Author

Tyler Benster

Stanford University

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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Neuroscience· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:electronic health records· 2 Organism:mouse· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Karl A. DeisserothiD· 2 shared Aaron S. Andalman· 1 shared Andrea GiovannucciiD· 1 shared Anne DraelosiD· 1 shared Chaichontat SriworaratiD· 1 shared Charlotte ArltiD· 1 shared Christopher D. HarveyiD· 1 shared Clayton P. MosheriD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersNeuroscience

Karl A. DeisserothORCID

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3 papers

Recent·Most cited

Inferring brain-wide interactions using data-constrained recurrent neural network models

Matthew G. Perich, Charlotte Arlt, Sofia Soares, Siyan Zhou, Manuel Beirán, Aaron S. Andalman, Tyler Benster, Megan E. Young, Clayton P. Mosher, Juri Minxha, Eugene Carter, Ueli Rutishauser, Peter H. Rudebeck, Christopher D. Harvey, Karl A. Deisseroth, Kanaka Rajan

This paper introduces CURBD, a method using data-constrained recurrent neural networks to infer brain-wide interactions from neural recordings across species.

Neuron · Aug 1, 2026Peer-reviewedNeuroscience

Reconstruction of visual images from mouse retinal ganglion cell spiking activity using convolutional neural networks

Tyler Benster, Darwin Babino, John Thickstun, Matthew Hunt, Xiyang Liu, Zaïd Harchaoui, Sewoong Oh, Russell Neil Van Gelder

This paper trains convolutional neural networks on retinal ganglion cell firing data to reconstruct images, showing that subpopulations and ON-OFF cells contribute to image reconstruction.

bioRxiv · Jun 10, 2022 · PreprintNeuroscience

improv: A software platform for real-time and adaptive neuroscience experiments

Anne Draelos, Matthew D. Loring, Maxim Nikitchenko, Chaichontat Sriworarat, Pranjal Gupta, Daniel Sprague, Eftychios A. Pnevmatikakis, Andrea Giovannucci, Tyler Benster, Karl A. Deisseroth, John M. Pearson, Eva A. Naumann

improv enables real-time adaptive neuroscience experiments by integrating modeling, data collection, and analysis across organisms and data types.

bioRxiv · Feb 22, 2021 · PreprintNeuroscience