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A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity
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 predict...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324880/ https://www.ncbi.nlm.nih.gov/pubmed/30526859 http://dx.doi.org/10.7554/eLife.38844 |
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author | Yamashita, Masahiro Yoshihara, Yujiro Hashimoto, Ryuichiro Yahata, Noriaki Ichikawa, Naho Sakai, Yuki Yamada, Takashi Matsukawa, Noriko Okada, Go Tanaka, Saori C Kasai, Kiyoto Kato, Nobumasa Okamoto, Yasumasa Seymour, Ben Takahashi, Hidehiko Kawato, Mitsuo Imamizu, Hiroshi |
author_facet | Yamashita, Masahiro Yoshihara, Yujiro Hashimoto, Ryuichiro Yahata, Noriaki Ichikawa, Naho Sakai, Yuki Yamada, Takashi Matsukawa, Noriko Okada, Go Tanaka, Saori C Kasai, Kiyoto Kato, Nobumasa Okamoto, Yasumasa Seymour, Ben Takahashi, Hidehiko Kawato, Mitsuo Imamizu, Hiroshi |
author_sort | Yamashita, Masahiro |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6324880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-63248802019-01-10 A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity Yamashita, Masahiro Yoshihara, Yujiro Hashimoto, Ryuichiro Yahata, Noriaki Ichikawa, Naho Sakai, Yuki Yamada, Takashi Matsukawa, Noriko Okada, Go Tanaka, Saori C Kasai, Kiyoto Kato, Nobumasa Okamoto, Yasumasa Seymour, Ben Takahashi, Hidehiko Kawato, Mitsuo Imamizu, Hiroshi eLife Neuroscience 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. eLife Sciences Publications, Ltd 2018-12-10 /pmc/articles/PMC6324880/ /pubmed/30526859 http://dx.doi.org/10.7554/eLife.38844 Text en © 2018, Yamashita et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Yamashita, Masahiro Yoshihara, Yujiro Hashimoto, Ryuichiro Yahata, Noriaki Ichikawa, Naho Sakai, Yuki Yamada, Takashi Matsukawa, Noriko Okada, Go Tanaka, Saori C Kasai, Kiyoto Kato, Nobumasa Okamoto, Yasumasa Seymour, Ben Takahashi, Hidehiko Kawato, Mitsuo Imamizu, Hiroshi A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title | A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title_full | A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title_fullStr | A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title_full_unstemmed | A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title_short | A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
title_sort | prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324880/ https://www.ncbi.nlm.nih.gov/pubmed/30526859 http://dx.doi.org/10.7554/eLife.38844 |
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