Dustin Scheinost
Affiliations: | 2013 | Biomedical Engineering | Yale University, New Haven, CT |
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| Ye J, Mehta S, Peterson H, et al. (2024) Investigating brain dynamics and their association with cognitive control in opioid use disorder using naturalistic and drug cue paradigms. Medrxiv : the Preprint Server For Health Sciences |
| Rosenblatt M, Tejavibulya L, Jiang R, et al. (2024) Data leakage inflates prediction performance in connectome-based machine learning models. Nature Communications. 15: 1829 |
| Adkinson BD, Rosenblatt M, Dadashkarimi J, et al. (2024) Brain-phenotype predictions can survive across diverse real-world data. Biorxiv : the Preprint Server For Biology |
| Rosenblatt M, Tejavibulya L, Jiang R, et al. (2023) The effects of data leakage on connectome-based machine learning models. Biorxiv : the Preprint Server For Biology |
| Weber CF, Lake EMR, Haider SP, et al. (2023) Autism spectrum disorder-specific changes in white matter connectome edge density based on functionally defined nodes. Frontiers in Neuroscience. 17: 1285396 |
| Rosenblatt M, Tejavibulya L, Camp CC, et al. (2023) Power and reproducibility in the external validation of brain-phenotype predictions. Biorxiv : the Preprint Server For Biology |
| Ye J, Garrison KA, Lacadie C, et al. (2023) Network state dynamics underpin craving in a transdiagnostic population. Medrxiv : the Preprint Server For Health Sciences |
| Camp CC, Noble S, Scheinost D, et al. (2023) Test-retest reliability of functional connectivity in depressed adolescents. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging |
| Sun H, Jiang R, Dai W, et al. (2023) Network controllability of structural connectomes in the neonatal brain. Nature Communications. 14: 5820 |
| Wu J, Li J, Eickhoff SB, et al. (2023) The challenges and prospects of brain-based prediction of behaviour. Nature Human Behaviour. 7: 1255-1264 |