eLife (May 2021)

fMRI-based detection of alertness predicts behavioral response variability

  • 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

DOI
https://doi.org/10.7554/eLife.62376
Journal volume & issue
Vol. 10

Abstract

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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.

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