Siyuan Gao
Siyuan Gao
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
Task-induced brain state manipulation improves prediction of individual traits
AS Greene, S Gao, D Scheinost, RT Constable
Nature communications 9 (1), 2807, 2018
Braingnn: Interpretable brain graph neural network for fmri analysis
X Li, Y Zhou, N Dvornek, M Zhang, S Gao, J Zhuang, D Scheinost, ...
Medical Image Analysis 74, 102233, 2021
Ten simple rules for predictive modeling of individual differences in neuroimaging
D Scheinost, S Noble, C Horien, AS Greene, EMR Lake, M Salehi, S Gao, ...
Neuroimage 193, 35-45, 2019
Combining multiple connectomes improves predictive modeling of phenotypic measures
S Gao, AS Greene, RT Constable, D Scheinost
Neuroimage 201, 116038, 2019
Distributed patterns of functional connectivity predict working memory performance in novel healthy and memory-impaired individuals
EW Avery, K Yoo, MD Rosenberg, AS Greene, S Gao, DL Na, D Scheinost, ...
Journal of cognitive neuroscience 32 (2), 241-255, 2020
How tasks change whole-brain functional organization to reveal brain-phenotype relationships
AS Greene, S Gao, S Noble, D Scheinost, RT Constable
Cell reports 32 (8), 2020
A hitchhiker’s guide to working with large, open-source neuroimaging datasets
C Horien, S Noble, AS Greene, K Lee, DS Barron, S Gao, D O’Connor, ...
Nature human behaviour 5 (2), 185-193, 2021
Rclens: Interactive rare category exploration and identification
H Lin, S Gao, D Gotz, F Du, J He, N Cao
IEEE transactions on visualization and computer graphics 24 (7), 2223-2237, 2017
Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low‐dimensional space of brain dynamics
S Gao, G Mishne, D Scheinost
Human brain mapping 42 (14), 4510-4524, 2021
Transdiagnostic, connectome-based prediction of memory constructs across psychiatric disorders
DS Barron, S Gao, J Dadashkarimi, AS Greene, MN Spann, S Noble, ...
Cerebral Cortex 31 (5), 2523-2533, 2021
Adaptively exploring population mobility patterns in flow visualization
F Wang, W Chen, Y Zhao, T Gu, S Gao, H Bao
IEEE Transactions on Intelligent Transportation Systems 18 (8), 2250-2259, 2017
Brainhack: Developing a culture of open, inclusive, community-driven neuroscience
R Gau, S Noble, K Heuer, KL Bottenhorn, IP Bilgin, YF Yang, ...
Neuron 109 (11), 1769-1775, 2021
Large-scale differences in functional organization of left-and right-handed individuals using whole-brain, data-driven analysis of connectivity
L Tejavibulya, H Peterson, A Greene, S Gao, M Rolison, S Noble, ...
Neuroimage 252, 119040, 2022
Predicting the future of neuroimaging predictive models in mental health
L Tejavibulya, M Rolison, S Gao, Q Liang, H Peterson, J Dadashkarimi, ...
Molecular Psychiatry 27 (8), 3129-3137, 2022
Transdiagnostic connectome-based prediction of craving
KA Garrison, R Sinha, MN Potenza, S Gao, Q Liang, C Lacadie, ...
American Journal of Psychiatry, appi. ajp. 21121207, 2023
Smooth graph learning for functional connectivity estimation
S Gao, X Xia, D Scheinost, G Mishne
NeuroImage 239, 118289, 2021
Poincaré embedding reveals edge-based functional networks of the brain
S Gao, G Mishne, D Scheinost
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
The instability of functional connectomes across the first year of life
AJ Dufford, S Noble, S Gao, D Scheinost
Developmental cognitive neuroscience 51, 101007, 2021
Using functional connectivity models to characterize relationships between working and episodic memory
GF Stark, EW Avery, MD Rosenberg, AS Greene, S Gao, D Scheinost, ...
Brain and Behavior 11 (8), e02105, 2021
A mass multivariate edge-wise approach for combining multiple connectomes to improve the detection of group differences
J Dadashkarimi, S Gao, E Yeagle, S Noble, D Scheinost
Connectomics in NeuroImaging: Third International Workshop, CNI 2019, Held …, 2019
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Artikkelit 1–20