Literature DB >> 29113944

Reliability of functional magnetic resonance imaging activation during working memory in a multisite study: Clarification and implications for statistical power.

Tyrone D Cannon1, Hengyi Cao2, Daniel H Mathalon3, Jennifer Forsyth4.   

Abstract

In this technical note, we clarify the meaning of the generalizability-theory based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during working memory processing (Forsyth et al., Neuroimage 2014;97:51-52). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single site study design for statistical power, including a figure that shows sample size requirements to detect activation in two key nodes of the working memory circuitry given observed differences in reliability of measurement between single and multisite designs.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 29113944      PMCID: PMC5716858          DOI: 10.1016/j.neuroimage.2017.11.005

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


  1 in total

1.  Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: analysis from the North American Prodrome Longitudinal Study.

Authors:  Jennifer K Forsyth; Sarah C McEwen; Dylan G Gee; Carrie E Bearden; Jean Addington; Brad Goodyear; Kristin S Cadenhead; Heline Mirzakhanian; Barbara A Cornblatt; Doreen M Olvet; Daniel H Mathalon; Thomas H McGlashan; Diana O Perkins; Aysenil Belger; Larry J Seidman; Heidi W Thermenos; Ming T Tsuang; Theo G M van Erp; Elaine F Walker; Stephan Hamann; Scott W Woods; Maolin Qiu; Tyrone D Cannon
Journal:  Neuroimage       Date:  2014-04-13       Impact factor: 6.556

  1 in total
  3 in total

1.  A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data.

Authors:  Colin Hawco; Joseph D Viviano; Sofia Chavez; Erin W Dickie; Navona Calarco; Peter Kochunov; Miklos Argyelan; Jessica A Turner; Anil K Malhotra; Robert W Buchanan; Aristotle N Voineskos
Journal:  Psychiatry Res Neuroimaging       Date:  2018-06-09       Impact factor: 2.376

2.  Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms.

Authors:  Hengyi Cao; Sarah C McEwen; Jennifer K Forsyth; Dylan G Gee; Carrie E Bearden; Jean Addington; Bradley Goodyear; Kristin S Cadenhead; Heline Mirzakhanian; Barbara A Cornblatt; Ricardo E Carrión; Daniel H Mathalon; Thomas H McGlashan; Diana O Perkins; Aysenil Belger; Larry J Seidman; Heidi Thermenos; Ming T Tsuang; Theo G M van Erp; Elaine F Walker; Stephan Hamann; Alan Anticevic; Scott W Woods; Tyrone D Cannon
Journal:  Cereb Cortex       Date:  2019-03-01       Impact factor: 5.357

3.  Influence of sample size and analytic approach on stability and interpretation of brain-behavior correlations in task-related fMRI data.

Authors:  Cheryl L Grady; Jenny R Rieck; Daniel Nichol; Karen M Rodrigue; Kristen M Kennedy
Journal:  Hum Brain Mapp       Date:  2020-09-30       Impact factor: 5.038

  3 in total

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