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Data-driven approaches for unveiling the neurophysiological functions of the auditory system

机译:用于揭示听觉系统的神经生理功能的数据驱动方法

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Typical neurophysiological experiments employ ``hypothesis-driven'' approaches: Researchers set a specific hypothesis, based on which stimuli and their parameters are chosen. However, there is always a concern that the hypothesis or stimulus parameter could be irrelevant to the essence of the brain function. The present paper review the authors' recent studies that have applied some ``data-driven'' approaches as relatively hypothesis-free methodologies to traditional questions in auditory neurophysiology, such as neural frequency tuning and cortical topography. The results provide some new insights into the functional organization of the cortex and the optimality of the brain structure for auditory processing.
机译:典型的神经生理学实验使用“假设驱动”的方法:研究人员设定了特定的假设,基于哪种刺激及其参数。然而,总是担心假设或刺激参数可能与大脑功能的本质无关。本文回顾了作者最近的研究,这些研究已经应用了一些“数据驱动”的方法作为对听觉神经生理学中的传统问题的相对假设的方法,例如神经频率调谐和皮质地形。结果为皮质功能组织提供了一些新的见解以及对听觉处理的大脑结构的最优性。

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