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

神经振荡在电生理记录中是普遍存在的。特别是，α波段（10 Hz）的振荡（人类EEG中最主要的节律）是神经元兴奋性的指标。先前的研究已经表明，在刺激呈现的时刻正在进行的α振荡的功率与近阈值刺激的正确检测相关。对这一发现的传统解释是，α振荡以及神经兴奋性调节视觉感知的准确性，即区分信号和噪声的能力。然而，最近的研究结果表明，阿尔法振荡可能会调节观察者感知决策的偏差。这种对自发性大脑活动的功能作用的意义深远的重新解释的经验基础需要得到证实。此外，信号检测措施的偏差可能有两个非常不同的根本原因：感知偏差，影响信号和噪声的主观外观，或决策偏差，影响响应选项的战略偏好。以前的研究无法区分这些替代品。在这个项目中，我建议研究持续的神经振荡对视觉感知的影响。具体而言，计划的实验旨在测试是否刺激前振荡影响客观准确性，刺激的主观外观（感知偏差），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EEG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如何与感知和行为相关。考虑到EEG振荡强度的自发波动与神经元兴奋性以及警惕性和表现的波动密切相关，该项目的研究结果对我们理解大脑对唤醒，觉醒的持续调节以及维持足够的感知和认知表现具有影响。

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.