A comparison of physiologic modulators of fMRI signals.

Hum Brain Mapp. 2012 Mar 28;

Authors: Liu P, Hebrank AC, Rodrigue KM, Kennedy KM, Park DC, Lu H

Abstract
One of the main obstacles in quantitative interpretation of functional magnetic resonance imaging (fMRI) signal is that this signal is influenced by non-neural factors such as vascular properties of the brain, which effectively increases signal variability. One approach to account for non-neural components is to identify and measure these confounding factors and to include them as covariates in data analysis or interpretation. Previously, several research groups have independently identified four potential physiologic modulators of fMRI signals, including baseline venous oxygenation (Y(v) ), cerebrovascular reactivity (CVR), resting state BOLD fluctuation amplitude (RSFA), and baseline cerebral blood flow (CBF). This study sought to directly compare the modulation effects of these indices in the same fMRI session. The physiologic parameters were measured with techniques comparable with those used in the previous studies except for CBF, which was determined globally with a velocity-based phase-contrast MRI (instead of arterial-spin-labeling MRI). Using an event-related, scene-categorization fMRI task, we showed that the fMRI signal amplitude was positively correlated with CVR (P < 0.0001) and RSFA (P = 0.002), while negatively correlated with baseline Y(v) (P < 0.0001). The fMRI-CBF correlation did not reach significance, although the (negative) sign of the correlation was consistent with the earlier study. Furthermore, among the physiologic modulators themselves, significant correlations were observed between baseline Y(v) and baseline CBF (P = 0.01), and between CVR and RSFA (P = 0.05), suggesting that some of the modulators may partly be of similar physiologic origins. These observations as well as findings in recent literature suggest that additional measurement of physiologic modulator(s) in an fMRI session may provide a practical approach to control for inter-subject variations and to improve the ability of fMRI in detecting disease or medication related differences. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.

PMID: 22461234 [PubMed - as supplied by publisher]