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Dive into the research topics where David C. Van Essen is active.

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Featured researches published by David C. Van Essen.


Neuron | 1998

A Common Network of Functional Areas for Attention and Eye Movements

Maurizio Corbetta; Erbil Akbudak; Thomas E. Conturo; Abraham Z. Snyder; John M. Ollinger; Heather A. Drury; Martin R Linenweber; Steven E. Petersen; Marcus E. Raichle; David C. Van Essen; Gordon L. Shulman

Functional magnetic resonance imaging (fMRI) and surface-based representations of brain activity were used to compare the functional anatomy of two tasks, one involving covert shifts of attention to peripheral visual stimuli, the other involving both attentional and saccadic shifts to the same stimuli. Overlapping regional networks in parietal, frontal, and temporal lobes were active in both tasks. This anatomical overlap is consistent with the hypothesis that attentional and oculomotor processes are tightly integrated at the neural level.


NeuroImage | 2005

A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex

David C. Van Essen

This report describes a new electronic atlas of human cerebral cortex that provides a substrate for a wide variety of brain-mapping analyses. The Population-Average, Landmark- and Surface-based (PALS) atlas approach involves surface-based and volume-based representations of cortical shape, each available as population averages and as individual subject data. The specific PALS-B12 atlas introduced here is derived from structural MRI volumes of 12 normal young adults. Accurate cortical surface reconstructions were generated for each hemisphere, and the surfaces were inflated, flattened, and mapped to standard spherical configurations using SureFit and Caret software. A target atlas sphere was generated by averaging selected landmark contours from each of the 24 contributing hemispheres. Each individual hemisphere was deformed to this target using landmark-constrained surface registration. The utility of the resultant PALS-B12 atlas was demonstrated using a variety of analyses. (i) Probabilistic maps of sulcal identity were generated using both surface-based registration (SBR) and conventional volume-based registration (VBR). The SBR approach achieved markedly better consistency of sulcal alignment than did VBR. (ii) A method is introduced for dmulti-fiducial mappingT of volume-averaged group data (e.g., fMRI data, probabilistic architectonic maps) onto each individual hemisphere in the atlas, followed by spatial averaging across the individual maps. This yielded a population-average surface representation that circumvents the biases inherent in choosing any single hemisphere as a target. (iii) Surface-based and volume-based morphometry applied to maps of sulcal depth and sulcal identity demonstrated prominent left–right asymmetries in and near the superior temporal sulcus and Sylvian fissure. Moreover, shape variability in the temporal lobe is significantly greater in the left than the right hemisphere. The PALS-B12 atlas has been registered to other surface-based atlases to facilitate interchange of data and comparison across atlases. All data sets in the PALS-B12 atlas are accessible via the SumsDB database for online and offline


Journal of the American Medical Informatics Association | 2001

An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex

David C. Van Essen; Heather A. Drury; James Dickson; John W. Harwell; Donna Hanlon; Charles H. Anderson

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.


NeuroImage | 2013

The WU-Minn Human Connectome Project: An Overview

David C. Van Essen; Stephen M. Smith; M Deanna; Timothy E. J. Behrens; Essa Yacoub; Kamil Ugurbil

The Human Connectome Project consortium led by Washington University, University of Minnesota, and Oxford University is undertaking a systematic effort to map macroscopic human brain circuits and their relationship to behavior in a large population of healthy adults. This overview article focuses on progress made during the first half of the 5-year project in refining the methods for data acquisition and analysis. Preliminary analyses based on a finalized set of acquisition and preprocessing protocols demonstrate the exceptionally high quality of the data from each modality. The first quarterly release of imaging and behavioral data via the ConnectomeDB database demonstrates the commitment to making HCP datasets freely accessible. Altogether, the progress to date provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings.


Trends in Neurosciences | 1983

Hierarchical organization and functional streams in the visual cortex

David C. Van Essen; John H. R. Maunsell

Abstract In the macaque monkey, a dozen distinct visual areas have been identified in the cerebral cortex. These areas can be arranged in a well-defined hierarchy on the basis of their pattern of interconnections. Physiological recordings suggest that there are at least two major functional streams in this hierarchy, one related to the analysis of motion and the other to the analysis of form and color.


NeuroImage | 2013

The minimal preprocessing pipelines for the Human Connectome Project

Matthew F. Glasser; Stamatios N. Sotiropoulos; J. Anthony Wilson; Timothy S. Coalson; Bruce Fischl; Jesper Andersson; Junqian Xu; Saâd Jbabdi; Matthew A. Webster; Jonathan R. Polimeni; David C. Van Essen; Mark Jenkinson

The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3 Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCPs acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines.


The Journal of Comparative Neurology | 2000

Corticocortical connections of visual, sensorimotor, and multimodal processing areas in the parietal lobe of the macaque monkey

James W. Lewis; David C. Van Essen

We studied the corticocortical connections of architectonically defined areas of parietal and temporoparietal cortex, with emphasis on areas in the intraparietal sulcus (IPS) that are implicated in visual and somatosensory integration. Retrograde tracers were injected into selected areas of the IPS, superior temporal sulcus, and parietal lobule. The distribution of labeled cells was charted in relation to architectonically defined borders throughout the hemisphere and displayed on computer‐generated three‐dimensional reconstructions and on cortical flat maps. Injections centered in the ventral intraparietal area (VIP) revealed a complex pattern of inputs from numerous visual, somatosensory, motor, and polysensory areas, and from presumed vestibular‐ and auditory‐related areas. Sensorimotor projections were predominantly from the upper body representations of at least six somatotopically organized areas. In contrast, injections centered in the neighboring ventral lateral intraparietal area (LIPv) revealed inputs mainly from extrastriate visual areas, consistent with previous studies. The pattern of inputs to LIPv largely overlapped those to zone MSTdp, a newly described subdivision of the medial superior temporal area. These results, in conjunction with those from injections into other parietal areas (7a, 7b, and anterior intraparietal area), support the fine‐grained architectonic partitioning of cortical areas described in the preceding study. They also support and extend previous evidence for multiple distributed networks that are implicated in multimodal integration, especially with regard to area VIP. J. Comp. Neurol. 428:112–137, 2000.


Nature | 2016

A multi-modal parcellation of human cerebral cortex

Matthew F. Glasser; Timothy S. Coalson; Emma C. Robinson; Carl D. Hacker; John W. Harwell; Essa Yacoub; Kamil Ugurbil; Jesper Andersson; Christian F. Beckmann; Mark Jenkinson; Stephen M. Smith; David C. Van Essen

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal ‘fingerprint’ of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.


Proceedings of the National Academy of Sciences of the United States of America | 2012

Temporally-independent functional modes of spontaneous brain activity

Stephen M. Smith; Karla L. Miller; Steen Moeller; Junqian Xu; Edward J. Auerbach; Mark W. Woolrich; Christian F. Beckmann; Mark Jenkinson; Jesper Andersson; Matthew F. Glasser; David C. Van Essen; David A. Feinberg; Essa Yacoub; Kamil Ugurbil

Resting-state functional magnetic resonance imaging has become a powerful tool for the study of functional networks in the brain. Even “at rest,” the brains different functional networks spontaneously fluctuate in their activity level; each networks spatial extent can therefore be mapped by finding temporal correlations between its different subregions. Current correlation-based approaches measure the average functional connectivity between regions, but this average is less meaningful for regions that are part of multiple networks; one ideally wants a network model that explicitly allows overlap, for example, allowing a regions activity pattern to reflect one networks activity some of the time, and another networks activity at other times. However, even those approaches that do allow overlap have often maximized mutual spatial independence, which may be suboptimal if distinct networks have significant overlap. In this work, we identify functionally distinct networks by virtue of their temporal independence, taking advantage of the additional temporal richness available via improvements in functional magnetic resonance imaging sampling rate. We identify multiple “temporal functional modes,” including several that subdivide the default-mode network (and the regions anticorrelated with it) into several functionally distinct, spatially overlapping, networks, each with its own pattern of correlations and anticorrelations. These functionally distinct modes of spontaneous brain activity are, in general, quite different from resting-state networks previously reported, and may have greater biological interpretability.


Trends in Cognitive Sciences | 2004

Comparative mapping of higher visual areas in monkeys and humans

Guy A. Orban; David C. Van Essen; Wim Vanduffel

The advent of functional magnetic resonance imaging (fMRI) in non-human primates has facilitated comparison of the neurobiology of cognitive functions in humans and macaque monkeys, the most intensively studied animal model for higher brain functions. Most of these comparative studies have been performed in the visual system. The early visual areas V1, V2 and V3, as well as the motion area MT are conserved in humans. Beyond these areas, differences between human and monkey functional organization are increasingly evident. At the regional level, the monkey inferotemporal and intraparietal complexes appear to be conserved in humans, but there are profound functional differences in the intraparietal cortex suggesting that not all its constituent areas are homologous. In the long term, fMRI offers opportunities to compare the functional anatomy of a variety of cognitive functions in the two species.

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Matthew F. Glasser

Washington University in St. Louis

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Donna L. Dierker

Washington University in St. Louis

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Timothy S. Coalson

Washington University in St. Louis

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John W. Harwell

Washington University in St. Louis

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Charles H. Anderson

California Institute of Technology

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Daniel J. Felleman

University of Texas at Austin

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Essa Yacoub

University of Minnesota

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Jack L. Gallant

California Institute of Technology

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M Deanna

Washington University in St. Louis

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