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Updated: Feb 14, 2026
08:27
A Real-World High-Intensity Interval Training Protocol for Cardiorespiratory Fitness Improvement
Published on: February 22, 2022
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Cardiorespiratory noise correction improves the ASL signal
Mahlega S Hassanpour1, Qingfei Luo1, W Kyle Simmons1,2
1Laureate Institute for Brain Research, Tulsa, Oklahoma.
Human Brain Mapping
|February 17, 2018
Summary
Physiological noise from breathing and heart rate significantly impacts cerebral blood flow (CBF) measurements in arterial spin labeling (ASL) fMRI. Correcting this noise improves ASL signal-to-noise ratio for better brain activity analysis.
Area of Science:
- Neuroimaging
- Physiological Monitoring
- Cardiorespiratory Interactions
Background:
- Cardiorespiratory fluctuations introduce physiological noise in ASL fMRI.
- This noise confounds resting-state network analysis and reduces ASL signal-to-noise ratio during tasks.
Purpose of the Study:
- To evaluate methods for minimizing synchronized and non-synchronized physiological noise in ASL CBF measurements.
- To assess the impact of noise correction on ASL data quality and activation detection.
Main Methods:
- Combined RETROICOR with linear deconvolution models to correct ASL data.
- Evaluated variance explained by noise correction during rest and task conditions.
- Induced cardiorespiratory deviations with isoproterenol to test noise correction efficacy.
Main Results:
- Noise correction explained a significant portion of variance in CBF.
- Substantial improvements in signal-to-noise ratio observed at individual and group levels post-correction.
- Demonstrated feasibility of noise reduction through induced cardiorespiratory fluctuations.
Conclusions:
- Cardiorespiratory variations significantly influence ASL CBF.
- Regressing out non-neuronal physiological noise enhances ASL signal-to-noise ratio.
- This approach improves the identification and control of physiologically driven activations in ASL.
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