Author

Rebecca S. Coalson

Washington University in St. Louis

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:human· 2 Assay:imaging· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

Ally Dworetsky· 3 shared Babatunde Adeyemo· 2 shared Benjamin A. SeitzmaniD· 2 shared Caterina GrattoniD· 2 shared Steven E. PeterseniD· 2 shared Abraham Z. SnyderiD· 1 shared Alana McMichaeliD· 1 shared Bradley L. SchlaggariD· 1 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersNeuroscience

Ally Dworetsky

Mutual co-authors in cluster

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3 papers

Recent·Most cited

NeuroscienceNeuroImagePeer-reviewedMay 15, 2021

Probabilistic mapping of human functional brain networks identifies regions of high group consensus

Ally Dworetsky, Benjamin A. Seitzman, Babatunde Adeyemo…·Caterina Gratton

The paper probabilistically maps human functional brain networks to identify regions of high inter-subject consensus across multiple datasets.

67 citationstop 2%

𝕏 PostBluesky

NeurosciencebioRxivPreprintApr 22, 2020

Cognitive Deficits and Altered Functional Brain Network Organization in Pediatric Brain Tumor Patients

Hari Anandarajah, Benjamin A. Seitzman, Alana McMichael…·Stephanie Mabry Perkins

This study examines functional brain network changes and cognitive impairments in pediatric brain tumor patients, finding altered network organization and its link to cognitive performance.

2 citations

𝕏 PostBluesky

NeuroscienceNeuroImagePeer-reviewedApr 20, 2020

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Caterina Gratton, Ally Dworetsky, Rebecca S. Coalson…·Meghan C. Campbell

This paper identifies and removes high-frequency motion artifacts in single-band fMRI data, improving motion estimates and reducing data loss without biasing functional connectivity.

99 citationstop 2%

statistical model

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