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Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a long-standing problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures for multiple hypothesis testing (e.g., Bonferroni) tend to not be(More)
More than one subject is scanned in a typical functional brain imaging experiment. How can the scientist make best use of the acquired data to map the specific areas of the brain that become active during the performance of different tasks? It is clear that we can gain both scientific and statistical power by pooling the images from multiple subjects;(More)
To characterize cognitive maturation through adolescence, processing speed, voluntary response suppression, and spatial working memory were measured in 8- to 30-year-old (N = 245) healthy participants using oculomotor tasks. Development progressed with a steep initial improvement in performance followed by stabilization in adolescence. Adult-level mature(More)
OBJECTIVE To test the hypothesis that deficits in spatial working memory in autism are due to abnormalities in prefrontal circuitry. METHODS Functional MRI (fMRI) at 3 T was performed in 11 rigorously diagnosed non-mentally retarded autistic and six healthy volunteers while they performed an oculomotor spatial working memory task and a visually guided(More)
OBJECTIVE The relationship between athlete reports of symptoms, neurophysiological activation, and neuropsychological functioning is investigated in a sample of high school athletes. METHODS All athletes were evaluated using functional magnetic resonance imaging (fMRI), a computer-based battery of neurocognitive tests, and a subjective symptom scale.(More)
In this paper, we propose an approach to modeling functional magnetic resonance imaging (fMRI) data that combines hierarchical polynomial models, Bayes estimation, and clustering. A cubic polynomial is used to fit the voxel time courses of event-related design experiments. The coefficients of the polynomials are estimated by Bayes estimation, in a two-level(More)
Group maps created from individual functional maps provide useful summaries of patterns of brain activation. Different methods for combining information have been proposed in the statistical literature and have been recently applied to fMRI data. Since these group maps are statistics, it is natural to ask how robust they are, that is, are they sensitive to(More)
Functional magnetic resonance imaging (fMRI) provides a means of identifying neural circuitry associated with startle and its modulation in humans. Twelve subjects who demonstrated eyeblink startle in the laboratory were recruited for an fMRI study in which they were scanned while presented with two identical runs consisting of alternating blocks of no(More)
Clustering is used in fMRI time series data analysis to find the active regions in the brain related to a stimulus. However, clustering algorithms usually do not work well for ill-balanced data, i.e., when only a small proportion of the voxels in the brain respond to the stimulus. This is the typical situation in fMRI--most voxels do not, in fact, respond(More)
In their article, Vul, Harris, Winkielman, and Pashler (2009), (this issue) raise the issue of nonindependent analysis in behavioral neuroimaging, whereby correlations are artificially inflated as a result of spurious statistical procedures. In this comment, I note that the phenomenon in question is a type of selection bias and hence is neither new nor(More)