Stability, repeatability, and the expression of signal magnitude in functional magnetic resonance imaging.
In 23 fMRI studies on six subjects, we examined activation in visual and motor tasks. We modeled the expected activation time course by convolving a temporal description of the behavioral task with an empirically determined impulse response function. We evaluated the signal activation intensity as both the number of activated voxels over arbitrary correlation thresholds and as the slope of the regression line between our modeled time course and the actual data. Whereas the voxel counting was strikingly unstable (standard deviation 74% in visual trials at a correlation of 0.5), the slope was relatively constant across trials and subjects (standard deviation <14%). Using Monte Carlo methods, we determined that the measured slope was largely independent of the contrast-to-noise ratio. Voxel counting is a poor proxy for activation intensity, with greatly increased scatter, much reduced statistical power, and increased type II error. The data support an alternative approach to functional magnetic resonance imaging (fMRI) that allows for quantitative comparisons of fMRI response magnitudes across trials and laboratories.
UCLA Brain Mapping Division, Ahmanson-Lovelace Brain Mapping Center, Los Angeles, California 90095-7085, USA. mscohen@ucla.edu
M S
MS
Cohen
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RM
DuBois
D000328:Adult; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009010:Monte Carlo Method; D009043:Motor Activity; D009044:Motor Cortex / Q000502:physiology; D010775:Photic Stimulation; D012680:Sensitivity and Specificity