Do ongoing neural oscillations influence objective visual acuity, perceptual bias, or decision bias?

神经振荡是电生理记录中普遍存在的现象。特别是，阿尔法频段(10赫兹)的振荡，这是人类脑电中最主要的节律，是神经元兴奋性的一个指标。先前的研究表明，在刺激呈现的时刻，持续的阿尔法振荡的力量与正确检测接近阈值的刺激有关。对这一发现的传统解释是，阿尔法振荡，从而神经兴奋性，调节了视觉感知的准确性，即区分信号和噪声的能力。然而，最近的发现表明，阿尔法振荡可能反而会调节观察者感知决策中的偏差。这种对自发脑活动的功能作用的深远的重新解释的经验基础需要得到证实。此外，信号检测措施中的偏差可能有两个非常不同的根本原因：影响信号和噪声的主观外观的感知偏差，或影响对响应选项的战略偏好的决策偏差。之前的研究无法区分这些替代方案。在这个项目中，我打算研究正在进行的神经振荡对视觉感知的影响。具体地说，计划中的实验旨在测试前刺激振荡是否会影响客观准确性、刺激的主观外观(知觉偏差)或战略决策(决策偏差)。为此，我计划使用单次试验时频分析来分析人类脑电中的振荡，并使用心理物理学、信号检测理论和计算建模的创新组合来研究它们与感知和行为的关系。考虑到脑电振荡强度的自发波动与神经元的兴奋性以及警觉性和表现的波动密切相关，该项目的发现对于我们理解大脑对觉醒、觉醒的持续调节以及维持足够的知觉和认知性能具有重要意义。

Neural oscillations are ubiquitous in electrophysiological recordings. In particular, oscillations in the alpha-band (10 Hz), the most dominant rhythm in human EEG, are an index of neuronal excitability. Previous studies have shown that the power of ongoing alpha oscillations at the moment of stimulus presentation is correlated with correct detection of near-threshold stimuli. The conventional interpretation of this finding has been that alpha oscillations, and thus neural excitability, modulate the accuracy of visual perception, i.e. the ability to distinguish signal and noise. Recent findings, however, suggest that alpha oscillations may instead modulate the bias in observers' perceptual decisions. The empirical basis for this far-reaching re-interpretation of the functional role of spontaneous brain activity needs to be substantiated. Furthermore, a bias in signal detection measures can have two very different underlying causes: a perceptual bias, which affects the subjective appearance of signal and noise, or a decision bias, which affects the strategic preference for a response option. Previous studies were unable to distinguish between these alternatives. In this project, I propose to study the effect of ongoing neural oscillations on visual perception. Specifically, the planned experiments are designed to test whether pre-stimulus oscillations affect objective accuracy, the subjective appearance of stimuli (perceptual bias), or strategic decision making (decision bias). To this end, I plan to analyze oscillations in human EEG using single-trial time-frequency analysis, and to study how they are related to perception and behavior using an innovative combination of psychophysics, signal detection theory, and computational modeling. Considering that spontaneous fluctuations in the strength of EEG oscillations are tightly correlated with neuronal excitability and with fluctuations in vigilance and performance, the findings of this project have implications for our understanding of the brain's ongoing regulation of arousal, wakefulness, and the maintenance of adequate perceptual and cognitive performance.