Author

Brian C. Caffo

Johns Hopkins University

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· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Bonnie B. SmithiD· 1 shared Cameron CraddockiD· 1 shared Carey E. PriebeiD· 1 shared Carlo ColantuoniiD· 1 shared Christopher Blair DouvilleiD· 1 shared Eric BridgefordiD· 1 shared Gregory KiariD· 1 shared Jayanta K. DeyiD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Bonnie B. SmithORCID

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2 papers

Recent·Most cited

Regression models for partially localized fMRI connectivity analyses

Bonnie B. Smith, Yi Zhao, Martin A. Lindquist, Brian C. Caffo

This paper introduces regression models for fMRI connectivity analysis that account for covariates like network labels and regional characteristics, showing they explain more variation than geographic or homotopic distances.

Frontiers in Neuroimaging · Nov 13, 2023Peer-reviewedNeuroscience

Eliminating accidental deviations to minimize generalization error and maximize replicability: applications in connectomics and genomics

Eric Bridgeford, Shangsi Wang, Zhi Yang, Zeyi Wang, Ting Xu, Cameron Craddock, Jayanta K. Dey, Gregory Kiar, William Gray-Roncal, Carlo Colantuoni, Christopher Blair Douville, Stephanie Noble, Carey E. Priebe, Brian C. Caffo, Michael Peter Milham, , Joshua T Vogelstein

This paper introduces a new statistic called discriminability to improve replicability by distinguishing accidental from systematic deviations in data, showing its effectiveness in both simulated and real datasets.

bioRxiv · Jul 24, 2021 · PreprintNeuroscience