Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales. - Saori C. Tanaka; Kenji Doya; Go Okada; Kazutaka Ueda; Yasumasa Okamoto; Shigeto Yamawaki (NIPS, 2003)

Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics. - Saori C. Tanaka; Kazuyuki Samejima; Go Okada; Kazutaka Ueda; Yasumasa Okamoto; Shigeto Yamawaki; Kenji Doya (Neural Networks, 2006)

Humans Can Adopt Optimal Discounting Strategy under Real-Time Constraints. - Nicolas Schweighofer; K. Shishida; Cheol E. Han; Yasumasa Okamoto; Saori C. Tanaka; Shigeto Yamawaki; Kenji Doya (PLoS Comput. Biol., 2006)

Erratum to "Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics" [Neural Networks 19 (8) (2006) 1233-1241]. - Saori C. Tanaka; Kazuyuki Samejima; Go Okada; Kazutaka Ueda; Yasumasa Okamoto; Shigeto Yamawaki; Kenji Doya (Neural Networks, 2007)

Neural processing of negative word stimuli concerning body image in patients with eating disorders: An fMRI study. - Yoshie Miyake; Yasumasa Okamoto; Keiichi Onoda; Naoko Shirao; Yuri Okamoto; Yoko Otagaki; Shigeto Yamawaki (NeuroImage, 2010)

Sadness enhances the experience of pain via neural activation in the anterior cingulate cortex and amygdala: An fMRI study. - Atsuo Yoshino; Yasumasa Okamoto; Keiichi Onoda; Shinpei Yoshimura; Yoshihiko Kunisato; Yoshihiko Demoto; Go Okada; Shigeto Yamawaki (NeuroImage, 2010)

Resting state functional connectivity explains individual scores of multiple clinical measures for major depression. - Kosuke Yoshida; Yu Shimizu; Junichiro Yoshimoto; Shigeru Toki; Go Okada; Masahiro Takamura; Yasumasa Okamoto; Shigeto Yamawaki; Kenji Doya (BIBM, 2015)

Maximum Credibility Voting (MCV) An Integrative Approach for Accurate Diagnosis of Major Depressive Disorder from Clinically Readily Available Data. - Yu Shimizu; Junichiro Yoshimoto; Masahiro Takamura; Go Okada; Tomoya Matsumoto; Manabu Fuchikami; Satoshi Okada; Shigeru Morinobu; Yasumasa Okamoto; Shigeto Yamawaki; Kenji Doya (APSIPA, 2020)

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training. - Takashi Nakano; Masahiro Takamura; Haruki Nishimura; Maro G. Machizawa; Naho Ichikawa; Atsuo Yoshino; Go Okada; Yasumasa Okamoto; Shigeto Yamawaki; Makiko Yamada; Tetsuya Suhara; Junichiro Yoshimoto (NeuroImage, 2021)

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features. - Vladimir Belov; Tracy Erwin-Grabner; Ling-Li Zeng; Christopher R. K. Ching; André Aleman; Alyssa R. Amod; Zeynep Basgoze; Francesco Benedetti; Bianca Besteher; Katharina Brosch; Robin Bülow; Romain Colle; et al. (CoRR, 2023)

Comprehensive evaluation of pipelines for classification of psychiatric disorders 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; et al. (Neural Networks, 2025)