1. Neuroscience

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

  1. Masahiro Yamashita
  2. Yujiro Yoshihara
  3. Ryuichiro Hashimoto
  4. Noriaki Yahata
  5. Naho Ichikawa
  6. Yuki Sakai
  7. Takashi Yamada
  8. Noriko Matsukawa
  9. Go Okada
  10. Saori C Tanaka
  11. Kiyoto Kasai
  12. Nobumasa Kato
  13. Yasumasma Okamoto
  14. Ben Seymour  Is a corresponding author
  15. Hidehiko Takahashi  Is a corresponding author
  16. Mitsuo Kawato  Is a corresponding author
  17. Hiroshi Imamizu  Is a corresponding author
  1. Advanced Telecommunications Research Institute International, Japan
  2. Kyoto University Graduate School of Medicine, Japan
  3. Showa University, Japan
  4. The University of Tokyo, Japan
  5. Hiroshima University Graduate School of Biomedical and Health Sciences, Japan
  6. University of Cambridge, United Kingdom
https://doi.org/10.7554/eLife.38844
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Cite this article
  1. Masahiro Yamashita
  2. Yujiro Yoshihara
  3. Ryuichiro Hashimoto
  4. Noriaki Yahata
  5. Naho Ichikawa
  6. Yuki Sakai
  7. Takashi Yamada
  8. Noriko Matsukawa
  9. Go Okada
  10. Saori C Tanaka
  11. Kiyoto Kasai
  12. Nobumasa Kato
  13. Yasumasma Okamoto
  14. Ben Seymour
  15. Hidehiko Takahashi
  16. Mitsuo Kawato
  17. Hiroshi Imamizu
(2018)
A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity
eLife 7:e38844.
https://doi.org/10.7554/eLife.38844
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  1. Masahiro Yamashita
  2. Yujiro Yoshihara
  3. Ryuichiro Hashimoto
  4. Noriaki Yahata
  5. Naho Ichikawa
  6. Yuki Sakai
  7. Takashi Yamada
  8. Noriko Matsukawa
  9. Go Okada
  10. Saori C Tanaka
  11. Kiyoto Kasai
  12. Nobumasa Kato
  13. Yasumasma Okamoto
  14. Ben Seymour
  15. Hidehiko Takahashi
  16. Mitsuo Kawato
  17. Hiroshi Imamizu
(2018)
A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity
eLife 7:e38844.
https://doi.org/10.7554/eLife.38844

Share this article

https://doi.org/10.7554/eLife.38844