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Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC)
PublisherIEEE
ISBN (Electronic)978-1-4577-0220-4
ISBN (Print)978-1-4577-0219-8
DOIs
Publication statusPublished - 2016
Publication typeA4 Article in a conference publication
EventAnnual International Conference of the IEEE Engineering in Medicine and Biology Society -
Duration: 1 Jan 1900 → …

Publication series

Name
ISSN (Electronic)1558-4615

Conference

ConferenceAnnual International Conference of the IEEE Engineering in Medicine and Biology Society
Period1/01/00 → …

Abstract

In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relations with in vivo rat hippocampal recordings, and observe the time courses of the correlations between different regions of hippocampus in three sequential recordings. Additionally, we evaluate the results with a commonly employed causality analysis method to assess the possible correlated findings. Results show that time correlated spectral entropy reveals different levels of interrelations in neuronal networks, which can be interpreted as different levels of neuronal network synchrony.

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