4.8 Article

Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation

Journal

ELIFE
Volume 10, Issue -, Pages -

Publisher

eLIFE SCIENCES PUBL LTD
DOI: 10.7554/eLife.68980

Keywords

pupil; fMRI; decoding; principal component analysis; neuromodulation; brain state; Rat

Categories

Funding

  1. Max-Planck-Gesellschaft
  2. National Institutes of Health [RF1NS113278-01, R01MH111438-01, S10 MH124733-01]
  3. Deutsche Forschungsgemeinschaft [YU215/2-1, Yu215/3-1]
  4. Bundesministerium fur Bildung und Forschung [01GQ1702]

Ask authors/readers for more resources

Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain in diverse behavioral experiments. By decomposing spatiotemporal patterns of resting-state fMRI using PCA and optimizing the PCA component weighting via decoding methods, unique activity patterns related to pupil diameter changes in different trials can be studied in relation to neuromodulatory centers. This novel PCA-based decoding method demonstrates the tight coupling between pupil dynamics and different neuromodulatory centers across trials.
Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain across a diverse range of behavioral experiments. Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil-fMRI relationship.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available