fMRI-based detection of alertness predicts behavioral response variability

• Main Authors: Sarah E Goodale, Nafis Ahmed, Chong Zhao, Jacco A de Zwart, Pinar S Özbay, Dante Picchioni, Jeff Duyn, Dario J Englot, Victoria L Morgan, Catie Chang
• Format: Article
• Language: English
• Published: eLife Sciences Publications Ltd 2021-05-01
• Series: eLife
• Subjects: fMRI; arousal; behavioral variability
• Online Access: https://elifesciences.org/articles/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.