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Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks
Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performa...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2715865/ https://www.ncbi.nlm.nih.gov/pubmed/19652720 http://dx.doi.org/10.1371/journal.pone.0006482 |
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author | Garofalo, Matteo Nieus, Thierry Massobrio, Paolo Martinoia, Sergio |
author_facet | Garofalo, Matteo Nieus, Thierry Massobrio, Paolo Martinoia, Sergio |
author_sort | Garofalo, Matteo |
collection | PubMed |
description | Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings. |
format | Text |
id | pubmed-2715865 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27158652009-08-04 Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks Garofalo, Matteo Nieus, Thierry Massobrio, Paolo Martinoia, Sergio PLoS One Research Article Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings. Public Library of Science 2009-08-04 /pmc/articles/PMC2715865/ /pubmed/19652720 http://dx.doi.org/10.1371/journal.pone.0006482 Text en Garofalo et al. http://creativecommons.org/licenses/by/4.0/ 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 properly credited. |
spellingShingle | Research Article Garofalo, Matteo Nieus, Thierry Massobrio, Paolo Martinoia, Sergio Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title | Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title_full | Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title_fullStr | Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title_full_unstemmed | Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title_short | Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks |
title_sort | evaluation of the performance of information theory-based methods and cross-correlation to estimate the functional connectivity in cortical networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2715865/ https://www.ncbi.nlm.nih.gov/pubmed/19652720 http://dx.doi.org/10.1371/journal.pone.0006482 |
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