Author

Koichi Ogawa

Shionogi (Japan)

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 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Assay:imaging· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Ayumu YamashitaiD· 2 shared Junichiro YoshimotoiD· 2 shared Mitsuo KawatoiD· 2 shared Okito YamashitaiD· 2 shared Tomoki TokudaiD· 2 shared Toshinori Yoshioka· 2 shared Yasumasa OkamotoiD· 2 shared Yuji TakaharaiD· 2 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersNeuroscience

Ayumu YamashitaORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Novel humanized anti-Nav1.7 antibodies with long-lasting, side-effect-free analgesic effects

Sosuke Yoneda, Daisuke Uta, Kana Yasufuku, Takuya Yamane, Saho Yoshioka, Keiko Takasu, Takaya Izumi, Sayaka Fujita, Daiki Nakamori, Shiori Kawasaki, Tatsuya Takahashi, Mai Yoshikawa, Koichi Ogawa, Erika Kasai

This study develops humanized anti-Nav1.7 antibodies that show long-lasting analgesic effects without side effects in neuropathic pain models.

bioRxiv · Aug 22, 2025 · PreprintPharmacology & Toxicology

Prediction of antidepressant treatment response with thalamo-somatomotor functional connectivity revealed by generalizable stratification of depressed patients

Yuto Kashiwagi, Tomoki Tokuda, Yuji Takahara, Yuki Sakai, Junichiro Yoshimoto, Ayumu Yamashita, Toshinori Yoshioka, Koichi Ogawa, Go Okada, Yasumasa Okamoto, Mitsuo Kawato, Okito Yamashita

This paper identifies a thalamo-somatomotor functional connectivity biomarker that stratifies MDD patients into subtypes with distinct antidepressant treatment responses, demonstrating generalizability across independent datasets.

bioRxiv · May 11, 2024 · PreprintNeuroscience

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets

Yuji Takahara, Yuto Kashiwagi, Tomoki Tokuda, Junichiro Yoshimoto, Yuki Sakai, Ayumu Yamashita, Toshinori Yoshioka, Hidehiko Takahashi, Hiroto Mizuta, Kiyoto Kasai, Akira Kunimitsu, Naohiro Okada, Eri Itai, Hotaka Shinzato, Satoshi Yokoyama, , Okito Yamashita

The paper evaluates rs-fMRI analysis pipelines for MDD biomarkers using multi-site datasets, finding optimal combinations of parcellation, connectivity estimation, harmonization, and machine learning methods.

bioRxiv · Mar 17, 2024 · PreprintNeuroscience