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Evolution of neuroarchitecture multi-level analyses and calibrative reductionism

机译:神经体系结构的演变多层次分析和校准归约主义

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摘要

Evolution has sculpted the incredibly complex human nervous system, among the most complex functions of which extend beyond the individual to an intricate social structure. Although these functions are deterministic, those determinants are legion, heavily interacting and dependent on a specific evolutionary trajectory. That trajectory was directed by the adaptive significance of quasi-random genetic variations, but was also influenced by chance and caprice. With a different evolutionary pathway, the same neural elements could subserve functions distinctly different from what they do in extant human brains. Consequently, the properties of higher level neural networks cannot be derived readily from the properties of the lower level constituent elements, without studying these elements in the aggregate. Thus, a multi-level approach to integrative neuroscience may offer an optimal strategy. Moreover, the process of calibrative reductionism, by which concepts and understandings from one level of organization or analysis can mutually inform and ‘calibrate’ those from other levels (both higher and lower), may represent a viable approach to the application of reductionism in science. This is especially relevant in social neuroscience, where the basic subject matter of interest is defined by interacting organisms across diverse environments.
机译:进化论雕刻了令人难以置信的复杂的人类神经系统,其中最复杂的功能超出了个人到复杂的社会结构的范围。尽管这些功能是确定性的,但这些决定性因素是众多的,相互影响很大,并依赖于特定的进化轨迹。该轨迹是由准随机遗传变异的适应性意义决定的,但也受到机会和随想的影响。通过不同的进化途径,相同的神经元可以提供的功能与其在现存人类大脑中的功能截然不同。因此,如果不研究总体中的这些元素,就无法从较低级别的构成元素的属性中轻易推导出较高级别的神经网络的属性。因此,整合神经科学的多层次方法可以提供最佳策略。此外,校准还原主义的过程,组织或分析的一个层次的概念和理解可以相互交流和“校准”其他层次(较高和较低)的概念和理解,这可能是一种在科学中应用还原主义的可行方法。 。这在社会神经科学中尤为重要,在该领域中,基本的主题是通过跨各种环境的生物相互作用来定义的。

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