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Kimberly L. Ray
Researcher at University of Texas at Austin
Publications - 34
Citations - 3681
Kimberly L. Ray is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Cognition & Default mode network. The author has an hindex of 16, co-authored 33 publications receiving 3042 citations. Previous affiliations of Kimberly L. Ray include University of Texas Health Science Center at San Antonio & University of California, Davis.
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Journal ArticleDOI
Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions
Tara A. Niendam,Angela R. Laird,Kimberly L. Ray,Y. Monica Dean,David C. Glahn,Cameron S. Carter +5 more
TL;DR: In this article, a common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network.
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Behavioral interpretations of intrinsic connectivity networks
Angela R. Laird,P. Mickle Fox,Simon B. Eickhoff,Jessica A. Turner,Kimberly L. Ray,D. Reese McKay,David C. Glahn,Christian F. Beckmann,Stephen M. Smith,Peter T. Fox +9 more
TL;DR: This work presents a full functional explication of intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes.
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Comparison of the disparity between Talairach and MNI coordinates in functional neuroimaging data: Validation of the Lancaster transform
Angela R. Laird,Jennifer L. Robinson,Kathryn M. McMillan,Diana Tordesillas-Gutiérrez,Sarah T. Moran,Sabina M. Gonzales,Kimberly L. Ray,Crystal Franklin,David C. Glahn,Peter T. Fox,Jack L. Lancaster +10 more
TL;DR: The Lancaster transform should be adopted as the community standard for reducing disparity between results reported as MNI or Talairach coordinates, and it is suggested that future spatial normalization strategies be designed to minimize this variability in the literature.
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The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data
Angela R. Laird,Simon B. Eickhoff,Simon B. Eickhoff,P. Mickle Fox,Angela M. Uecker,Kimberly L. Ray,Juan J Saenz,Juan J Saenz,D. Reese McKay,Danilo Bzdok,Danilo Bzdok,Robert W. Laird,Jennifer L. Robinson,Jennifer L. Robinson,Jessica A. Turner,Peter E. Turkeltaub,Jack L. Lancaster,Peter T. Fox +17 more
TL;DR: The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities.
Journal ArticleDOI
ICA model order selection of task co-activation networks.
Kimberly L. Ray,D. Reese McKay,Peter Fox,Michael C. Riedel,Angela M. Uecker,Christian F. Beckmann,Stephen M. Smith,Peter T. Fox,Peter T. Fox,Angela R. Laird +9 more
TL;DR: This study investigates the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components and suggests dimensionality of 20 for low model order ICA to examine large-scale brain networks.