基于频率动力学的遗传大鼠峰波放电重启检测

Q3 Physics and Astronomy Cybernetics and Physics Pub Date : 2022-11-17 DOI:10.35470/2226-4116-2022-11-3-121-130
A. Dolinina, M. Sysoeva, C. V. van Rijn, I. Sysoev
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引用次数: 1

摘要

癫痫脑中的棘波放电可以通过一次或多次连续重启来维持,其机制应与放电启动机制相似。为了检验这一假设,开发了一种用于自动确定重启的原始算法。为了实现该算法,使用了具有Hann窗口的加窗快速傅立叶变换。该方法是在选定的频率范围(7–12 Hz)内跟踪由频谱图构建的骨架上的频率连续下降。该方法不依赖于振荡幅度的变化,而大多数已知的方法显然依赖于在某些频谱范围内功率的增加。成功检测到放电重新启动,并发现在主频动态方面与初始启动没有什么不同。重新启动的诊断频率比启动低约四次。重启的存在证实了维持长尖峰波放电的不同因素:一些放电由特殊的维持机制支持,另一些是短放电的连续链。
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Detection Of Spike-Wave Discharge Restarts In Genetic Rat Model Based On Frequency Dynamics
The spike-wave discharges in epileptic brain can be maintained by one or more sequential restarts, which should have mechanisms similar to those of discharge initiation. To examine this hypothesis an original algorithm for automatically determining restarts was developed. To implement the algorithm the windowed fast Fourier transform with a Hann window was used. The method was to track the frequency consecutive drops on a skeleton constructed from a spectrogram in a selected frequency range (7–12 Hz). The method does not rely on changes in the amplitude of the oscillations, while most of the known methods clearly rely on an increase in power in certain spectral ranges. Discharge restarts were successfully detected and were found to be not different from initial starts in terms of main frequency dynamics. Restarts were diagnosed in about four less often than starts. The existence of restarts confirms that different factors are responsible for maintenance of long spike-wave discharges: some discharges are supported by the special maintenance mechanism, others are continuous chains of short discharges.
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来源期刊
Cybernetics and Physics
Cybernetics and Physics Chemical Engineering-Fluid Flow and Transfer Processes
CiteScore
1.70
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The scope of the journal includes: -Nonlinear dynamics and control -Complexity and self-organization -Control of oscillations -Control of chaos and bifurcations -Control in thermodynamics -Control of flows and turbulence -Information Physics -Cyber-physical systems -Modeling and identification of physical systems -Quantum information and control -Analysis and control of complex networks -Synchronization of systems and networks -Control of mechanical and micromechanical systems -Dynamics and control of plasma, beams, lasers, nanostructures -Applications of cybernetic methods in chemistry, biology, other natural sciences The papers in cybernetics with physical flavor as well as the papers in physics with cybernetic flavor are welcome. Cybernetics is assumed to include, in addition to control, such areas as estimation, filtering, optimization, identification, information theory, pattern recognition and other related areas.
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