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Proceedings of the National Academy of Sciences of the United States of America|August 4, 2022
Improving power in functional magnetic resonance imaging by moving beyond cluster-level inferenceStephanie Noble, Amanda F Mejia, Andrew Zalesky, et al.Neuroimage|February 6, 2019
The individual functional connectome is unique and stable over months to yearsCorey Horien, Xilin Shen, Dustin Scheinost, et al.Nature Communications|July 20, 2018
Task-induced brain state manipulation improves prediction of individual traitsAbigail S Greene, Siyuan Gao, Dustin Scheinost, et al.Nature Communications|February 28, 2024
Data leakage inflates prediction performance in connectome-based machine learning modelsMatthew Rosenblatt, Link Tejavibulya, Rongtao Jiang, et al.Nature Neuroscience|November 3, 2025
Connectome caricatures remove large-amplitude coactivation patterns in resting-state fMRI to emphasize individual differencesRaimundo X Rodriguez, Stephanie Noble, Chris C Camp, et al.The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry|July 16, 2019
Regions and Connections: Complementary Approaches to Characterize Brain Organization and FunctionCorey Horien, Abigail S Greene, R Todd Constable, et al.Neuroimage|July 24, 2019
Combining multiple connectomes improves predictive modeling of phenotypic measuresSiyuan Gao, Abigail S Greene, R Todd Constable, et al.Neuroscience|April 12, 2016
Neural Correlates of Success and Failure Signals During Neurofeedback LearningJoaquim Radua, Teodora Stoica, Dustin Scheinost, et al.Biorxiv : the Preprint Server for Biology|January 18, 2024
The effects of data leakage on connectome-based machine learning modelsMatthew Rosenblatt, Link Tejavibulya, Rongtao Jiang, et al.Cerebral Cortex (New York, N.Y. : 1991)|August 23, 2021
Atypical Intrinsic Hemispheric Interaction Associated with Autism Spectrum Disorder Is Present within the First Year of LifeMax Rolison, Cheryl Lacadie, Katarzyna Chawarska, et al.Pageof 25