BOLD response is more than just magnitude: improving detection sensitivity through capturing hemodynamic profiles

Abstract

Typical FMRI analyses assume a canonical hemodynamic response function (HRF) with a focus on the overshoot peak height, while other morphological aspects are largely ignored. Thus, in most reported analyses, the overall effect is reduced from a curve to a single scalar. Here, we adopt a data-driven approach to HRF estimation at the whole-brain voxel level, without assuming a response profile at the individual level. Then, we estimate the response in its entirety with a roughness penalty at the population level to improve predictive accuracy, inferential efficiency, and cross-study reproducibility. Using a fast event-related FMRI dataset, we demonstrate the extent of under-fitting and information loss that occurs when adopting the canonical approach. We also address the following questions: O_LIHow much does the HRF shape vary across regions, conditions, and groups? C_LIO_LIDoes an agnostic approach improve sensitivity to detect an effect compared to an assumed HRF? C_LIO_LICan examining HRF shape help validate the presence of an effect complementing statistical evidence? C_LIO_LICould the HRF shape provide evidence for whole-brain BOLD response during a simple task? C_LI