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Back to Pupillometry: How Cortical Network State Fluctuations Tracked by Pupil Dynamics Could Explain Neural Signal
Miriam Schwalm1,2, Eduardo Rosales Jubal1,3
1Focus Program Translational Neuroscience (FTN) and Institute for Microscopic Anatomy and Neurobiology, Johannes Gutenberg-University Mainz, Mainz D-55128, Germany.
Eneuro
|January 31, 2018
Summary
Pupil size changes reflect brain network states in rodents and humans. This finding suggests pupillometry can track brain activity fluctuations, potentially explaining previously disregarded neural signal variations.
Area of Science:
- Neuroscience
- Cognitive Neuroscience
- Computational Neuroscience
Background:
- Mammalian thalamocortical networks exhibit intrinsic activity reflecting varying neuronal excitability states.
- These network state fluctuations occur spontaneously during wakefulness and impact neural processing and behavior.
- Pupil size changes in rodents correlate with neuronal membrane potential and network states.
Purpose of the Study:
- To investigate if pupillometry can serve as an index for network state fluctuations in human brain signals.
- To explore the potential of pupil dilation as a marker for task-independent neural variability.
Main Methods:
- Review of existing literature on thalamocortical system activity and pupillometry.
- Analysis of studies linking rodent pupil size to neuronal membrane potential and cortical states.
- Extrapolation of findings to human brain signal analysis.
Main Results:
- Pupil size is a reliable indicator of neuronal membrane potential in rodents.
- Pupil size changes are associated with network state fluctuations in the rodent cortex.
- Pupillometry holds potential as a non-invasive index for human brain network states.
Conclusions:
- Pupillometry offers a promising, non-invasive method to index brain network states in humans.
- Understanding pupil size-linked network fluctuations may help interpret previously disregarded neural and behavioral signal variance.
- This approach could enhance the analysis of cognitive and neural processes by accounting for intrinsic brain dynamics.
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