John Patrick Cunningham, Phd
Affiliations: | Electrical Engineering | Stanford University, Palo Alto, CA | |
| Columbia University, New York, NY |
Area:
Computation and Theory, Theoretical Neuroscience, Cognitive/Systems Neuroscience, statistical Machine Learning, Motor SystemsGoogle:
"John Cunningham"Mean distance: 14.7 (cluster 17) | S | N | B | C | P |
Cross-listing: Physics Tree
Parents
Sign in to add mentor| Krishna V. Shenoy | grad student | 2004-2009 | Stanford | |
| (Algorithms for understanding motor cortical processing and neural prosthetic systems.) | ||||
| Krishna V. Shenoy | post-doc | 2009-2009 | Stanford | |
Children
Sign in to add trainee| Estefany Kelly Buchanan | grad student | 2018- | Columbia |
| Scott W Linderman | post-doc | Columbia |
BETA: Related publications
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Publications
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| Zimnik AJ, Ames KC, An X, et al. (2024) Identifying Interpretable Latent Factors with Sparse Component Analysis. Biorxiv : the Preprint Server For Biology |
| Biderman D, Whiteway MR, Hurwitz C, et al. (2023) Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools. Biorxiv : the Preprint Server For Biology |
| Marshall NJ, Glaser JI, Trautmann EM, et al. (2022) Flexible neural control of motor units. Nature Neuroscience |
| Abe T, Kinsella I, Saxena S, et al. (2022) Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis. Neuron |
| Saxena S, Russo AA, Cunningham J, et al. (2022) Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity. Elife. 11 |
| Whiteway MR, Biderman D, Friedman Y, et al. (2021) Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. Plos Computational Biology. 17: e1009439 |
| Couto J, Musall S, Sun XR, et al. (2021) Chronic, cortex-wide imaging of specific cell populations during behavior. Nature Protocols |
| Kimmel DL, Elsayed GF, Cunningham JP, et al. (2020) Value and choice as separable and stable representations in orbitofrontal cortex. Nature Communications. 11: 3466 |
| Russo AA, Khajeh R, Bittner SR, et al. (2020) Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation. Neuron |
| Saxena S, Kinsella I, Musall S, et al. (2020) Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data. Plos Computational Biology. 16: e1007791 |