Estimating the Delay of the fMRI Response

We propose a fast, efficient, general, simple, valid, and robust method of estimating and making inference about the delay of the fMRI response modeled as a temporal shift of the hemodynamic response function (HRF). We estimate the shift unbiasedly using two optimally chosen basis functions for a spectrum of time shifted HRFs. This is done at every voxel, to create an image of estimated delays and their standard deviations. This can be used to compare delays for the same stimulus at different voxels, or for different stimuli at the same voxel. Our method is compared to other alternatives and validated on an fMRI data set from an experiment in pain perception.

[1]  Bruce Pike,et al.  Differentiating noxious- and innocuous-related activation of human somatosensory cortices using temporal analysis of fMRI. , 2002, Journal of neurophysiology.

[2]  R. Turner,et al.  Detecting Latency Differences in Event-Related BOLD Responses: Application to Words versus Nonwords and Initial versus Repeated Face Presentations , 2002, NeuroImage.

[3]  Emery N. Brown,et al.  Locally Regularized Spatiotemporal Modeling and Model Comparison for Functional MRI , 2001, NeuroImage.

[4]  P. Bandettini,et al.  Spatial Heterogeneity of the Nonlinear Dynamics in the FMRI BOLD Response , 2001, NeuroImage.

[5]  E. DeYoe,et al.  Analysis and use of FMRI response delays , 2001, Human brain mapping.

[6]  G Gratton,et al.  Comparison of neuronal and hemodynamic measures of the brain response to visual stimulation: An optical imaging study , 2001, Human brain mapping.

[7]  D. V. Cramon,et al.  Nonlinear Regression of Functional MRI Data: An Item Recognition Task Study , 2000, NeuroImage.

[8]  Alan C. Evans,et al.  A general statistical analysis for fMRI data , 2000, NeuroImage.

[9]  Jean-Baptiste Poline,et al.  Ambiguous Results in Functional Neuroimaging Data Analysis Due to Covariate Correlation , 1999, NeuroImage.

[10]  Ferath Kherif,et al.  Temporal sorting of neural components underlying phonological processing. , 1999, Neuroreport.

[11]  G. Glover.  Deconvolution of Impulse Response in Event-Related BOLD fMRI1 , 1999, NeuroImage.

[12]  D. Noll,et al.  Nonlinear Aspects of the BOLD Response in Functional MRI , 1998, NeuroImage.

[13]  R. Turner,et al.  Event-Related fMRI: Characterizing Differential Responses , 1998, NeuroImage.

[14]  D. Heeger,et al.  Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1 , 1996, The Journal of Neuroscience.

[15]  D. V. von Cramon,et al.  Temporal properties of the hemodynamic response in functional MRI , 1999, Human brain mapping.

[16]  Scott L. Zeger,et al.  Non‐linear Fourier Time Series Analysis for Human Brain Mapping by Functional Magnetic Resonance Imaging , 1997 .

[17]  C. Mountford.  Non-linear Fourier time series analysis for human brain mapping by functional magnetic resonance imaging - Discussion , 1997 .

[18]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[19]  J. Rajapakse,et al.  Human Brain Mapping 6:283–300(1998) � Modeling Hemodynamic Response for Analysis of Functional MRI Time-Series , 2022 .