title: Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling.
abstract: Most brain research to date have focused on studying the amplitude of evoked fMRI responses, though there has recently been an increased interest in measuring onset, peak latency and duration of the responses as well. A number of modeling procedures provide measures of the latency and duration of fMRI responses. In this work we compare several techniques that vary in their assumptions, model complexity, and interpretation. For each method, we introduce methods for estimating amplitude, peak latency, and duration and for performing inference in a multi-subject fMRI setting. We then assess the techniques' relative sensitivity and their propensity for mis-attributing task effects on one parameter (e.g., duration) to another (e.g., amplitude). Finally, we introduce methods for quantifying model misspecification and assessing bias and power-loss related to the choice of model. Overall, the results show that it is surprisingly difficult to accurately recover true task-evoked changes in BOLD signal and that there are substantial differences among models in terms of power, bias and parameter confusability. Because virtually all fMRI studies in cognitive and affective neuroscience employ these models, the results bear on the interpretation of hemodynamic response estimates across a wide variety of psychological and neuroscientific studies.
authors.affiliation: Department of Statistics, Columbia University, New York, NY 10027, USA. martin@stat.columbia.edu
authors.forename: Martin A
authors.initials: MA
authors.lastname: Lindquist
authors.forename: Ji
authors.initials: J
authors.lastname: Meng Loh
authors.forename: Lauren Y
authors.initials: LY
authors.lastname: Atlas
authors.forename: Tor D
authors.initials: TD
authors.lastname: Wager
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology; D006439:Hemodynamics / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008959:Models, Neurological