Author

Mikito Ogino

The University of TokyoORCID 0000-0003-1089-4469Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:electronic health records· 1 Organism:human· 1 Research Focus:perturbation response prediction· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Daiki SekizawaiD· 2 shared Masafumi OizumiiD· 2 shared Jun KitazonoiD· 1 shared Raku Miyoshi· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 5 mutual co-author links

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2 shared papersNeuroscience

Daiki SekizawaORCID

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2 papers

Recent·Most cited

NeuroscienceeLifePeer-reviewedOct 13, 2026

Designing optimal perturbation inputs for system identification in neuroscience

Mikito Ogino, Daiki Sekizawa, Jun Kitazono, Masafumi Oizumi

This paper proposes a data-driven framework for optimally designing perturbation inputs to improve neural system identification and control.

1 citation

statistical modelperturbation response prediction

𝕏 PostBluesky

NeurosciencebioRxivPreprintOct 13, 2026

Recovering Hidden Neural Oscillatory Modes from Partial Observations through Delay Embedding and Perturbation

Raku Miyoshi, Mikito Ogino, Daiki Sekizawa, Masafumi Oizumi

This paper improves recovery of neural oscillatory modes from partial recordings using delay embedding and perturbation, showing increased mode estimates with deeper delay and perturbation.

DOI 10.64898/2026.10.05.756919

humanelectronic health records

𝕏 PostBluesky