Author

H. Maeda

Institute for Quantitative Biosciences, The University of TokyoORCID 0000-0002-8546-6250Unclaimed ORCID profile · follow to get notified of new preprints

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H. Maeda4 papers

Biology Disciplines

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Neuroscience· 2

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Organism:mouse· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:statistical model· 1

Frequent Co-Authors

Akihiro FunamizuiD· 2 shared Shuo WangiD· 1 shared Shuo WangiD· 1 shared Yutaro UeokaiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

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4 top collaborators · 4 mutual co-author links

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2 shared papersNeuroscience

Akihiro FunamizuORCID

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2 papers

Recent·Most cited

Dual reinforcement-learning network modules for modeling decision-making with multiple strategies

H. Maeda, Shuo Wang, Akihiro Funamizu

This paper introduces a hybrid deep reinforcement learning method to model decision-making with multiple strategies, showing it can replicate human behavior in a two-step task.

bioRxiv · Mar 10, 2026 · PreprintNeuroscience

Real-cyber hybrid neural network for predicting neural circuits in mouse decision-making

Yutaro Ueoka, H. Maeda, Shuo Wang, Akihiro Funamizu

The paper develops a real-cyber hybrid neural network to predict mouse decision-making movements by incorporating real neuronal activity and generated activity, outperforming traditional ANNs.

bioRxiv · Oct 15, 2024 · PreprintNeuroscience