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Inter-subject variability in hypercapnic normalization of the BOLD fMRI response.
1Center for Functional Magnetic Resonance Imaging, University of California San Diego, La Jolla, CA 92093-0677, USA.
Neuroimage
|December 30, 2008
Summary
Hypercapnic normalization in functional magnetic resonance imaging (fMRI) can increase variability. Using the hypercapnic BOLD response as a covariate, rather than dividing by it, reduces inter-subject variability in BOLD fMRI studies.
Area of Science:
- Neuroimaging
- Physiological measurements
Background:
- Hypercapnic normalization is used in functional magnetic resonance imaging (fMRI) to reduce variability in the blood oxygenation level dependent (BOLD) response.
- Previous studies have yielded conflicting results regarding its effectiveness in reducing inter-subject BOLD variability.
Purpose of the Study:
- To assess the impact of hypercapnic normalization on inter-subject BOLD variability.
- To investigate the influence of baseline cerebral blood flow (CBF) on BOLD and CBF responses to visual stimuli and hypercapnia.
Main Methods:
- Measured baseline CBF, and functional BOLD and CBF responses to visual stimuli and hypercapnia.
- Assessed inter-subject variability using division-based and covariate-based hypercapnic normalization methods.
Main Results:
- Functional and hypercapnic BOLD/CBF responses showed inverse dependence on baseline CBF.
- Division-based normalization increased inter-subject variability due to a systematic bias.
- Covariate-based normalization reduced inter-subject variability without introducing bias.
Conclusions:
- The positive intercept in the linear relationship between functional and hypercapnic BOLD responses is a critical factor in normalization.
- Covariate-based hypercapnic normalization is a more effective method for reducing inter-subject BOLD variability in fMRI studies.
