Brendan Adkinson
MD-PhD StudentAbout
Research
Publications
2026
External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging
Rosenblatt M, Foster M, Adkinson B, Tejavibulya L, Khaitova M, Ye J, Sun H, Rodriguez R, Camp C, Chinta A, McCusker M, Han L, Fields C, Mehta S, Scheinost D. External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging. Nature Methods 2026, 1-11. PMID: 42203860, DOI: 10.1038/s41592-026-03115-9.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsWhat effect sizes can we expect in functional neuroimaging?
Shearer H, Rosenblatt M, Ye J, Jiang R, Tejavibulya L, Foster M, Liang Q, Dadashkarimi J, Westwater M, Cheng I, Rolison M, Peterson H, Adkinson B, Mehta S, Camp C, Fischbach A, Cravo F, Meija A, Nichols T, Curtiss J, Scheinost D, Noble S. What effect sizes can we expect in functional neuroimaging? JoCN Forum 2026 DOI: 10.21428/8e6ba8ef.af9f794c.Peer-Reviewed Original ResearchOptimizing functional connectivity scanning conditions for predicting autistic traits
Horien C, Mandino F, Greene A, Shen X, Powell K, Vernetti A, O’Connor D, Adkinson B, Tejavibulya L, McPartland J, Volkmar F, Chun M, Chawarska K, Lake E, Rosenberg M, Satterthwaite T, Scheinost D, Finn E, Constable R. Optimizing functional connectivity scanning conditions for predicting autistic traits. Nature Mental Health 2026, 4: 792-805. PMID: 42137910, PMCID: PMC13167459, DOI: 10.1038/s44220-026-00623-7.Peer-Reviewed Original ResearchFeature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers
Adkinson B, Rosenblatt M, Sun H, Dadashkarimi J, Tejavibulya L, Horien C, Westwater M, Rodriguez R, Noble S, Scheinost D. Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers. Nature Human Behaviour 2026, 1-15. PMID: 41986741, DOI: 10.1038/s41562-026-02447-y.Peer-Reviewed Original Research
2025
BrainEffeX: A Web App for Exploring fMRI Effect Sizes
Shearer H, Rosenblatt M, Ye J, Jiang R, Tejavibulya L, Foster M, Liang Q, Dadashkarimi J, Westwater M, Cahill C, Cheng I, Fischbach A, Humphries A, Baskaran A, Rolison M, Peterson H, Adkinson B, Mehta S, Camp C, Nichols T, Curtiss J, Scheinost D, Noble S. BrainEffeX: A Web App for Exploring fMRI Effect Sizes. Aperture Neuro 2025, 5: 10.52294/001c.146251. PMID: 41675933, PMCID: PMC12889895, DOI: 10.52294/001c.146251.Peer-Reviewed Original ResearchTrends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals
Rosenblatt M, Mehta S, Peterson H, Dadashkarimi J, Rodriguez R, Foster M, Adkinson B, Liang Q, Kimble V, Ye J, McCusker M, Farruggia M, Rolison M, Westwater M, Jiang R, Noble S, Scheinost D. Trends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals. ELife 2025, 12 DOI: 10.7554/elife.88540.4.Peer-Reviewed Original ResearchMeta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces
Liang Q, Adkinson B, Scheinost D. Meta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10981255.Peer-Reviewed Original ResearchEditorial: Reward processing in motivational and affective disorders, volume II
Ryan F, Kumar P, Skandali N, Adkinson B. Editorial: Reward processing in motivational and affective disorders, volume II. Frontiers In Psychology 2025, 16: 1549667. PMID: 40313892, PMCID: PMC12043889, DOI: 10.3389/fpsyg.2025.1549667.Commentaries, Editorials and Letters
2024
Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations
Adkinson B, Rosenblatt M, Dadashkarimi J, Tejavibulya L, Jiang R, Noble S, Scheinost D. Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations. Developmental Cognitive Neuroscience 2024, 70: 101464. PMID: 39447452, PMCID: PMC11538622, DOI: 10.1016/j.dcn.2024.101464.Peer-Reviewed Original ResearchOvercoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling
Liang Q, Adkinson B, Jiang R, Scheinost D. Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling. Lecture Notes In Computer Science 2024, 15010: 579-588. DOI: 10.1007/978-3-031-72117-5_54.Chapters