Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada.
Laboratory on Neurobiology of Compulsive Behaviors, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland 20892.
J Neurosci. 2023 Feb 15;43(7):1074-1088. doi: 10.1523/JNEUROSCI.1179-22.2022.
In recent years, the field of neuroscience has gone through rapid experimental advances and a significant increase in the use of quantitative and computational methods. This growth has created a need for clearer analyses of the theory and modeling approaches used in the field. This issue is particularly complex in neuroscience because the field studies phenomena that cross a wide range of scales and often require consideration at varying degrees of abstraction, from precise biophysical interactions to the computations they implement. We argue that a pragmatic perspective of science, in which descriptive, mechanistic, and normative models and theories each play a distinct role in defining and bridging levels of abstraction, will facilitate neuroscientific practice. This analysis leads to methodological suggestions, including selecting a level of abstraction that is appropriate for a given problem, identifying transfer functions to connect models and data, and the use of models themselves as a form of experiment.
近年来,神经科学领域经历了快速的实验进展和定量与计算方法的大量应用。这种增长需求对该领域所使用的理论和建模方法进行更清晰的分析。在神经科学中,这个问题尤其复杂,因为该领域研究的现象跨越了广泛的尺度,通常需要在不同程度的抽象层面上进行考虑,从精确的生物物理相互作用到它们实现的计算。我们认为,科学的实用主义观点,其中描述性、机械性和规范性模型和理论各自在定义和连接抽象层次方面发挥着独特的作用,将促进神经科学实践。这种分析导致了方法学建议,包括选择适合给定问题的抽象层次,确定连接模型和数据的传递函数,以及将模型本身用作实验的一种形式。