Department of Psychiatry and Behavioural Neuroscience/McMaster University, Hamilton, Ontario, Canada,
Neuropsychobiology. 2021;80(2):134-146. doi: 10.1159/000509572. Epub 2020 Aug 27.
Temperament in healthy individuals and mental illness have been conjectured to lie along a continuum of neurobehavioral regulation. This continuum is frequently regarded in dimensional terms, with temperament and mental illness lying at opposite poles along various dimensional descriptors. However, temperament and mental illness are quintessentially dynamical phenomena, and as such there is value in examining what insights can be arrived at through the lens of our current understanding of dynamical systems. The formal study of dynamical systems has led to the development of a host of markers which serve to characterize and classify dynamical systems and which could be used to study temperament and mental illness. The most useful markers for temperament and mental illness apply to time series data and include geometrical markers such as (strange) attractors and repellors and analytical markers such as fluctuation spectroscopy, scaling, entropy, recurrence time. Temperament and mental illness, however, possess fundamental characteristics that present considerable challenges for current dynamical systems approaches: transience, contextuality and emergence. This review discusses the need for time series data and the implications of these three characteristics on the formal study of the continuum and presents a dynamical systems model based upon Whitehead's Process Theory and the neurochemical Functional Ensemble of Temperament model. The continuum can be understood as second or higher order dynamical phases in a multiscale landscape of superposed dynamical systems. Markers are sought to distinguish the order parameters associated with these phases and the control parameters which describe transitions among these dynamics.
在健康个体和精神疾病中，气质被推测沿着神经行为调节的连续统存在。这个连续统通常以维度术语来描述，气质和精神疾病沿着各种维度描述符的相对极端存在。然而，气质和精神疾病本质上是动态现象，因此，通过我们目前对动力系统的理解来检查可以得出什么见解是有价值的。动力系统的正式研究导致了大量标记的发展，这些标记用于描述和分类动力系统，并可用于研究气质和精神疾病。最有用的气质和精神疾病标记适用于时间序列数据，包括几何标记，如（奇怪的）吸引子和排斥子，以及分析标记，如涨落谱、标度、熵、递归时间。然而，气质和精神疾病具有一些基本特征，这些特征对当前的动力系统方法提出了相当大的挑战：瞬态、语境和涌现。这篇综述讨论了对时间序列数据的需求，以及这三个特征对连续统的正式研究的影响，并提出了一个基于怀特海的过程理论和神经化学功能气质模型的动力系统模型。连续统可以被理解为多尺度叠加动力系统景观中的二阶或更高阶动力相。寻求标记来区分与这些相相关的序参量以及描述这些动力学之间转换的控制参数。
