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The Fallacy of Univariate Solutions to Complex Systems Problems

机译:复杂系统问题单变量解的谬误

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Complex biological systems, by definition, are composed of multiple components that interact non-linearly. The human brain constitutes, arguably, the most complex biological system known. Yet most investigation of the brain and its function is carried out using assumptions appropriate for simple systems—univariate design and linear statistical approaches. This heuristic must change before we can hope to discover and test interventions to improve the lives of individuals with complex disorders of brain development and function. Indeed, a movement away from simplistic models of biological systems will benefit essentially all domains of biology and medicine. The present brief essay lays the foundation for this argument.
机译:根据定义,复杂的生物系统由非线性相互作用的多个组件组成。可以说,人脑是已知的最复杂的生物系统。然而,对大脑及其功能的大多数研究都是使用适合简单系统的假设进行的,即单变量设计和线性统计方法。在我们希望发现并测试干预措施以改善患有复杂大脑发育和功能障碍的人的生活之前,必须改变这种启发式方法。的确,从简单的生物系统模型中脱身将使生物学和医学的所有领域受益。本简短文章为这一论点奠定了基础。

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