PsychophysiologyNeurosciencePeer-reviewed journal article
Electrophysiological correlates of hyperoxia during resting-state EEG in awake human subjects
Sayeed A. D. KizukiD, Wesley VuongiD, Joanna E. MacLeaniD, Clayton T. DicksoniD, Kyle E. MathewsoniD
Abstract
Recreational use of concentrated oxygen has increased. Claims have been made that hyperoxic breathing can help reduce fatigue, increase alertness, and improve attentional capacities; however, few systematic studies of these potential benefits exist. Here we examined the effects of short-term (15 minute) hyperoxia on resting-states in awake human subjects by measuring spontaneous EEG activity between normoxic and hyperoxic situations, using a within-subjects design for both eyes-opened and eyes-closed conditions. We also measured respiration rate, heart rate, and blood oxygen saturation levels to correlate basic physiological changes due to the hyperoxic challenge with any brain activity changes. Our results show that breathing short term 100% oxygen led to increased blood-oxygen saturation levels, decreased heart rate, and a slight, but non-significant, decrease in breathing rate. Changes of brain activity were apparent, including decreases in low-alpha (7-10 Hz), high-alpha (10-14 Hz), beta (14-30 Hz), and gamma (30-50 Hz) frequency ranges during eyes-opened hyperoxic conditions. During eyes-closed hyperoxia, increases in the delta (0.5-3.5 Hz) and theta (3.5-7 Hz) frequency range were apparent together with decreases in the beta range. Hyperoxia appeared to accentuate the decrease of low alpha and gamma ranges across the eyes-opened and closed conditions suggesting that it modulated brain state itself. As decreased alpha during eyes-opened conditions has been associated with increased attentional processing and selective attention, and increased delta and theta during eyes-closed condition are typically associated with the initiation of sleep, our results suggest a state-specific and perhaps opposing influence of short-term hyperoxia.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 13
- FWCI
- 0.87
- Field percentile
- top 29%
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