Department of Psychology, University of Miami, PO Box 248185-0751, Coral Gables, FL 33124, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
Trends Cogn Sci. 2020 Sep;24(9):734-746. doi: 10.1016/j.tics.2020.06.003. Epub 2020 Jun 27.
Definitions of what constitutes the 'signal of interest' in neuroscience can be controversial, due in part to continuously evolving notions regarding the significance of spontaneous neural activity. This review highlights how the challenge of separating brain signal from noise has led to new conceptualizations of brain functional organization at both the micro- and macroscopic level. Recent debates in the functional neuroimaging community surrounding artifact removal processes have revived earlier discussions surrounding how to appropriately isolate and measure neuronal signals against a background of noise from various sources. Insights from electrophysiological studies and computational modeling can inform current theory and data analytic practices in human functional neuroimaging, given that signal and noise may be inextricably linked in the brain.
由于人们对自发神经活动的意义的认识不断发展，因此神经科学中“感兴趣的信号”的定义可能存在争议。这篇综述强调了如何将大脑信号与噪声分离的挑战，这导致了在微观和宏观层面上对大脑功能组织的新概念化。在功能神经影像学领域，围绕去除伪影过程的最新讨论，重新引发了关于如何在来自各种来源的噪声背景下适当隔离和测量神经元信号的早期讨论。鉴于信号和噪声在大脑中可能是不可分割的，来自电生理学研究和计算模型的见解可以为人类功能神经影像学中的当前理论和数据分析实践提供信息。
