title: Modeling of the hemodynamic responses in block design fMRI studies.
abstract: The hemodynamic response function (HRF) describes the local response of brain vasculature to functional activation. Accurate HRF modeling enables the investigation of cerebral blood flow regulation and improves our ability to interpret fMRI results. Block designs have been used extensively as fMRI paradigms because detection power is maximized; however, block designs are not optimal for HRF parameter estimation. Here we assessed the utility of block design fMRI data for HRF modeling. The trueness (relative deviation), precision (relative uncertainty), and identifiability (goodness-of-fit) of different HRF models were examined and test-retest reproducibility of HRF parameter estimates was assessed using computer simulations and fMRI data from 82 healthy young adult twins acquired on two occasions 3 to 4 months apart. The effects of systematically varying attributes of the block design paradigm were also examined. In our comparison of five HRF models, the model comprising the sum of two gamma functions with six free parameters had greatest parameter accuracy and identifiability. Hemodynamic response function height and time to peak were highly reproducible between studies and width was moderately reproducible but the reproducibility of onset time was low. This study established the feasibility and test-retest reliability of estimating HRF parameters using data from block design fMRI studies.
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Zuyao Y
authors.initials: ZY
authors.lastname: Shan
authors.affiliation: Queensland Institute of Medical Research, Brisbane, Queensland, Australia.
authors.forename: Margaret J
authors.initials: MJ
authors.lastname: Wright
authors.affiliation: Imaging Genetics Center, Laboratory of NeuroImaging, Department of Neurology & Psychiatry, UCLA School of Medicine, Los Angeles, California, USA.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Katie L
authors.initials: KL
authors.lastname: McMahon
authors.affiliation: Queensland Institute of Medical Research, Brisbane, Queensland, Australia.
authors.forename: Gabriella G A M
authors.initials: GG
authors.lastname: Blokland
authors.affiliation: School of Psychology, The University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Greig I
authors.initials: GI
authors.lastname: de Zubicaray
authors.affiliation: Queensland Institute of Medical Research, Brisbane, Queensland, Australia.
authors.forename: Nicholas G
authors.initials: NG
authors.lastname: Martin
authors.affiliation: Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Anna A E
authors.initials: AA
authors.lastname: Vinkhuyzen
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
authors.forename: David C
authors.initials: DC
authors.lastname: Reutens
mesh_terms: D000328:Adult; D001783:Blood Flow Velocity; D002560:Cerebrovascular Circulation; D003198:Computer Simulation; D005260:Female; D006801:Humans; D018810:Magnetic Resonance Angiography; D008297:Male; D008955:Models, Cardiovascular; D015203:Reproducibility of Results