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Multisite reliability of cognitive BOLD data.

Publication ,  Journal Article
Brown, GG; Mathalon, DH; Stern, H; Ford, J; Mueller, B; Greve, DN; McCarthy, G; Voyvodic, J; Glover, G; Diaz, M; Yetter, E; Ozyurt, IB ...
Published in: Neuroimage
February 1, 2011

Investigators perform multi-site functional magnetic resonance imaging studies to increase statistical power, to enhance generalizability, and to improve the likelihood of sampling relevant subgroups. Yet undesired site variation in imaging methods could off-set these potential advantages. We used variance components analysis to investigate sources of variation in the blood oxygen level-dependent (BOLD) signal across four 3-T magnets in voxelwise and region-of-interest (ROI) analyses. Eighteen participants traveled to four magnet sites to complete eight runs of a working memory task involving emotional or neutral distraction. Person variance was more than 10 times larger than site variance for five of six ROIs studied. Person-by-site interactions, however, contributed sizable unwanted variance to the total. Averaging over runs increased between-site reliability, with many voxels showing good to excellent between-site reliability when eight runs were averaged and regions of interest showing fair to good reliability. Between-site reliability depended on the specific functional contrast analyzed in addition to the number of runs averaged. Although median effect size was correlated with between-site reliability, dissociations were observed for many voxels. Brain regions where the pooled effect size was large but between-site reliability was poor were associated with reduced individual differences. Brain regions where the pooled effect size was small but between-site reliability was excellent were associated with a balance of participants who displayed consistently positive or consistently negative BOLD responses. Although between-site reliability of BOLD data can be good to excellent, acquiring highly reliable data requires robust activation paradigms, ongoing quality assurance, and careful experimental control.

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Published In

Neuroimage

DOI

EISSN

1095-9572

Publication Date

February 1, 2011

Volume

54

Issue

3

Start / End Page

2163 / 2175

Location

United States

Related Subject Headings

  • Young Adult
  • Reproducibility of Results
  • Quality Control
  • Oxygen
  • Neurology & Neurosurgery
  • Middle Aged
  • Memory, Short-Term
  • Male
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
 

Citation

APA
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ICMJE
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Brown, G. G., Mathalon, D. H., Stern, H., Ford, J., Mueller, B., Greve, D. N., … Function Biomedical Informatics Research Network, . (2011). Multisite reliability of cognitive BOLD data. Neuroimage, 54(3), 2163–2175. https://doi.org/10.1016/j.neuroimage.2010.09.076
Brown, Gregory G., Daniel H. Mathalon, Hal Stern, Judith Ford, Bryon Mueller, Douglas N. Greve, Gregory McCarthy, et al. “Multisite reliability of cognitive BOLD data.Neuroimage 54, no. 3 (February 1, 2011): 2163–75. https://doi.org/10.1016/j.neuroimage.2010.09.076.
Brown GG, Mathalon DH, Stern H, Ford J, Mueller B, Greve DN, et al. Multisite reliability of cognitive BOLD data. Neuroimage. 2011 Feb 1;54(3):2163–75.
Brown, Gregory G., et al. “Multisite reliability of cognitive BOLD data.Neuroimage, vol. 54, no. 3, Feb. 2011, pp. 2163–75. Pubmed, doi:10.1016/j.neuroimage.2010.09.076.
Brown GG, Mathalon DH, Stern H, Ford J, Mueller B, Greve DN, McCarthy G, Voyvodic J, Glover G, Diaz M, Yetter E, Ozyurt IB, Jorgensen KW, Wible CG, Turner JA, Thompson WK, Potkin SG, Function Biomedical Informatics Research Network. Multisite reliability of cognitive BOLD data. Neuroimage. 2011 Feb 1;54(3):2163–2175.
Journal cover image

Published In

Neuroimage

DOI

EISSN

1095-9572

Publication Date

February 1, 2011

Volume

54

Issue

3

Start / End Page

2163 / 2175

Location

United States

Related Subject Headings

  • Young Adult
  • Reproducibility of Results
  • Quality Control
  • Oxygen
  • Neurology & Neurosurgery
  • Middle Aged
  • Memory, Short-Term
  • Male
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted