Literature DB >> 30731246

A critical assessment of data quality and venous effects in sub-millimeter fMRI.

Kendrick Kay1, Keith W Jamison2, Luca Vizioli2, Ruyuan Zhang2, Eshed Margalit3, Kamil Ugurbil2.   

Abstract

Advances in hardware, pulse sequences, and reconstruction techniques have made it possible to perform functional magnetic resonance imaging (fMRI) at sub-millimeter resolution while maintaining high spatial coverage and acceptable signal-to-noise ratio. Here, we examine whether sub-millimeter fMRI can be used as a routine method for obtaining accurate measurements of fine-scale local neural activity. We conducted fMRI in human visual cortex during a simple event-related visual experiment (7 T, gradient-echo EPI, 0.8-mm isotropic voxels, 2.2-s sampling rate, 84 slices), and developed analysis and visualization tools to assess the quality of the data. Our results fall along three lines of inquiry. First, we find that the acquired fMRI images, combined with appropriate surface-based processing, provide reliable and accurate measurements of fine-scale blood oxygenation level dependent (BOLD) activity patterns. Second, we show that the highly folded structure of cortex causes substantial biases on spatial resolution and data visualization. Third, we examine the well-recognized issue of venous contributions to fMRI signals. In a systematic assessment of large sections of cortex measured at a fine scale, we show that time-averaged T2*-weighted EPI intensity is a simple, robust marker of venous effects. These venous effects are unevenly distributed across cortex, are more pronounced in gyri and outer cortical depths, and are, to a certain degree, in consistent locations across subjects relative to cortical folding. Furthermore, we show that these venous effects are strongly correlated with BOLD responses evoked by the experiment. We conclude that sub-millimeter fMRI can provide robust information about fine-scale BOLD activity patterns, but special care must be exercised in visualizing and interpreting these patterns, especially with regards to the confounding influence of the brain's vasculature. To help translate these methodological findings to neuroscience research, we provide practical suggestions for both high-resolution and standard-resolution fMRI studies.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BOLD signal; Cortical curvature; Cortical depth; High-resolution fMRI; Vasculature; Veins

Mesh:

Year:  2019        PMID: 30731246     DOI: 10.1016/j.neuroimage.2019.02.006

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  23 in total

1.  The morphology of the human cerebrovascular system.

Authors:  Michaël Bernier; Stephen C Cunnane; Kevin Whittingstall
Journal:  Hum Brain Mapp       Date:  2018-09-28       Impact factor: 5.038

2.  Intracortical smoothing of small-voxel fMRI data can provide increased detection power without spatial resolution losses compared to conventional large-voxel fMRI data.

Authors:  Anna I Blazejewska; Bruce Fischl; Lawrence L Wald; Jonathan R Polimeni
Journal:  Neuroimage       Date:  2019-01-25       Impact factor: 6.556

3.  Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception.

Authors:  Adrian K T Ng; Ke Jia; Nuno R Goncalves; Elisa Zamboni; Valentin G Kemper; Rainer Goebel; Andrew E Welchman; Zoe Kourtzi
Journal:  J Neurosci       Date:  2021-08-19       Impact factor: 6.167

4.  Non-neural factors influencing BOLD response magnitudes within individual subjects.

Authors:  Jan W Kurzawski; Omer Faruk Gulban; Keith Jamison; Jonathan Winawer; Kendrick Kay
Journal:  J Neurosci       Date:  2022-08-12       Impact factor: 6.709

5.  A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence.

Authors:  Emily J Allen; Ghislain St-Yves; Yihan Wu; Jesse L Breedlove; Jacob S Prince; Logan T Dowdle; Matthias Nau; Brad Caron; Franco Pestilli; Ian Charest; J Benjamin Hutchinson; Thomas Naselaris; Kendrick Kay
Journal:  Nat Neurosci       Date:  2021-12-16       Impact factor: 28.771

6.  Ultra-high-resolution fMRI of Human Ventral Temporal Cortex Reveals Differential Representation of Categories and Domains.

Authors:  Eshed Margalit; Keith W Jamison; Kevin S Weiner; Luca Vizioli; Ru-Yuan Zhang; Kendrick N Kay; Kalanit Grill-Spector
Journal:  J Neurosci       Date:  2020-02-24       Impact factor: 6.167

7.  Fast Polynomial Approximation of Heat Kernel Convolution on Manifolds and Its Application to Brain Sulcal and Gyral Graph Pattern Analysis.

Authors:  Shih-Gu Huang; Ilwoo Lyu; Anqi Qiu; Moo K Chung
Journal:  IEEE Trans Med Imaging       Date:  2020-01-17       Impact factor: 10.048

8.  A temporal decomposition method for identifying venous effects in task-based fMRI.

Authors:  Kendrick Kay; Keith W Jamison; Ru-Yuan Zhang; Kamil Uğurbil
Journal:  Nat Methods       Date:  2020-09-07       Impact factor: 28.547

Review 9.  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

10.  Mapping of whole-cerebrum resting-state networks using ultra-high resolution acquisition protocols.

Authors:  Seong Dae Yun; Patricia Pais-Roldán; Nicola Palomero-Gallagher; N Jon Shah
Journal:  Hum Brain Mapp       Date:  2022-04-06       Impact factor: 5.399

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