Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

Handle URI:
http://hdl.handle.net/10754/617307
Title:
Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression
Authors:
Onesto, Valentina; Cosentino, Carlo; Di Fabrizio, Enzo M. ( 0000-0001-5886-4678 ) ; Cesarelli, Mario; Amato, Francesco; Gentile, Francesco
Abstract:
Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.
KAUST Department:
Physical Sciences and Engineering (PSE) Division
Citation:
Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression 2016, 2016:1 BioMed Research International
Publisher:
Hindawi Publishing Corporation
Journal:
BioMed Research International
Issue Date:
10-May-2016
DOI:
10.1155/2016/2769698
Type:
Article
ISSN:
2314-6133; 2314-6141
Sponsors:
This work has been partially funded from the Italian Minister of Health (Project no. GR-2010-2320665).
Additional Links:
http://www.hindawi.com/journals/bmri/2016/2769698/
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorOnesto, Valentinaen
dc.contributor.authorCosentino, Carloen
dc.contributor.authorDi Fabrizio, Enzo M.en
dc.contributor.authorCesarelli, Marioen
dc.contributor.authorAmato, Francescoen
dc.contributor.authorGentile, Francescoen
dc.date.accessioned2016-07-21T10:18:56Z-
dc.date.available2016-07-21T10:18:56Z-
dc.date.issued2016-05-10-
dc.identifier.citationInformation in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression 2016, 2016:1 BioMed Research Internationalen
dc.identifier.issn2314-6133-
dc.identifier.issn2314-6141-
dc.identifier.doi10.1155/2016/2769698-
dc.identifier.urihttp://hdl.handle.net/10754/617307-
dc.description.abstractNeurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.en
dc.description.sponsorshipThis work has been partially funded from the Italian Minister of Health (Project no. GR-2010-2320665).en
dc.language.isoenen
dc.publisherHindawi Publishing Corporationen
dc.relation.urlhttp://www.hindawi.com/journals/bmri/2016/2769698/en
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/en
dc.titleInformation in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depressionen
dc.typeArticleen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalBioMed Research Internationalen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100 Catanzaro, Italyen
dc.contributor.institutionDepartment of Electrical Engineering and Information Technology, University of Naples, 80125 Naples, Italyen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorDi Fabrizio, Enzo M.en
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