ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

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Zhuravlev M. O., Akimova A. S., Panina O. S., Kiselev A. R. Oscillatory characteristics in the brain activity of the newborns and their correlation with different gestational ages. Izvestiya VUZ. Applied Nonlinear Dynamics, 2023, vol. 31, iss. 5, pp. 650-660. DOI: 10.18500/0869-6632-003063, EDN: SOMZPJ

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Oscillatory characteristics in the brain activity of the newborns and their correlation with different gestational ages

Zhuravlev Maksim Olegovich, Saratov State University
Akimova Alesia Sergeevna, Saratov State University
Panina Olga Sergeevna, Saratov State Medical University named after V. I. Razumovsky
Kiselev Anton Robertovich, Saratov research Institute of Cardiology

The purpose of this study is to detect the characteristic features of the oscillatory electrical activity of the brain in early postnatal development, depending on the gestational age of newborns.

Methods. The study is based on automatic processing of clinical data from electroencephalography of newborns on the third day after birth. Behavioral characteristics assessed periods of sleep and wakefulness, without a precise division into stages of sleep and various states of wakefulness. The processing of multichannel electroencephalography signals was carried out on the basis of the method of modifying the continuous wavelet transform (CWT), which makes it possible to estimate the average characteristics of the number, duration and energy of oscillatory components (patterns) developing in different frequency ranges.

Results. A paradoxical picture has been demonstrated describing the state of sleep and wakefulness in weakly preterm infants. For this group of children, the number and average energy of patterns detected in the frequency ranges from 1 to 20 Hz behave in a reflected way during sleep compared to children born at the usual time. At the same time, the average duration of oscillatory patterns remains unchanged.

Conclusion. In the first days of a child’s life, it is possible to detect significant differences in the activity of the brain of newborns with slightly different gestational age during sleep/wake behavioral states. Quantitative estimates of the parameters of oscillatory CWT patterns are promising for use as the basis for systems for automatic processing of neonatal brain activity, additional to amplitude electroencephalography estimates. Such systems may be relevant for the search for early signs of anomalies in the development of the central nervous system.

The study was conducted with the financial support of the Russian Science Foundation (Project No. 22-22-00517)
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