models of brain networks at cellular level
title_fullStr	On the structural connectivity of large-scale models of brain networks at cellular level
title_full_unstemmed	On the structural connectivity of large-scale models of brain networks at cellular level
title_sort	on the structural connectivity of large-scale models of brain networks at cellular level
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3789f692d92f487591ad06ce40e94f5f
work_keys_str_mv	AT giuseppegiacopelli onthestructuralconnectivityoflargescalemodelsofbrainnetworksatcellularlevel AT domenicotegolo onthestructuralconnectivityoflargescalemodelsofbrainnetworksatcellularlevel AT emilianospera onthestructuralconnectivityoflargescalemodelsofbrainnetworksatcellularlevel AT michelemigliore onthestructuralconnectivityoflargescalemodelsofbrainnetworksatcellularlevel
_version_	1718391243927453696

On the structural connectivity of large-scale models of brain networks at cellular level

Ejemplares similares