Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK.
Neuroscientist. 2022 Aug;28(4):382-399. doi: 10.1177/1073858421994784. Epub 2021 Feb 16.
The study of complex systems deals with emergent behavior that arises as a result of nonlinear spatiotemporal interactions between a large number of components both within the system, as well as between the system and its environment. There is a strong case to be made that neural systems as well as their emergent behavior and disorders can be studied within the framework of complexity science. In particular, the field of neuroimaging has begun to apply both theoretical and experimental procedures originating in complexity science-usually in parallel with traditional methodologies. Here, we illustrate the basic properties that characterize complex systems and evaluate how they relate to what we have learned about brain structure and function from neuroimaging experiments. We then argue in favor of adopting a complex systems-based methodology in the study of neuroimaging, alongside appropriate experimental paradigms, and with minimal influences from noncomplex system approaches. Our exposition includes a review of the fundamental mathematical concepts, combined with practical examples and a compilation of results from the literature.
复杂系统研究涉及到涌现行为，这些行为是由于系统内部以及系统与环境之间大量组件之间的非线性时空相互作用而产生的。有充分的理由可以认为，神经系统及其涌现行为和障碍可以在复杂性科学的框架内进行研究。特别是，神经影像学领域已经开始应用复杂性科学中的理论和实验程序，通常与传统方法并行。在这里，我们说明了描述复杂系统的基本特性，并评估了它们与我们从神经影像学实验中了解到的大脑结构和功能的关系。然后，我们主张在神经影像学研究中采用基于复杂系统的方法，同时结合适当的实验范式，并尽可能减少非复杂系统方法的影响。我们的论述包括对基本数学概念的回顾，结合实际例子和文献结果的汇编。
