Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where David A. Feinberg is active.

Publication


Featured researches published by David A. Feinberg.


PLOS ONE | 2010

Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging

David A. Feinberg; Steen Moeller; Stephen M. Smith; Edward J. Auerbach; Sudhir Ramanna; Matt F. Glasser; Karla L. Miller; Kamil Ugurbil; Essa Yacoub

Echo planar imaging (EPI) is an MRI technique of particular value to neuroscience, with its use for virtually all functional MRI (fMRI) and diffusion imaging of fiber connections in the human brain. EPI generates a single 2D image in a fraction of a second; however, it requires 2–3 seconds to acquire multi-slice whole brain coverage for fMRI and even longer for diffusion imaging. Here we report on a large reduction in EPI whole brain scan time at 3 and 7 Tesla, without significantly sacrificing spatial resolution, and while gaining functional sensitivity. The multiplexed-EPI (M-EPI) pulse sequence combines two forms of multiplexing: temporal multiplexing (m) utilizing simultaneous echo refocused (SIR) EPI and spatial multiplexing (n) with multibanded RF pulses (MB) to achieve m×n images in an EPI echo train instead of the normal single image. This resulted in an unprecedented reduction in EPI scan time for whole brain fMRI performed at 3 Tesla, permitting TRs of 400 ms and 800 ms compared to a more conventional 2.5 sec TR, and 2–4 times reductions in scan time for HARDI imaging of neuronal fibertracks. The simultaneous SE refocusing of SIR imaging at 7 Tesla advantageously reduced SAR by using fewer RF refocusing pulses and by shifting fat signal out of the image plane so that fat suppression pulses were not required. In preliminary studies of resting state functional networks identified through independent component analysis, the 6-fold higher sampling rate increased the peak functional sensitivity by 60%. The novel M-EPI pulse sequence resulted in a significantly increased temporal resolution for whole brain fMRI, and as such, this new methodology can be used for studying non-stationarity in networks and generally for expanding and enriching the functional information.


NeuroImage | 2012

The Human Connectome Project: A data acquisition perspective

D. C. Van Essen; Kamil Ugurbil; Edward J. Auerbach; Timothy E. J. Behrens; Richard D. Bucholz; A. Chang; Liyong Chen; Maurizio Corbetta; Sandra W. Curtiss; S. Della Penna; David A. Feinberg; Matthew F. Glasser; Noam Harel; A. C. Heath; Linda J. Larson-Prior; Daniel S. Marcus; G. Michalareas; Steen Moeller; Robert Oostenveld; S.E. Petersen; Fred W. Prior; Bradley L. Schlaggar; Stephen M. Smith; Avi Snyder; Junqian Xu; Essa Yacoub

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences.


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.


NeuroImage | 2013

Resting-state fMRI in the Human Connectome Project

Stephen M. Smith; Christian F. Beckmann; Jesper Andersson; Edward J. Auerbach; Janine D. Bijsterbosch; Gwenaëlle Douaud; Eugene P. Duff; David A. Feinberg; Ludovica Griffanti; Michael P. Harms; Michael Kelly; Timothy O. Laumann; Karla L. Miller; Steen Moeller; S.E. Petersen; Jonathan D. Power; Gholamreza Salimi-Khorshidi; Avi Snyder; An T. Vu; Mark W. Woolrich; Junqian Xu; Essa Yacoub; Kamil Ugurbil; D. C. Van Essen; Matthew F. Glasser

Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI scanner, and taking advantage of the fact that functionally related brain regions spontaneously co-activate. rfMRI is one of the two primary data modalities being acquired for the Human Connectome Project (the other being diffusion MRI). A key objective is to generate a detailed in vivo mapping of functional connectivity in a large cohort of healthy adults (over 1000 subjects), and to make these datasets freely available for use by the neuroimaging community. In each subject we acquire a total of 1h of whole-brain rfMRI data at 3 T, with a spatial resolution of 2×2×2 mm and a temporal resolution of 0.7s, capitalizing on recent developments in slice-accelerated echo-planar imaging. We will also scan a subset of the cohort at higher field strength and resolution. In this paper we outline the work behind, and rationale for, decisions taken regarding the rfMRI data acquisition protocol and pre-processing pipelines, and present some initial results showing data quality and example functional connectivity analyses.


NeuroImage | 2013

Advances in diffusion MRI acquisition and processing in the Human Connectome Project

Stamatios N. Sotiropoulos; Saâd Jbabdi; Junqian Xu; Jesper Andersson; Steen Moeller; Edward J. Auerbach; Matthew F. Glasser; Moisés Hernández; Guillermo Sapiro; Mark Jenkinson; David A. Feinberg; Essa Yacoub; Christophe Lenglet; David C. Van Essen; Kamil Ugurbil; Timothy E. J. Behrens

The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013.


Journal of Magnetic Resonance | 2013

Ultra-fast MRI of the human brain with simultaneous multi-slice imaging.

David A. Feinberg; Kawin Setsompop

The recent advancement of simultaneous multi-slice imaging using multiband excitation has dramatically reduced the scan time of the brain. The evolution of this parallel imaging technique began over a decade ago and through recent sequence improvements has reduced the acquisition time of multi-slice EPI by over ten fold. This technique has recently become extremely useful for (i) functional MRI studies improving the statistical definition of neuronal networks, and (ii) diffusion based fiber tractography to visualize structural connections in the human brain. Several applications and evaluations are underway which show promise for this family of fast imaging sequences.


NeuroImage | 2013

Evaluation of slice accelerations using multiband echo planar imaging at 3 T.

Junqian Xu; Steen Moeller; Edward J. Auerbach; John Strupp; Stephen M. Smith; David A. Feinberg; Essa Yacoub; Kamil Ugurbil

We evaluate residual aliasing among simultaneously excited and acquired slices in slice accelerated multiband (MB) echo planar imaging (EPI). No in-plane accelerations were used in order to maximize and evaluate achievable slice acceleration factors at 3 T. We propose a novel leakage (L-) factor to quantify the effects of signal leakage between simultaneously acquired slices. With a standard 32-channel receiver coil at 3 T, we demonstrate that slice acceleration factors of up to eight (MB=8) with blipped controlled aliasing in parallel imaging (CAIPI), in the absence of in-plane accelerations, can be used routinely with acceptable image quality and integrity for whole brain imaging. Spectral analyses of single-shot fMRI time series demonstrate that temporal fluctuations due to both neuronal and physiological sources were distinguishable and comparable up to slice-acceleration factors of nine (MB=9). The increased temporal efficiency could be employed to achieve, within a given acquisition period, higher spatial resolution, increased fMRI statistical power, multiple TEs, faster sampling of temporal events in a resting state fMRI time series, increased sampling of q-space in diffusion imaging, or more quiet time during a scan.


PLOS ONE | 2012

Layer-Specific fMRI Reflects Different Neuronal Computations at Different Depths in Human V1

Cheryl A. Olman; Noam Harel; David A. Feinberg; Sheng He; Peng Zhang; Kamil Ugurbil; Essa Yacoub

Recent work has established that cerebral blood flow is regulated at a spatial scale that can be resolved by high field fMRI to show cortical columns in humans. While cortical columns represent a cluster of neurons with similar response properties (spanning from the pial surface to the white matter), important information regarding neuronal interactions and computational processes is also contained within a single column, distributed across the six cortical lamina. A basic understanding of underlying neuronal circuitry or computations may be revealed through investigations of the distribution of neural responses at different cortical depths. In this study, we used T2-weighted imaging with 0.7 mm (isotropic) resolution to measure fMRI responses at different depths in the gray matter while human subjects observed images with either recognizable or scrambled (physically impossible) objects. Intact and scrambled images were partially occluded, resulting in clusters of activity distributed across primary visual cortex. A subset of the identified clusters of voxels showed a preference for scrambled objects over intact; in these clusters, the fMRI response in middle layers was stronger during the presentation of scrambled objects than during the presentation of intact objects. A second experiment, using stimuli targeted at either the magnocellular or the parvocellular visual pathway, shows that laminar profiles in response to parvocellular-targeted stimuli peak in more superficial layers. These findings provide new evidence for the differential sensitivity of high-field fMRI to modulations of the neural responses at different cortical depths.


PLOS ONE | 2011

Mapping the organization of axis of motion selective features in human area mt using high-field fmri

Jan Zimmermann; Rainer Goebel; Federico De Martino; Pierre-Francois Van de Moortele; David A. Feinberg; Gregor Adriany; Denis Chaimow; Amir Shmuel; Kamil Ugurbil; Essa Yacoub

Functional magnetic resonance imaging (fMRI) at high magnetic fields has made it possible to investigate the columnar organization of the human brain in vivo with high degrees of accuracy and sensitivity. Until now, these results have been limited to the organization principles of early visual cortex (V1). While the middle temporal area (MT) has been the first identified extra-striate visual area shown to exhibit a columnar organization in monkeys, evidence of MTs columnar response properties and topographic layout in humans has remained elusive. Research using various approaches suggests similar response properties as in monkeys but failed to provide direct evidence for direction or axis of motion selectivity in human area MT. By combining state of the art pulse sequence design, high spatial resolution in all three dimensions (0.8 mm isotropic), optimized coil design, ultrahigh field magnets (7 Tesla) and novel high resolution cortical grid sampling analysis tools, we provide the first direct evidence for large-scale axis of motion selective feature organization in human area MT closely matching predictions from topographic columnar-level simulations.


Journal of Cerebral Blood Flow and Metabolism | 2008

Measuring the effects of remifentanil on cerebral blood flow and arterial arrival time using 3D GRASE MRI with pulsed arterial spin labelling

Bradley J. MacIntosh; Kyle T.S. Pattinson; Daniel Gallichan; Imran Ahmad; Karla L. Miller; David A. Feinberg; Richard Geoffrey Wise; Peter Jezzard

Arterial spin labelling (ASL) has proved to be a promising magnetic resonance imaging (MRI) technique to measure brain perfusion. In this study, volumetric three-dimensional (3D) gradient and spin echo (GRASE) ASL was used to produce cerebral blood flow (CBF) and arterial arrival time (AAT) maps during rest and during an infusion of remifentanil. Gradient and spin echo ASL perfusion-weighted images were collected at multiple inflow times (500 to 2,500 ms in increments of 250 ms) to accurately fit an ASL perfusion model. Fit estimates were assessed using z-statistics, allowing voxels with a poor fit to be excluded from subsequent analyses. Nonparametric permutation testing showed voxels with a significant difference in CBF and AAT between conditions across a group of healthy participants (N = 10). Administration of remifentanil produced an increase in end-tidal CO2, an increase in CBF from 57 ± 12.0 to 77 ± 18.4 mL/100 g tissue per min and a reduction in AAT from 0.73 ± 0.073 to 0.64 ± 0.076 secs. Within grey matter, remifentanil produced a cerebrovascular response of 5.7 ± 1.60 %CBF per mm Hg. Significant differences between physiologic conditions were observed in both CBF and AAT maps, indicating that 3D GRASE-ASL has the sensitivity to study changes in physiology at a voxel level.

Collaboration


Dive into the David A. Feinberg's collaboration.

Top Co-Authors

Avatar

Essa Yacoub

University of Minnesota

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Junqian Xu

Icahn School of Medicine at Mount Sinai

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

An T. Vu

Helen Wills Neuroscience Institute

View shared research outputs
Top Co-Authors

Avatar

Matthew F. Glasser

Washington University in St. Louis

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge