Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses

• Published in: NeuroImage (Orlando, Fla.) Vol. 21; no. 4; pp. 1639 - 1651
• Main Authors: Handwerker, Daniel A., Ollinger, John M., D'Esposito, Mark
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.04.2004; Elsevier Limited
• Subjects: Activation latency; Adolescent; Adult; Analysis of Variance; Brain - blood supply; Brain Mapping; Cerebral Cortex - physiology; Dominance, Cerebral - physiology; Echo-Planar Imaging; Estimates; Evoked Potentials - physiology; Experiments; Female; fMRI; Frontal Lobe - physiology; Functional neuroimaging; Hemodynamic response function; Hemodynamics - physiology; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Linear Models; Linear regression; Magnetic Resonance Imaging - statistics & numerical data; Male; Mathematical Computing; Motor Cortex - physiology; Oxygen - blood; Pattern Recognition, Visual - physiology; Psychomotor Performance - physiology; Random effects; Reaction Time - physiology; Reflex - physiology; Saccades; Saccades - physiology; Statistics as Topic; Studies; Time series; Visual areas; Visual Cortex - physiology; fMRI; Saccades; Linear regression; Functional neuroimaging; Random effects; Activation latency; Hemodynamic response function; Visual areas
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2003.11.029

Estimates of hemodynamic response functions (HRF) are often integral parts of event-related fMRI analyses. Although HRFs vary across individuals and brain regions, few studies have investigated how variations affect the results of statistical analyses using the general linear model (GLM). In this study, we empirically estimated HRFs from primary motor and visual cortices and frontal and supplementary eye fields (SEF) in 20 subjects. We observed more variability across subjects than regions and correlated variation of time-to-peak values across several pairs of regions. Simulations examined the effects of observed variability on statistical results and ways different experimental designs and statistical models can limit these effects. Widely spaced and rapid event-related experimental designs with two sampling rates were tested. Statistical models compared an empirically derived HRF to a canonical HRF and included the first derivative of the HRF in the GLM. Small differences between the estimated and true HRFs did not cause false negatives, but larger differences within an observed range of variation, such as a 2.5-s time-to-onset misestimate, led to false negatives. Although small errors minimally affected detection of activity, time-to-onset misestimates as small as 1 s influenced model parameter estimation and therefore random effects analyses across subjects. Experiment and analysis design methods such as decreasing the sampling rate or including the HRF's temporal derivative in the GLM improved results, but did not eliminate errors caused by HRF misestimates. These results highlight the benefits of determining the best possible HRF estimate and potential negative consequences of assuming HRF consistency across subjects or brain regions.