MEASURING THE VARIABILITY OF EVENT-RELATED BOLD SIGNAL

Most current analysis methods for functional magnetic resonance imaging (fMRI) data assume a priori knowledge of the time course of the hemodynamic response (HR) to experimental stimuli or events in brain areas of interest. In addition, they typically assume homogeneity of both the HR and the non-HR “noise” signals both across brain regions and across similar experimental events. When HRs vary unpredictably from area to area, or from trial to trial, different approaches are needed. Here we used infomax Independent Component Analysis (ICA) to detect and visualize variations in single-trial HRs in event-related fMRI data. ICA decomposition of the resulting BOLD data produced independent components with variable stimulus-locked HRs active in primary visual (V1) and medial temporal (MT/V5) cortices respectively. Contrary to expectation, in four of six subjects the HR of the V1 component contained two positive peaks in response to short-stimulus bursts, while nearly identical component maps were associated with single-peaked HRs in long-stimulus sessions from the same subject. Thus, ICA combined with single-trial visualization can reveal dramatic and unforeseen task-related HR variation not apparent to researchers analyzing the data with fixed HR