Siyuan Gao
Title
Cited by
Cited by
Year
Task-induced brain state manipulation improves prediction of individual traits
AS Greene, S Gao, D Scheinost, RT Constable
Nature communications 9 (1), 1-13, 2018
1992018
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
1442019
Combining multiple connectomes improves predictive modeling of phenotypic measures
S Gao, AS Greene, RT Constable, D Scheinost
Neuroimage 201, 116038, 2019
512019
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
342020
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
332017
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
262017
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), 108066, 2020
202020
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
192021
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
92021
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
72021
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
62021
Task integration for connectome-based prediction via canonical correlation analysis
S Gao, AS Greene, RT Constable, D Scheinost
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 87-91, 2018
62018
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
International Workshop on Connectomics in Neuroimaging, 64-73, 2019
42019
A Hierarchical Manifold Learning Framework for High-Dimensional Neuroimaging Data
S Gao, G Mishne, D Scheinost
International Conference on Information Processing in Medical Imaging, 631-643, 2019
42019
Poincaré embedding reveals edge-based functional networks of the brain
S Gao, G Mishne, D Scheinost
International Conference on Medical Image Computing and Computer-Assisted …, 2020
32020
Combining multiple connectomes via canonical correlation analysis improves predictive models
S Gao, AS Greene, RT Constable, D Scheinost
International Conference on Medical Image Computing and Computer-Assisted …, 2018
32018
Low Infant Functional Connectome-based Identification Rates Across the First Year of Life
A Dufford, S Noble, S Gao, D Scheinost
bioRxiv, 2021
12021
Non-linear manifold learning in fMRI uncovers a low-dimensional space of brain dynamics
S Gao, G Mishne, D Scheinost
bioRxiv, 2020
12020
Task-Based Functional Connectomes Predict Cognitive Phenotypes Across Psychiatric Disease
DS Barron, S Gao, J Dadashkarimi, AS Greene, MN Spann, S Noble, ...
bioRxiv, 638825, 2019
12019
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
2021
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Articles 1–20