Author

J. P. Cunningham

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Animal Behavior & Cognition· 1 Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:deconvolution· 1 Research Focus:dimensionality reduction· 1 Research Focus:drug response / drug discovery· 1 Assay:electrophysiology· 1

Frequent Co-Authors

A. Norovich· 1 shared A. Wu· 1 shared C. D. Salzman· 1 shared C. Everett· 1 shared D. E. Angelaki· 1 shared E. A. Amematsro· 1 shared E. K. Buchanan· 1 shared E. Rodriguez· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperAnimal Behavior & Cognition

A. Norovich

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2 papers

Recent·Most cited

An emerging view of neural geometry in motor cortex supports high-performance decoding

S. M. Perkins, E. A. Amematsro, J. P. Cunningham, Q. Wang, M. M. Churchland

This paper introduces MINT, a decoder for brain-computer interfaces that uses statistical constraints, outperforming interpretable methods and competing with machine learning approaches in multiple tasks.

bioRxiv · Apr 5, 2023Bioengineering

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking

A. Wu, E. K. Buchanan, M. R. Whiteway, M. Schartner, G. T. Meijer, J.-P. Noel, E. Rodriguez, C. Everett, A. Norovich, E. S. Schaffer, N. Mishra, C. D. Salzman, D. E. Angelaki, T. International Brain Laboratory, J. P. Cunningham, L. Paninski

This paper introduces a semi-supervised deep graphical model for animal pose tracking that improves accuracy by leveraging spatial and temporal constraints in behavioral videos.

bioRxiv · Aug 20, 2020 · PreprintAnimal Behavior & Cognition