Author

M. Rmus

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· 4

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 3 Research Focus:synaptic & neural circuits· 2 Assay:behavioral assay· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Assay:imaging· 1

Frequent Co-Authors

A. G. E. Collins· 3 shared A. M. Bornstein· 1 shared A. R. Zou· 1 shared A. Shenhav· 1 shared B. Baribault· 1 shared E. G. Walsh· 1 shared E. K. Festa· 1 shared H. Ritz· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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3 shared papersAnimal Behavior & Cognition

A. G. E. Collins

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4 papers

Recent·Most cited

Artificial neural networks for model identification and parameter estimation in computational cognitive models

M. Rmus, T.-F. Pan, L. Xia, A. G. E. Collins

This paper uses artificial neural networks to estimate parameters and identify cognitive models without likelihood computation, demonstrating effectiveness for models with inter-trial dependencies.

bioRxiv · Sep 14, 2023Animal Behavior & Cognition

Age-related differences in prefrontal glutamate are associated with increased working memory decay that gives the appearance of learning deficits

M. Rmus, M. He, B. Baribault, E. G. Walsh, E. K. Festa, A. G. E. Collins, M. R. Nassar

This study links age-related prefrontal glutamate levels to working memory deficits and decision-making impairments in older adults.

bioRxiv · Nov 28, 2022Animal Behavior & Cognition

Plucking a string or playing a G? Choice type impacts human reinforcement learning

M. Rmus, A. R. Zou, A. G. E. Collins

This study shows that human reinforcement learning is slower and less accurate for general choice types compared to concrete motor actions, due to credit assignment interference and slower information integration.

bioRxiv · Aug 25, 2021 · PreprintAnimal Behavior & Cognition

Humans can navigate complex graph structures acquired during latent learning

M. Rmus, H. Ritz, L. E. Hunter, A. M. Bornstein, A. Shenhav

The paper shows humans can infer graph structures from disjoint experiences and link this ability to model-based reinforcement learning.

bioRxiv · Jul 9, 2021Animal Behavior & Cognition