A Consistent Definition of Phase Resetting Using Hilbert Transform.

International Scholarly Research Notices Pub Date : 2017-05-03 eCollection Date: 2017-01-01 DOI:10.1155/2017/5865101
Sorinel A Oprisan
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引用次数: 10

Abstract

A phase resetting curve (PRC) measures the transient change in the phase of a neural oscillator subject to an external perturbation. The PRC encapsulates the dynamical response of a neural oscillator and, as a result, it is often used for predicting phase-locked modes in neural networks. While phase is a fundamental concept, it has multiple definitions that may lead to contradictory results. We used the Hilbert Transform (HT) to define the phase of the membrane potential oscillations and HT amplitude to estimate the PRC of a single neural oscillator. We found that HT's amplitude and its corresponding instantaneous frequency are very sensitive to membrane potential perturbations. We also found that the phase shift of HT amplitude between the pre- and poststimulus cycles gives an accurate estimate of the PRC. Moreover, HT phase does not suffer from the shortcomings of voltage threshold or isochrone methods and, as a result, gives accurate and reliable estimations of phase resetting.

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基于希尔伯特变换的相位重置的一致定义。
相位重置曲线(PRC)测量的是神经振荡器在外部扰动作用下的瞬态相位变化。PRC封装了神经振荡器的动态响应,因此,它经常用于预测神经网络中的锁相模式。虽然相位是一个基本概念,但它有多种定义,可能导致相互矛盾的结果。我们使用希尔伯特变换(HT)来定义膜电位振荡的相位和HT振幅来估计单个神经振荡器的PRC。我们发现,膜电位扰动对HT的振幅及其对应的瞬时频率非常敏感。我们还发现,刺激前和刺激后周期之间的高温振幅相移可以准确地估计PRC。此外,高温相位没有电压阈值或等时方法的缺点,因此可以准确可靠地估计相位复位。
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