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75
Deconvolution of impulse response in eventrelated BOLD fMRI
- NEUROIMAGE
, 1999
"... The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both corti ..."
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Cited by 205 (2 self)
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The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both cortical systems were found to be nonlinear in that the response to a long stimulus could not be predicted by convolving the 1-s response with a rectangular function. In the shorttime regime, the amplitude of the response varied only slowly with stimulus duration. It was found that this character was predicted with a modification to Buxton’s balloon model. Wiener deconvolution was used to deblur the response to concatenated short episodes of finger tapping at different temporal separations and at rates from 1 to 4 Hz. While the measured response curves were distorted by overlap between the individual episodes, the deconvolved response at each rate was found to agree well with separate scans at each of the individual rates. Thus, although the impulse response cannot predict the response to fully overlapping stimuli, linear deconvolution is effective when the stimuli are separated by at least 4 s. The deconvolution filter must be measured for each subject using a shortstimulus paradigm. It is concluded that deconvolution may be effective in diminishing the hemodynamically imposed temporal blurring and may have potential applications in quantitating responses in eventrelated fMRI.
Characterizing the hemodynamic response: Effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing
- NEUROIMAGE 11: 735–759
, 2000
"... Rapid-presentation event-related functional MRI (ER-fMRI) allows neuroimaging methods based on hemodynamics to employ behavioral task paradigms typical of cognitive settings. However, the sluggishness of the hemodynamic response and its variance provide constraints on how ER-fMRI can be applied. In ..."
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Cited by 157 (15 self)
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Rapid-presentation event-related functional MRI (ER-fMRI) allows neuroimaging methods based on hemodynamics to employ behavioral task paradigms typical of cognitive settings. However, the sluggishness of the hemodynamic response and its variance provide constraints on how ER-fMRI can be applied. In a series of two studies, estimates of the hemodynamic response in or near the primary visual and motor cortices were compared across various paradigms and sampling procedures to determine the limits of ER-fMRI procedures and, more generally, to describe the behavior of the hemodynamic response. The temporal profile of the hemodynamic response was estimated across overlapping events by solving a set of linear equations within the general linear model. No
Multisubject fMRI studies and conjunction analyses
- NeuroImage
, 1999
"... In this paper we present an approach to making inferences about generic activations in groups of subjects using fMRI. In particular we suggest that activations common to all subjects reflect aspects of functional anatomy that may be ‘‘typical’ ’ of the population from which that group was sampled. T ..."
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Cited by 147 (7 self)
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In this paper we present an approach to making inferences about generic activations in groups of subjects using fMRI. In particular we suggest that activations common to all subjects reflect aspects of functional anatomy that may be ‘‘typical’ ’ of the population from which that group was sampled. These commonalities can be identified by a conjunction analysis of the activation effects in which the contrasts, testing for an activation, are specified separately for each subject. A conjunction is the joint refutation of multiple null hypotheses, in this instance, of no activation in any subject. The motivation behind this use of conjunctions is that fixed-effect analyses are generally more ‘‘sensitive’ ’ than equivalent random-effect analyses. This is because fixed-effect analyses can harness the large degrees of freedom and small scan-to-scan variability (relative to the variability in responses from subject to subject) when assessing the significance of an estimated response. The price one pays for the apparent sensitivity of fixed-effect analyses is that the ensuing inferences pertain to, and only to, the subjects studied. However, a conjunction analysis, using a fixedeffect model, allows one to infer: (i) that every subject studied activated and (ii) that at least a certain proportion of the population would have shown this effect. The second inference depends upon a meta-analytic formulation in terms of a confidence region for this proportion. This approach retains the sensitivity of fixed-effect analyses when the inference that only a substantial proportion of the population activates is sufficient.
Separating processes within a trial in event-related functional MRI. I. The method. NeuroImage 13
, 2001
"... Many cognitive processes occur on time scales that can significantly affect the shape of the blood oxygenation level-dependent (BOLD) response in eventrelated functional MRI. This shape can be estimated from event related designs, even if these processes occur in a fixed temporal sequence (J. M. Oll ..."
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Cited by 113 (3 self)
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Many cognitive processes occur on time scales that can significantly affect the shape of the blood oxygenation level-dependent (BOLD) response in eventrelated functional MRI. This shape can be estimated from event related designs, even if these processes occur in a fixed temporal sequence (J. M. Ollinger, G. L. Shulman, and M. Corbetta. 2001. NeuroImage 13: 210–217). Several important considerations come into play when interpreting these time courses. First, in single subjects, correlations among neighboring time points give the noise a smooth appearance that can be confused with changes in the BOLD response. Second, the variance and degree of correlation among estimated time courses are strongly influenced by the timing of the experimental design. Simulations show that optimal results are obtained if the intertrial intervals are as short as possible, if they follow an exponential distribution with at least three distinct values, and if 40 % of the trials are partial trials. These results are not particularly sensitive to the fraction of partial trials, so accurate estimation of time courses can be obtained with lower percentages of partial trials (20–25%). Third, statistical maps can be formed from F statistics computed with the extra sum of square principle or by t statistics computed from the cross-correlation of the time courses with a model for the hemodynamic response. The latter method relies on an accurate model for the hemodynamic response. The most robust model among those tested was a single gamma function. Finally, the power spectrum of the measured BOLD signal in rapid event-related paradigms is similar to that of the noise. Nevertheless, highpass filtering is desirable if the appropriate model
Classical and Bayesian inference in neuroimaging: applications
- NeuroImage
"... introduced empirical Bayes as a potentially useful way to estimate and make inferences about effects in hierarchical models. In this paper we present a series of models that exemplify the diversity of problems that can be addressed within this framework. In hierarchical linear observation models, bo ..."
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Cited by 111 (14 self)
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introduced empirical Bayes as a potentially useful way to estimate and make inferences about effects in hierarchical models. In this paper we present a series of models that exemplify the diversity of problems that can be addressed within this framework. In hierarchical linear observation models, both classical and empirical Bayesian approaches can be framed in terms of covariance component estimation (e.g., variance partitioning). To illustrate the use of the expectation– maximization (EM) algorithm in covariance component estimation we focus first on two important problems in fMRI: nonsphericity induced by (i) serial or temporal correlations among errors and (ii) variance components caused by the hierarchical nature of multisubject studies. In hierarchical observation models,
Event-related functional magnetic resonance imaging: modelling, . . .
, 1999
"... Event-related functional magnetic resonance imaging is a recent and popular technique for detecting haemodynamic responses to brief stimuli or events. However, the design of event-related experiments requires careful consideration of numerous issues of measurement, modelling and inference. Here we r ..."
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Cited by 99 (3 self)
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Event-related functional magnetic resonance imaging is a recent and popular technique for detecting haemodynamic responses to brief stimuli or events. However, the design of event-related experiments requires careful consideration of numerous issues of measurement, modelling and inference. Here we review these issues, with particular emphasis on the use of basis functions within a general linear modelling framework to model and make inferences about the haemodynamic response. With these models in mind, we then consider how the properties of functional magnetic resonance imaging data determine the optimal experimental design for a specific hypothesis, in terms of stimulus ordering and interstimulus interval. Finally, we illustrate various event-related models with examples from recent studies.
An event-related neuroimaging study distinguishing form and content in sentence processing
- J Cogn Neurosci
, 2000
"... & Two coordinated experiments using functional Magnetic Resonance Imaging (fMRI) investigated whether the brain represents language form (grammatical structure) separately from its meaning content (semantics). While in the scanner, 14 young, unimpaired adults listened to simple sentences that we ..."
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Cited by 83 (4 self)
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& Two coordinated experiments using functional Magnetic Resonance Imaging (fMRI) investigated whether the brain represents language form (grammatical structure) separately from its meaning content (semantics). While in the scanner, 14 young, unimpaired adults listened to simple sentences that were either nonanomalous or contained a grammatical error (for example, *Trees can grew.), or a semantic anomaly (for example, *Trees can eat.). A same/different tone pitch judgment task provided a baseline that isolated brain activity associated with linguistic processing from background activity generated by attention to the task and analysis of the auditory input. Sites selectively activated by sentence processing were found in both hemispheres in inferior frontal, middle, and superior frontal, superior temporal, and temporo-parietal regions. Effects of syntactic and semantic anomalies were differentiated by some nonoverlapping areas of activation: Syntactic anomaly triggered significantly increased activity in and around Broca’s area, whereas semantic anomaly activated several other sites anteriorly and posteriorly, among them Wernicke’s area. These dissociations occurred when listeners were not required to attend to the anomaly. The results confirm that linguistic operations in sentence processing can be isolated from nonlinguistic operations and support the hypothesis of a specialization for syntactic processing. &
Optimization of experimental design in fMRI: a general framework using a genetic algorithm
, 2003
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Characterizing Stimulus-Response Functions Using Nonlinear Regressors in Parametric fMRI Experiments
, 1998
"... this paper. C.B., A.P.H., G.R., and K.J.F. were funded by the Wellcome Trust ..."
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Cited by 76 (2 self)
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this paper. C.B., A.P.H., G.R., and K.J.F. were funded by the Wellcome Trust
To smooth or not to smooth? Bias and efficiency in fMRI time-series analysis
- NeuroImage
, 2000
"... This paper concerns temporal filtering in fMRI timeseries analysis. Whitening serially correlated data is the most efficient approach to parameter estimation. However, if there is a discrepancy between the assumed and the actual correlations, whitening can render the analysis exquisitely sensitive t ..."
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Cited by 60 (4 self)
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This paper concerns temporal filtering in fMRI timeseries analysis. Whitening serially correlated data is the most efficient approach to parameter estimation. However, if there is a discrepancy between the assumed and the actual correlations, whitening can render the analysis exquisitely sensitive to bias when estimating the standard error of the ensuing parameter estimates. This bias, although not expressed in terms of the estimated responses, has profound effects on any statistic used for inference. The special constraints of fMRI analysis ensure that there will always be a misspecification of the assumed serial correlations. One resolution of this problem is to filter the data to minimize bias, while maintaining a reasonable degree of efficiency. In this paper we present expressions for efficiency (of parameter estimation) and bias (in estimating standard error) in terms of assumed and actual correlation structures in the context of the general linear model. We show that: (i) Whitening strategies can result in profound bias and are therefore probably precluded in parametric fMRI data analyses. (ii) Band-pass filtering, and implicitly smoothing, has an important role in protecting against inferential
