eLife (Dec 2018)

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

  • Masahiro Yamashita,
  • Yujiro Yoshihara,
  • Ryuichiro Hashimoto,
  • Noriaki Yahata,
  • Naho Ichikawa,
  • Yuki Sakai,
  • Takashi Yamada,
  • Noriko Matsukawa,
  • Go Okada,
  • Saori C Tanaka,
  • Kiyoto Kasai,
  • Nobumasa Kato,
  • Yasumasa Okamoto,
  • Ben Seymour,
  • Hidehiko Takahashi,
  • Mitsuo Kawato,
  • Hiroshi Imamizu

DOI
https://doi.org/10.7554/eLife.38844
Journal volume & issue
Vol. 7

Abstract

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Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual’s predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.

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