School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
J Neurosci Methods. 2010 Apr 30;188(1):113-26. doi: 10.1016/j.jneumeth.2010.01.029. Epub 2010 Feb 2.
Simplexity is an emerging concept that expresses a possible complementary relationship between complexity and simplicity. The brain has been known as the most complex structure, and tremendous effort has been spent to study how it works. By understanding complex function of the brain, one can hope to unravel the mystery of its diseases and its biological systems. We propose herein an entropy-based framework for analysis of complexity with a particular application to the study of white matter changes of the human brain. In this analysis, the proposed approach takes into account both morphological structure and image intensity values of MRI scans to construct the complexity profiles of the brain. It has been realized that the quantity and spatial distribution of white matter changes play an important role in cognitive decline (i.e. dementia) and other neuropsychiatric disorders (i.e. multiple sclerosis, depression) as well as in other dementia disorders such as Alzheimers disease. Thus, the results can be utilized as a tool for automated quantification and comparison of various spatial distributions and orientations of age-related white matter changes where manual analysis is difficult and leads to different sensitivities for the respective MRI-based information of the brain.
单纯性是一个新兴概念，表达了复杂性和简单性之间可能存在的互补关系。大脑一直被认为是最复杂的结构，人们花费了大量的精力来研究它是如何工作的。通过了解大脑的复杂功能，人们有望揭开其疾病和生物系统的奥秘。本文提出了一种基于熵的复杂性分析框架，并特别应用于研究人脑的白质变化。在这种分析中，所提出的方法考虑了 MRI 扫描的形态结构和图像强度值，以构建大脑的复杂性分布。已经意识到，白质变化的数量和空间分布在认知能力下降（即痴呆）和其他神经精神疾病（即多发性硬化症、抑郁症）以及其他痴呆症（如阿尔茨海默病）中起着重要作用。因此，这些结果可以用作工具，用于自动量化和比较与年龄相关的白质变化的各种空间分布和方向，在手动分析中存在困难，并且导致大脑各自基于 MRI 的信息的敏感性不同。
