Literature DB >> 17405190

Very high-resolution three-dimensional functional MRI of the human visual cortex with elimination of large venous vessels.

M Barth1, D G Norris.   

Abstract

We propose a very high-resolution, three-dimensional (3D) gradient-echo technique with a twofold parallel imaging acceleration using a specialized occipital receiver coil at 3 T to perform functional MRI (fMRI) of the visual cortex. This configuration makes it possible to acquire 3D fMRI data within a timescale compatible with a block design. Without further processing, the functional maps at an isotropic 3D resolution of 0.42 microL (0.75 mm voxel size) and near-isotropic resolution of 1.2 microL (1 mm voxel size) show very robust activation in visual areas, but with clear contamination from larger veins. As this technique allows direct identification of veins in the functional scan, it permits removal of their effect from the activation maps. In our study, elimination of veins qualitatively improves the spatial specificity of activation maps, while reducing the activated volume by about 25%. The proposed technique provides functional information at the resolution of anatomical scans, is localized to gray matter, and facilitates functional to anatomical co-registration because of minimal distortions. Copyright 2007 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Year:  2007        PMID: 17405190     DOI: 10.1002/nbm.1158

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  14 in total

1.  MR venography of the human brain using susceptibility weighted imaging at very high field strength.

Authors:  Peter J Koopmans; Rashindra Manniesing; Wiro J Niessen; Max A Viergever; Markus Barth
Journal:  MAGMA       Date:  2008-01-11       Impact factor: 2.310

2.  Adjacent visual representations of self-motion in different reference frames.

Authors:  David Mattijs Arnoldussen; Jeroen Goossens; Albert V van den Berg
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-27       Impact factor: 11.205

3.  Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T.

Authors:  João Jorge; Patrícia Figueiredo; Rolf Gruetter; Wietske van der Zwaag
Journal:  Hum Brain Mapp       Date:  2018-02-20       Impact factor: 5.038

4.  T2-weighted 3D fMRI using S2-SSFP at 7 tesla.

Authors:  Markus Barth; Heiko Meyer; Stephan A R Kannengiesser; Jonathan R Polimeni; Lawrence L Wald; David G Norris
Journal:  Magn Reson Med       Date:  2010-04       Impact factor: 4.668

5.  Laminar analysis of 7T BOLD using an imposed spatial activation pattern in human V1.

Authors:  Jonathan R Polimeni; Bruce Fischl; Douglas N Greve; Lawrence L Wald
Journal:  Neuroimage       Date:  2010-05-09       Impact factor: 6.556

6.  Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals.

Authors:  Yi He; Maosen Wang; Xuming Chen; Rolf Pohmann; Jonathan R Polimeni; Klaus Scheffler; Bruce R Rosen; David Kleinfeld; Xin Yu
Journal:  Neuron       Date:  2018-02-21       Impact factor: 17.173

7.  Layer-specific BOLD activation in human V1.

Authors:  Peter J Koopmans; Markus Barth; David G Norris
Journal:  Hum Brain Mapp       Date:  2010-09       Impact factor: 5.038

8.  Regional variations in vascular density correlate with resting-state and task-evoked blood oxygen level-dependent signal amplitude.

Authors:  Nicolas Vigneau-Roy; Michaël Bernier; Maxime Descoteaux; Kevin Whittingstall
Journal:  Hum Brain Mapp       Date:  2013-07-11       Impact factor: 5.038

9.  Predicting the fMRI Signal Fluctuation with Recurrent Neural Networks Trained on Vascular Network Dynamics.

Authors:  Filip Sobczak; Yi He; Terrence J Sejnowski; Xin Yu
Journal:  Cereb Cortex       Date:  2021-01-05       Impact factor: 5.357

Review 10.  New acquisition techniques and their prospects for the achievable resolution of fMRI.

Authors:  Saskia Bollmann; Markus Barth
Journal:  Prog Neurobiol       Date:  2020-10-23       Impact factor: 11.685

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