动物行为学
认知科学
心理学
计算神经科学
转化式学习
动物行为
领域(数学)
神经科学
计算机科学
人工智能
认知心理学
生物
发展心理学
生态学
动物
数学
纯数学
作者
Dean Mobbs,Toby Wise,Nanthia Suthana,Noah Guzmán,Nikolaus Kriegeskorte,Joel Z. Leibo
出处
期刊:Neuron
[Elsevier]
日期:2021-07-01
卷期号:109 (14): 2224-2238
被引量:43
标识
DOI:10.1016/j.neuron.2021.05.021
摘要
The movements an organism makes provide insights into its internal states and motives. This principle is the foundation of the new field of computational ethology, which links rich automatic measurements of natural behaviors to motivational states and neural activity. Computational ethology has proven transformative for animal behavioral neuroscience. This success raises the question of whether rich automatic measurements of behavior can similarly drive progress in human neuroscience and psychology. New technologies for capturing and analyzing complex behaviors in real and virtual environments enable us to probe the human brain during naturalistic dynamic interactions with the environment that so far were beyond experimental investigation. Inspired by nonhuman computational ethology, we explore how these new tools can be used to test important questions in human neuroscience. We argue that application of this methodology will help human neuroscience and psychology extend limited behavioral measurements such as reaction time and accuracy, permit novel insights into how the human brain produces behavior, and ultimately reduce the growing measurement gap between human and animal neuroscience.
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