Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia.
Department of Psychology, Wake Forest University, Winston-Salem, United States of America.
PLoS One. 2018 Jul 5;13(7):e0198929. doi: 10.1371/journal.pone.0198929. eCollection 2018.
Probabilistic formalism of quantum mechanics is used to quantitatively link the global scale mass potential with the underlying electrical activity of excitable cells. Previous approaches implemented methods of classical physics to reconstruct the mass potential in terms of explicit physical models of participating cells and the volume conductor. However, the multiplicity of cellular processes with extremely intricate mixtures of deterministic and random factors prevents the creation of consistent biophysical parameter sets. To avoid the uncertainty inherent in physical attributes of cell ensembles, we undertake here a radical departure from deterministic equations of classical physics, instead applying the probabilistic reasoning of quantum mechanics. Crucial steps include: (1) the relocation of the elementary bioelectric sources from a cellular to a molecular level; (2) the creation of microscale particle models in terms of a non-homogenous birth-and-death process. To link the microscale processes with macroscale potentials, time-frequency analysis was applied for estimation of the empirical characteristic functions for component waveforms of electroencephalogram (EEG), eye-blink electromyogram (EMG), and electrocardiogram (ECG). We describe universal models for the amplitude spectra and phase functions of functional components of mass potentials. The corresponding time domain relationships disclose the dynamics of mass potential components as limit distribution functions produced by specific microscale transients. The probabilistic laws governing the microscale machinery, founded on an empirical basis, are presented. Computer simulations of particle populations with time dependent transition probabilities reveal that hidden deterministic chaos underlies development of the components of mass potentials. We label this kind of behaviour "transient deterministic chaos".
量子力学的概率形式主义被用于将全局质量势与可兴奋细胞的潜在电活动定量联系起来。以前的方法采用经典物理学的方法,根据参与细胞和容积导体的显式物理模型来重建质量势。然而,由于细胞过程的多样性以及确定性和随机性因素的极其复杂的混合,阻止了一致的生物物理参数集的创建。为了避免细胞群体的物理属性固有的不确定性,我们在这里从经典物理学的确定性方程中进行了彻底的背离,而是应用了量子力学的概率推理。关键步骤包括:(1)将基本生物电源从细胞水平转移到分子水平;(2)以非均匀的生死过程术语创建微尺度粒子模型。为了将微观过程与宏观势联系起来,应用时频分析来估计脑电图(EEG)、眼动肌电图(EMG)和心电图(ECG)的组成波形的经验特征函数。我们描述了质量势的功能分量的幅度谱和相位函数的通用模型。相应的时域关系揭示了质量势分量的动力学作为由特定微尺度瞬态产生的极限分布函数。以经验为基础建立的,支配微观机制的概率定律被呈现出来。具有时变跃迁概率的粒子群的计算机模拟表明,质量势分量的发展隐藏着确定性混沌。我们将这种行为标记为“瞬态确定性混沌”。