Author

Kenichiro Harada

Yamaguchi 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· 4

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:imaging· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Koji MatsuoiD· 4 shared Ayumu YamashitaiD· 3 shared Go OkadaiD· 3 shared Hidehiko TakahashiiD· 3 shared Hiroshi ImamizuiD· 3 shared Hirotaka YamagataiD· 3 shared Kiyoto KasaiiD· 3 shared Mitsuo KawatoiD· 3 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersNeuroscience

Koji MatsuoORCID

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Author profile →

4 papers

Recent·Most cited

A Scalable Toolkit for Modeling 3D Surface-based Brain Geometry

Yanghee Im, Leila Nabulsi, Melody J.Y. Kang, Sophia I. Thomopoulos, Ana M. Díaz Zuluaga, Anders Martin Dale, Andriana Karuk, Annabella Di Giorgio, Benson Mwangi, Boris A. Gutman, Bronwyn J. Overs, Carlos López‐Jaramillo, Colm McDonald, Dan Joseph Stein, Dara M. Cannon, , for the ENIGMA Bipolar Disorder Working Group

The paper introduces a scalable toolkit for 3D surface-based brain analysis, demonstrating its utility in mapping subcortical shape variations across 21 international samples.

Lecture notes in computer science · Oct 4, 2025Peer-reviewedNeuroscience

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Ayumu Yamashita, Takashi Itahashi, Yuki Sakai, Masahiro Takamura, Hiroki Togo, Yujiro Yoshihara, Tomohisa Okada, Hirotaka Yamagata, Kenichiro Harada, Haruto Takagishi, Koichi Hosomi, Naohiro Okada, Osamu Abe, Go Okada, Yasumasa Okamoto, , Brain/MINDS Beyond Human Brain MRI Group

This study compares unsupervised feature selection with supervised methods to identify robust resting-state functional connectivity patterns associated with psychiatric disorders.

bioRxiv · Apr 14, 2025 · 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

Common brain networks between major depressive disorder and symptoms of depression that are validated for independent cohorts

Ayumu Yamashita, Yuki Sakai, Takashi Yamada, Noriaki Yahata, Akira Kunimatsu, Naohiro Okada, Takashi Itahashi, Ryuichiro Hashimoto, Hiroto Mizuta, Naho Ichikawa, Masahiro Takamura, Go Okada, Hirotaka Yamagata, Kenichiro Harada, Koji Matsuo, , Hiroshi Imamizu

The paper identifies common brain networks between major depressive disorder and depression symptoms that generalize across independent imaging sites.

Frontiers in Psychiatry · Jun 10, 2021Peer-reviewedNeuroscience