Author

Matt Deible

University of PittsburghORCID 0000-0001-7494-4555Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Daniel HaşeganiD· 2 shared David D’OnofrioiD· 2 shared Hananel HazaniD· 2 shared Haroon AnwariD· 2 shared Samuel A. NeymotiniD· 2 shared Christopher Earl· 1 shared Cliff C. KerriD· 1 shared George L. ChadderdoniD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersNeuroscience

Daniel HaşeganORCID

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2 papers

Recent·Most cited

NeurosciencePLoS ONEPeer-reviewedMay 11, 2022

Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning

Haroon Anwar, Simon Caby, Salvador Durá-Bernal…·Samuel A. Neymotin

This paper trains spiking neuronal network models to play a virtual racket-ball game using reinforcement learning and evaluates different circuit architectures and learning rules.

15 citations

statistical modelexperimental assay

𝕏 PostBluesky

NeurosciencebioRxivPreprintNov 20, 2021

Evolutionary and spike-timing-dependent reinforcement learning train spiking neuronal network motor control

Daniel Haşegan, Matt Deible, Christopher Earl…·Samuel A. Neymotin

This study compares spike-timing-dependent reinforcement learning and evolutionary strategy for training spiking neuronal networks to solve a reinforcement learning control task.

4 citations

statistical modelmachine learning (classical)

𝕏 PostBluesky