Oscillatory wavelet-patterns in complex data: mutual estimation of frequencies and energy dynamics
Institute of Cardiological Research, Saratov State Medical University, 410005, Saratov, Russia
2 Department of Pathological Physiology named after Academician A. A. Bogomolets, Saratov State Medical University, 410005, Saratov, Russia
3 Laboratory of Smart Sleep, Saratov State University, 410012, Saratov, Russia
4 Center for Coordination of Fundamental Scientific Activities, National Medical Research Center for Therapy and Preventive Medicine, 101990, Moscow, Russia
Accepted: 28 November 2022
Published online: 9 December 2022
In this work, we propose a modification of the wavelet oscillatory pattern method for analyzing energy characteristics of oscillatory components in complex signals. The energy analysis of oscillatory wavelet patterns allows fast two-dimensional sorting of oscillatory components in frequency and power, thus allows for further statistical calculation of the observed technologies. Counting operations are simply realized on the base of parallel calculations. The presented technique could be used in studying the electrophysiological features of brain activity during animals sleep and awake. The method was used in investigations of brain’s electrophysiological characteristics during sleep and awake in animals. We found out that standard energy analysis could determine NREM sleep and awake condition in rats with normal weight and obesity. However, calculation of energy characteristics of the ECoG patterns in animals of two groups demonstrate a significant transformation of electrophysiological signals oscillatory structure during NREM sleep and awake in rats with severe visceral obesity. We suppose the changes of these characteristics may be associated with shifts in homeostasis indicators due to animal obesity.
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