We investigate both experimentally and using a computational model how the power of the electroencephalogram (EEG) recorded in human subjects tracks the presentation of sounds with acoustic intensities that increase exponentially (looming) or remain constant (flat). We focus on the link between this EEG tracking response, behavioral reaction times and the time scale of fluctuations in the resting state, which show considerable inter-subject variability. Looming sounds are shown to generally elicit a sustained power increase in the alpha and beta frequency bands. In contrast, flat sounds only elicit a transient upsurge at frequencies ranging from 7 to 45 Hz. Likewise, reaction times (RTs) in an audio-tactile task at different latencies from sound onset also present significant differences between sound types. RTs decrease with increasing looming intensities, i.e. as the sense of urgency increases, but remain constant with stationary flat intensities. We define the reaction time variation or “gain” during looming sound presentation, and show that higher RT gains are associated with stronger correlations between EEG power responses and sound intensity. Higher RT gain further entails higher relative power differences between loom and flat in the alpha and beta bands. The full-width-at-half-maximum of the autocorrelation function of the eyes-closed resting state EEG also increases with RT gain. The effects are topographically located over the central and frontal electrodes. A computational model reveals that the increase in stimulus–response correlation in subjects with slower resting state fluctuations is expected when EEG power fluctuations at each electrode and in a given band are viewed as simple coupled low-pass filtered noise processes jointly driven by the sound intensity. The model assumes that the strength of stimulus-power coupling is proportional to RT gain in different coupling scenarios, suggesting a mechanism by which slower resting state fluctuations enhance EEG response and shorten reaction times.

我们通过实验和使用计算模型研究人类受试者中记录的脑电图 (EEG) 的功率如何跟踪声强度呈指数增加（隐约）或保持恒定（平坦）的声音的呈现。我们专注于这种脑电图跟踪反应、行为反应时间和静息状态波动的时间尺度之间的联系，这显示出相当大的受试者间变异性。隐约可见的声音通常会在 alpha 和 beta 频带中引起持续的功率增加。相比之下，平坦的声音只会在 7 到 45 Hz 的频率范围内引起瞬态高涨。同样，从声音开始到不同延迟的听觉触觉任务中的反应时间 (RT) 也呈现出声音类型之间的显着差异。RT随着迫在眉睫的强度增加而降低，即随着紧迫感的增加，但随着固定的平坦强度保持不变。我们定义了迫在眉睫的声音呈现期间的反应时间变化或“增益”，并表明更高的 RT 增益与 EEG 功率响应和声音强度之间更强的相关性相关。更高的 RT 增益进一步导致 alpha 和 beta 波段中织机和平板之间的相对功率差异更大。闭眼静息状态EEG的自相关函数的半峰全宽也随着RT增益而增加。这些效果在地形上位于中央和正面电极上。计算模型表明，当每个电极和给定频带中的 EEG 功率波动被视为由声音强度共同驱动的简单耦合低通滤波噪声过程时，预计静息状态波动较慢的受试者的刺激 - 反应相关性会增加. 该模型假设刺激-功率耦合的强度与不同耦合情况下的 RT 增益成正比，这表明较慢的静息状态波动增强 EEG 反应并缩短反应时间的机制。