Department of Psychology and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA.
Trends Cogn Sci. 2018 Dec;22(12):1091-1102. doi: 10.1016/j.tics.2018.09.002. Epub 2018 Sep 29.
An intrinsic difficulty in studying cognitive processes is that they are unobservable states that exist in between observable responses to the sensory environment. Cognitive states must be inferred from indirect behavioral measures. Neuroscience potentially provides the tools necessary to measure cognitive processes directly, but it is challenged on two fronts. First, neuroscientific measures often lack the spatiotemporal resolution to identify the neural computations that underlie a cognitive process. Second, the activity of a single neuron, which is the fundamental building block of neural computation, is too noisy to provide accurate measurements of a cognitive process. In this paper, I examine recent developments in neurophysiological recording and analysis methods that provide a potential solution to these problems.
研究认知过程的一个内在困难是，它们是不可观察的状态，存在于对感官环境的可观察反应之间。认知状态必须从间接的行为测量中推断出来。神经科学有可能提供直接测量认知过程所需的工具，但它在两个方面受到挑战。首先，神经科学的测量往往缺乏时空分辨率，无法确定认知过程所依据的神经计算。其次，单个神经元的活动是神经计算的基本构建块，但过于嘈杂，无法对认知过程进行准确的测量。在本文中，我考察了神经生理记录和分析方法的最新进展，这些方法为解决这些问题提供了一种潜在的解决方案。
