Literature DB >> 33744454

Which multiband factor should you choose for your resting-state fMRI study?

Benjamin B Risk1, Raphiel J Murden2, Junjie Wu3, Mary Beth Nebel4, Arun Venkataraman5, Zhengwu Zhang6, Deqiang Qiu3.   

Abstract

Multiband acquisition, also called simultaneous multislice, has become a popular technique in resting-state functional connectivity studies. Multiband (MB) acceleration leads to a higher temporal resolution but also leads to spatially heterogeneous noise amplification, suggesting the costs may be greater in areas such as the subcortex. We evaluate MB factors of 2, 3, 4, 6, 8, 9, and 12 with 2 mm isotropic voxels, and additionally 2 mm and 3.3 mm single-band acquisitions, on a 32-channel head coil. Noise amplification was greater in deeper brain regions, including subcortical regions. Correlations were attenuated by noise amplification, which resulted in spatially varying biases that were more severe at higher MB factors. Temporal filtering decreased spatial biases in correlations due to noise amplification, but also tended to decrease effect sizes. In seed-based correlation maps, left-right putamen connectivity and thalamo-motor connectivity were highest in the single-band 3.3 mm protocol. In correlation matrices, MB 4, 6, and 8 had a greater number of significant correlations than the other acquisitions (both with and without temporal filtering). We recommend single-band 3.3 mm for seed-based subcortical analyses, and MB 4 provides a reasonable balance for studies analyzing both seed-based correlation maps and connectivity matrices. In multiband studies including secondary analyses of large-scale datasets, we recommend reporting effect sizes or test statistics instead of correlations. If correlations are reported, temporal filtering (or another method for thermal noise removal) should be used. The Emory Multiband Dataset is available on OpenNeuro.
Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Acceleration; Functional connectivity; Noise amplification; Putamen; Simultaneous multislice; Subcortical; Temporal resolution; Thalamus

Year:  2021        PMID: 33744454     DOI: 10.1016/j.neuroimage.2021.117965

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


  5 in total

1.  Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder.

Authors:  Veronika Vilgis; Debbie Yee; Tim J Silk; Alasdair Vance
Journal:  Cogn Affect Behav Neurosci       Date:  2022-03-29       Impact factor: 3.526

2.  Reliability and stability challenges in ABCD task fMRI data.

Authors:  James T Kennedy; Michael P Harms; Ozlem Korucuoglu; Serguei V Astafiev; Deanna M Barch; Wesley K Thompson; James M Bjork; Andrey P Anokhin
Journal:  Neuroimage       Date:  2022-03-01       Impact factor: 7.400

3.  The Dual Mechanisms of Cognitive Control dataset, a theoretically-guided within-subject task fMRI battery.

Authors:  Joset A Etzel; Rachel E Brough; Michael C Freund; Alexander Kizhner; Yanli Lin; Matthew F Singh; Rongxiang Tang; Allison Tay; Anxu Wang; Todd S Braver
Journal:  Sci Data       Date:  2022-03-29       Impact factor: 6.444

4.  Covariance shrinkage can assess and improve functional connectomes.

Authors:  Nicolas Honnorat; Mohamad Habes
Journal:  Neuroimage       Date:  2022-04-20       Impact factor: 7.400

5.  Multi-band FMRI compromises detection of mesolimbic reward responses.

Authors:  Tara Srirangarajan; Leili Mortazavi; Tiago Bortolini; Jorge Moll; Brian Knutson
Journal:  Neuroimage       Date:  2021-09-29       Impact factor: 6.556

  5 in total

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