Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

Full text
Author(s):
Ciba, Manuel [1] ; Bestel, Robert [1] ; Nick, Christoph [1] ; de Arruda, Guilherme Ferraz [2] ; Peron, Thomas [3] ; Henrique, Comin Cesar [4] ; Costa, Luciano da Fontoura [5] ; Rodrigues, Francisco Aparecido [3] ; Thielemann, Christiane [1]
Total Authors: 9
Affiliation:
[1] Univ Appl Sci Aschaffenburg, Biomems Lab, D-63743 Aschaffenburg - Germany
[2] ISI Fdn, I-10126 Turin - Italy
[3] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[4] Univ Fed Sao Carlos, Dept Comp Sci, BR-13565905 Sao Carlos, SP - Brazil
[5] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 5
Document type: Journal article
Source: NEURAL COMPUTATION; v. 32, n. 5, p. 887-911, MAY 2020.
Web of Science Citations: 0
Abstract

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. (AU)

FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 16/23827-6 - Analysis of epidemic and synchronization processes in complex networks
Grantee:Thomas Kaue Dal Maso Peron
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 18/09125-4 - Representation, characterization and modeling of biological images using complex networks
Grantee:Cesar Henrique Comin
Support Opportunities: Regular Research Grants
FAPESP's process: 13/26416-9 - Modelling of dynamical processes in complex networks
Grantee:Francisco Aparecido Rodrigues
Support Opportunities: Regular Research Grants
FAPESP's process: 12/51301-8 - Cortical networks
Grantee:Francisco Aparecido Rodrigues
Support Opportunities: Regular Research Grants
FAPESP's process: 12/25219-2 - Modeling, analysis and simulation of dynamic process on complex networks
Grantee:Guilherme Ferraz de Arruda
Support Opportunities: Scholarships in Brazil - Doctorate