High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package

Abstract Synchronized brain activity in the form of alternating epochs of massive persistent network activity and periods of generalized neural silence, has been extensively studied as a fundamental form of circuit dynamics, important for many cognitive functions including short-term memory, memory...

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Autores principales:	P. Tsakanikas, C. Sigalas, P. Rigas, I. Skaliora
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1d0dceae3bd14d8289f5184c921f3623
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spelling	oai:doaj.org-article:1d0dceae3bd14d8289f5184c921f36232021-12-02T15:05:11ZHigh-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package10.1038/s41598-017-03269-92045-2322https://doaj.org/article/1d0dceae3bd14d8289f5184c921f36232017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03269-9https://doaj.org/toc/2045-2322Abstract Synchronized brain activity in the form of alternating epochs of massive persistent network activity and periods of generalized neural silence, has been extensively studied as a fundamental form of circuit dynamics, important for many cognitive functions including short-term memory, memory consolidation, or attentional modulation. A key element in such studies is the accurate determination of the timing and duration of those network events. The local field potential (LFP) is a particularly attractive method for recording network activity, because it allows for long and stable recordings from multiple sites, allowing researchers to estimate the functional connectivity of local networks. Here, we present a computational method for the automatic detection and quantification of in-vitro LFP events, aiming to overcome the limitations of current approaches (e.g. slow analysis speed, arbitrary threshold-based detection and lack of reproducibility across and within experiments). The developed method is based on the implementation of established signal processing and machine learning approaches, is fully automated and depends solely on the data. In addition, it is fast, highly efficient and reproducible. The performance of the software is compared against semi-manual analysis and validated by verification of prior biological knowledge.P. TsakanikasC. SigalasP. RigasI. SkalioraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q P. Tsakanikas C. Sigalas P. Rigas I. Skaliora High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
description	Abstract Synchronized brain activity in the form of alternating epochs of massive persistent network activity and periods of generalized neural silence, has been extensively studied as a fundamental form of circuit dynamics, important for many cognitive functions including short-term memory, memory consolidation, or attentional modulation. A key element in such studies is the accurate determination of the timing and duration of those network events. The local field potential (LFP) is a particularly attractive method for recording network activity, because it allows for long and stable recordings from multiple sites, allowing researchers to estimate the functional connectivity of local networks. Here, we present a computational method for the automatic detection and quantification of in-vitro LFP events, aiming to overcome the limitations of current approaches (e.g. slow analysis speed, arbitrary threshold-based detection and lack of reproducibility across and within experiments). The developed method is based on the implementation of established signal processing and machine learning approaches, is fully automated and depends solely on the data. In addition, it is fast, highly efficient and reproducible. The performance of the software is compared against semi-manual analysis and validated by verification of prior biological knowledge.
format	article
author	P. Tsakanikas C. Sigalas P. Rigas I. Skaliora
author_facet	P. Tsakanikas C. Sigalas P. Rigas I. Skaliora
author_sort	P. Tsakanikas
title	High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
title_short	High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
title_full	High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
title_fullStr	High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
title_full_unstemmed	High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
title_sort	high-throughput analysis of in-vitro lfp electrophysiological signals: a validated workflow/software package
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/1d0dceae3bd14d8289f5184c921f3623
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High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package

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