Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity.


Journal

Neural computation
ISSN: 1530-888X
Titre abrégé: Neural Comput
Pays: United States
ID NLM: 9426182

Informations de publication

Date de publication:
05 2020
Historique:
pubmed: 19 3 2020
medline: 13 8 2021
entrez: 19 3 2020
Statut: ppublish

Résumé

As synchronized activity is associated with basic brain functions and pathological states, spike train synchrony has become an important measure to analyze experimental neuronal data. Many measures of spike train synchrony have been proposed, but there is no gold standard allowing for comparison of results from different experiments. This work aims to provide guidance on which synchrony measure is best suited to quantify the effect of epileptiform-inducing substances (e.g., bicuculline, BIC) in in vitro neuronal spike train data. Spike train data from recordings are likely to suffer from erroneous spike detection, such as missed spikes (false negative) or noise (false positive). Therefore, different timescale-dependent (cross-correlation, mutual information, spike time tiling coefficient) and timescale-independent (Spike-contrast, phase synchronization (PS), A-SPIKE-synchronization, A-ISI-distance, ARI-SPIKE-distance) synchrony measures were compared in terms of their robustness to erroneous spike trains. For this purpose, erroneous spike trains were generated by randomly adding (false positive) or deleting (false negative) spikes (in silico manipulated data) from experimental data. In addition, experimental data were analyzed using different spike detection threshold factors in order to confirm the robustness of the synchrony measures. All experimental data were recorded from cortical neuronal networks on microelectrode array chips, which show epileptiform activity induced by the substance BIC. As a result of the in silico manipulated data, Spike-contrast was the only measure that was robust to false-negative as well as false-positive spikes. Analyzing the experimental data set revealed that all measures were able to capture the effect of BIC in a statistically significant way, with Spike-contrast showing the highest statistical significance even at low spike detection thresholds. In summary, we suggest using Spike-contrast to complement established synchrony measures because it is timescale independent and robust to erroneous spike trains.

Identifiants

pubmed: 32187002
doi: 10.1162/neco_a_01277
doi:

Substances chimiques

Bicuculline Y37615DVKC

Types de publication

Comparative Study Letter Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

887-911

Auteurs

Manuel Ciba (M)

Biomems Lab, University of Applied Science Aschaffenburg, 63743 Aschaffenburg, Germany manuel.ciba@th-ab.de.

Robert Bestel (R)

Biomems Lab, University of Applied Science Aschaffenburg, 63743 Aschaffenburg, Germany robert.bestel@mailbox.org.

Christoph Nick (C)

Biomems Lab, University of Applied Science Aschaffenburg, 63743 Aschaffenburg, Germany christoph.nick@web.de.

Guilherme Ferraz de Arruda (GF)

ISI Foundation, 10126 Turin, Italy gui.f.arruda@gmail.com.

Thomas Peron (T)

Institute of Mathematics and Computer Science, University of São Paulo, São Carlos SP 13566-590, Brazil thomaskaue@gmail.com.

Comin César Henrique (CC)

Department of Computer Science, Federal University of São Carlos, São Carlos SP 13565-905, Brazil chcomin@gmail.com.

Luciano da Fontoura Costa (LDF)

Instituto de Física de São Carlos, University of São Paulo, São Carlos SP 13566-590, Brazil ldfcosta@gmail.com.

Francisco Aparecido Rodrigues (FA)

Institute of Mathematics and Computer Science, University of São Paulo, São Carlos SP 13566-590, Brazil francisco.rodrigues.usp@gmail.com.

Christiane Thielemann (C)

Biomems Lab, University of Applied Science Aschaffenburg, 63743 Aschaffenburg, Germany Christiane.Thielemann@th-ab.de.

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