Department of Biomedical Engineering, Vanderbilt University, Nashville, United States.
Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, United States.
Elife. 2021 May 7;10:e62376. doi: 10.7554/eLife.62376.
Levels of alertness are closely linked with human behavior and cognition. However, while functional magnetic resonance imaging (fMRI) allows for investigating whole-brain dynamics during behavior and task engagement, concurrent measures of alertness (such as EEG or pupillometry) are often unavailable. Here, we extract a continuous, time-resolved marker of alertness from fMRI data alone. We demonstrate that this fMRI alertness marker, calculated in a short pre-stimulus interval, captures trial-to-trial behavioral responses to incoming sensory stimuli. In addition, we find that the prediction of both EEG and behavioral responses during the task may be accomplished using only a small fraction of fMRI voxels. Furthermore, we observe that accounting for alertness appears to increase the statistical detection of task-activated brain areas. These findings have broad implications for augmenting a large body of existing datasets with information about ongoing arousal states, enriching fMRI studies of neural variability in health and disease.
警觉水平与人类行为和认知密切相关。然而，虽然功能磁共振成像 (fMRI) 可以在行为和任务参与期间研究全脑动力学，但通常无法同时进行警觉度的测量（如 EEG 或瞳孔测量）。在这里，我们仅从 fMRI 数据中提取出一种连续的、时间分辨的警觉度标记物。我们证明，在短的刺激前间隔内计算出的 fMRI 警觉度标记物可以捕获对传入感觉刺激的逐次行为反应。此外，我们发现，仅使用 fMRI 体素的一小部分就可以完成对 EEG 和行为反应的预测。此外，我们观察到，考虑警觉度似乎可以增加对任务激活脑区的统计检测。这些发现对用关于持续唤醒状态的信息来扩充大量现有数据集具有广泛的意义，丰富了健康和疾病中神经变异性的 fMRI 研究。
