Convolution Models for fMRI

This chapter reviews issues specific to the analysis of functional magnetic resonance imaging (fMRI) data. It extends the general linear model (GLM) introduced in Chapter 8 to convolution models, in which the blood oxygenation-level-dependent (BOLD) signal is modelled by neuronal causes that are expressed via a haemodynamic response function (HRF). We begin by considering linear convolution models and introduce the concept of temporal basis functions. We then consider the related issues of temporal filtering and temporal autocorrelation. Finally, we extend the convolution model to include nonlinear terms and conclude with some example analyses of fMRI data.

[1]  Karl J. Friston,et al.  Statistical parametric mapping for event-related potentials (II): a hierarchical temporal model , 2004, NeuroImage.

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

[3]  E. Zarahn Testing for Neural Responses during Temporal Components of Trials with BOLD fMRI , 2000, NeuroImage.

[4]  M. D’Esposito,et al.  A Trial-Based Experimental Design for fMRI , 1997, NeuroImage.

[5]  Karl J. Friston,et al.  Statistical parametric mapping for event-related potentials: I. Generic considerations , 2004, NeuroImage.

[6]  Guillaume Flandin,et al.  Bayesian comparison of spatially regularised general linear models , 2007, Human brain mapping.

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

[8]  A. Dale,et al.  Late Onset of Anterior Prefrontal Activity during True and False Recognition: An Event-Related fMRI Study , 1997, NeuroImage.

[9]  A M Dale,et al.  Optimal experimental design for event‐related fMRI , 1999, Human brain mapping.

[10]  Alan C. Evans,et al.  Estimating the delay of the hemodyanamic response in fMRI data , 2001, NeuroImage.

[11]  Adrian T. Lee,et al.  Discrimination of Large Venous Vessels in Time‐Course Spiral Blood‐Oxygen‐Level‐Dependent Magnetic‐Resonance Functional Neuroimaging , 1995, Magnetic resonance in medicine.

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

[13]  S. Petersen,et al.  Characterizing the Hemodynamic Response: Effects of Presentation Rate, Sampling Procedure, and the Possibility of Ordering Brain Activity Based on Relative Timing , 2000, NeuroImage.

[14]  A M Dale,et al.  Estimation and detection of event‐related fMRI signals with temporally correlated noise: A statistically efficient and unbiased approach , 2000, Human brain mapping.

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

[16]  Karl J. Friston,et al.  Bayesian fMRI time series analysis with spatial priors , 2005, NeuroImage.

[17]  M. Corbetta,et al.  Separating Processes within a Trial in Event-Related Functional MRI I. The Method , 2001, NeuroImage.

[18]  Karl J. Friston,et al.  Multivariate SPM: Application to basis function characterisations of event-related fMRI responses , 2000, NeuroImage.

[19]  M. Corbetta,et al.  Separating Processes within a Trial in Event-Related Functional MRI II. Analysis , 2001, NeuroImage.

[20]  M. D’Esposito,et al.  Empirical analyses of BOLD fMRI statistics. I. Spatially unsmoothed data collected under null-hypothesis conditions. , 1997, NeuroImage.

[21]  Karl J. Friston,et al.  Event-related fMRI , 1997 .

[22]  G. Krüger,et al.  MRI of Functional Deactivation: Temporal and Spatial Characteristics of Oxygenation-Sensitive Responses in Human Visual Cortex , 1999, NeuroImage.

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

[24]  Stephen M. Smith,et al.  Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data , 2001, NeuroImage.

[25]  Stefan Pollmann,et al.  Use of Short Intertrial Intervals in Single-Trial Experiments: A 3T fMRI-Study , 1998, NeuroImage.

[26]  R. Turner,et al.  Functional magnetic resonance imaging of the human brain: data acquisition and analysis , 1998, Experimental Brain Research.

[27]  J. -B. Poline,et al.  Estimating the Delay of the fMRI Response , 2002, NeuroImage.

[28]  Karl J. Friston,et al.  Classical and Bayesian Inference in Neuroimaging: Applications , 2002, NeuroImage.

[29]  A. Grinvald,et al.  Interactions Between Electrical Activity and Cortical Microcirculation Revealed by Imaging Spectroscopy: Implications for Functional Brain Mapping , 1996, Science.

[30]  M. D’Esposito,et al.  The variability of human BOLD hemodynamic responses , 1998, NeuroImage.

[31]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited—Again , 1995, NeuroImage.

[32]  Karl J. Friston,et al.  The slice-timing problem in event-related fMRI , 1999 .

[33]  Karl J. Friston,et al.  Analysis of functional MRI time‐series , 1994, Human Brain Mapping.

[34]  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.

[35]  Karl J. Friston,et al.  A heuristic for the degrees of freedom of statistics based on multiple variance parameters , 2003, NeuroImage.

[36]  L. Fahrmeir,et al.  Bayesian Modeling of the Hemodynamic Response Function in BOLD fMRI , 2001, NeuroImage.

[37]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[38]  Karl J. Friston,et al.  Bayesian Estimation of Dynamical Systems: An Application to fMRI , 2002, NeuroImage.

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

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

[41]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[42]  Mark W. Woolrich,et al.  Constrained linear basis sets for HRF modelling using Variational Bayes , 2004, NeuroImage.

[43]  T. Shallice,et al.  Face repetition effects in implicit and explicit memory tests as measured by fMRI. , 2002, Cerebral cortex.

[44]  R. Henson,et al.  Effects of stimulus repetition on latency of BOLD impulse response , 2001, NeuroImage.

[45]  Karl J. Friston,et al.  Nonlinear event‐related responses in fMRI , 1998, Magnetic resonance in medicine.

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

[47]  E. Bullmore,et al.  Statistical methods of estimation and inference for functional MR image analysis , 1996, Magnetic resonance in medicine.

[48]  Karl J. Friston,et al.  Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics , 2000, NeuroImage.

[49]  R. Weisskoff,et al.  Effect of temporal autocorrelation due to physiological noise and stimulus paradigm on voxel‐level false‐positive rates in fMRI , 1998, Human brain mapping.

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

[51]  Scott A. Huettel,et al.  Regional Differences in the Refractory Period of the Hemodynamic Response: An Event-Related fMRI Study , 2001, NeuroImage.

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

[53]  O Josephs,et al.  Event-related functional magnetic resonance imaging: modelling, inference and optimization. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[54]  Karl J. Friston,et al.  To Smooth or Not to Smooth? Bias and Efficiency in fMRI Time-Series Analysis , 2000, NeuroImage.

[55]  M. D’Esposito,et al.  The Variability of Human, BOLD Hemodynamic Responses , 1998, NeuroImage.

[56]  A. Dale,et al.  Selective averaging of rapidly presented individual trials using fMRI , 1997, Human brain mapping.

[57]  Karl J. Friston,et al.  The choice of basis functions in event-related fMRI , 2001, NeuroImage.