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Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate(More)
The surface of the human cerebral cortex is a highly folded sheet with the majority of its surface area buried within folds. As such, it is a difficult domain for computational as well as visualization purposes. We have therefore designed a set of procedures for modifying the representation of the cortical surface to (i) inflate it so that activity buried(More)
We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel,(More)
Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist.(More)
The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical(More)
In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information(More)
The borders of human visual areas V1, V2, VP, V3, and V4 were precisely and noninvasively determined. Functional magnetic resonance images were recorded during phase-encoded retinal stimulation. This volume data set was then sampled with a cortical surface reconstruction, making it possible to calculate the local visual field sign (mirror image versus(More)
An important challenge in the design and analysis of event-related or single-trial functional magnetic resonance imaging (fMRI) experiments is to optimize statistical efficiency, i.e., the accuracy with which the event-related hemodynamic response to different stimuli can be estimated for a given amount of imaging time. Several studies have suggested that(More)
Using functional magnetic resonance imaging (fMRI) and cortical unfolding techniques, we analyzed the retinotopy, motion sensitivity, and functional organization of human area V3A. These data were compared with data from additional human cortical visual areas, including V1, V2, V3/VP, V4v, and MT (V5). Human V3A has a retinotopy that is similar to that(More)
A major limitation in conducting functional neuroimaging studies, particularly for cognitive experiments, has been the use of blocked task paradigms. Here we explored whether selective averaging techniques similar to those applied in event-related potential (ERP) experiments could be used to demonstrate functional magnetic resonance imaging (fMRI) responses(More)