Systems Neuroscience Group, Brisbane, Australia; Centre for Integrative Brain Function, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2017 Apr;2(3):216-224. doi: 10.1016/j.bpsc.2017.01.010. Epub 2017 Feb 7.
Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior.
生物现象是由生物体内在动力学和随机力之间的相互作用产生的——由于外部输入、热能或其他外源性影响而产生的随机波动。大脑中的动态过程源于神经生理学和解剖连接；随机效应通过感觉波动、脑干放电以及随机微观状态（如热噪声）产生。由动态和随机效应组成的系统的动态演化可以用随机动态模型（SDM）来研究。本文是两部分系列的第一部分，介绍了 SDM 的原理及其在健康和疾病大尺度神经系统中的应用。第二篇文章，即第二部分，回顾了 SDM 在脑疾病中的应用。SDM 产生了一个动态状态的分布，我们认为这些状态是模拟大脑如何表示世界状态的理想候选者。当与模型反转的变分方法相结合时，SDM 代表了一种从健康和疾病中的功能神经影像学数据推断神经元动力学的强大手段。结合更深入的理论考虑，这项工作表明，SDM 将在计算精神病学中发挥独特而有影响力的作用，将感知和行为模型与经验观察统一起来。
