Author

Yosuke Ikejiri

Nagoya City 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· 2

Signature Assays, Organisms & Methods

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Organism:C. elegans· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Fumie HiramatsuiD· 2 shared Kosuke FujitaiD· 2 shared Koutarou D. KimuraiD· 2 shared Shuhei J. YamazakiiD· 2 shared Yuki TanimotoiD· 2 shared Akiko Yamazoe-Umemoto· 1 shared Akinori TakahashiiD· 1 shared Azusa KamikouchiiD· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersNeuroscience

Fumie HiramatsuORCID

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2 papers

Recent·Most cited

Neural mechanism of experience-dependent sensory gain control in C. elegans

Yosuke Ikejiri, Yuki Tanimoto, Kosuke Fujita, Fumie Hiramatsu, Shuhei J. Yamazaki, Yuto Endo, Yasushi Iwatani, Koichi Fujimoto, Koutarou D. Kimura

This study identifies how prior experience modulates sensory gain control in C. elegans ASH neurons, altering their response to odor concentration changes and enhancing odor avoidance behavior.

Neuroscience Research · Jan 19, 2023Peer-reviewedNeuroscience

A hybrid versatile method for state estimation and feature extraction from the trajectory of animal behavior

Shuhei J. Yamazaki, Kazuya Ohara, Kentaro Ito, Nobuo Kokubun, Takuma Kitanishi, Daisuke Takaichi, Yasufumi Yamada, Yosuke Ikejiri, Fumie Hiramatsu, Kosuke Fujita, Yuki Tanimoto, Akiko Yamazoe-Umemoto, Koichi Hashimoto, Katsufumi Sato, Ken Yoda, , Koutarou D. Kimura

This paper introduces a hybrid machine learning method to estimate behavioral states and extract features from low-content animal trajectory data, validated across diverse species and environments.

Frontiers in Neuroscience · Jun 28, 2019Peer-reviewedNeuroscience