Modified wavelet analysis of ECoG-pattern as promising tool for detection of the blood–brain barrier leakage

Abstract A new approach for detection oscillatory patterns and estimation of their dynamics based by a modified CWT skeleton method is presented. The method opens up additional perspectives for the analysis of subtle changes in the oscillatory activity of complex nonstationary signals. The method wa...

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Autores principales: Anastasiya Runnova, Maksim Zhuravlev, Rodion Ukolov, Inna Blokhina, Alexander Dubrovski, Nikita Lezhnev, Evgeniya Sitnikova, Elena Saranceva, Anton Kiselev, Anatoly Karavaev, Anton Selskii, Oxana Semyachkina-Glushkovskaya, Thomas Penzel, Jurgen Kurths
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/fe6126dc0236421392f1671ef80b4dcf
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Sumario:Abstract A new approach for detection oscillatory patterns and estimation of their dynamics based by a modified CWT skeleton method is presented. The method opens up additional perspectives for the analysis of subtle changes in the oscillatory activity of complex nonstationary signals. The method was applied to analyze unique experimental signals obtained in usual conditions and after the non-invasive increase in the blood–brain barrier (BBB) permeability in 10 male Wistar rats. The results of the wavelet-analysis of electrocorticography (ECoG) recorded in a normal physiological state and after an increase in the BBB permeability of animals demonstrate significant changes between these states during wakefulness of animals and an essential smoothing of these differences during sleep. Sleep is closely related to the processes of observed changes in the BBB permeability.