Yasumasa Okamoto - researchr alias

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Viewing Publication 1 - 9 from 9

2021

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback trainingTakashi 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, 245:118733, 2021. [doi]

2020

Maximum Credibility Voting (MCV) An Integrative Approach for Accurate Diagnosis of Major Depressive Disorder from Clinically Readily Available DataYu Shimizu, Junichiro Yoshimoto, Masahiro Takamura, Go Okada, Tomoya Matsumoto, Manabu Fuchikami, Satoshi Okada, Shigeru Morinobu, Yasumasa Okamoto, Shigeto Yamawaki, Kenji Doya. apsipa 2020: 1023-1032 [doi]

2015

Resting state functional connectivity explains individual scores of multiple clinical measures for major depressionKosuke Yoshida, Yu Shimizu, Junichiro Yoshimoto, Shigeru Toki, Go Okada, Masahiro Takamura, Yasumasa Okamoto, Shigeto Yamawaki, Kenji Doya. bibm 2015: 1078-1083 [doi]

2010

2007

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. NN, 20(2):285-286, 2007. [doi]

2006

2003

Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time ScalesSaori C. Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto, Shigeto Yamawaki. nips 2004: 701-708 [doi]

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