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DOI | 10.1038/s41467-018-07217-7 |
Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization | |
Cao, Hengyi1; Chen, Oliver Y.1; Chung, Yoonho1; Forsyth, Jennifer K.2; McEwen, Sarah C.3; Gee, Dylan G.1; Bearden, Carrie E.3; Addington, Jean4; Goodyear, Bradley4,5,6; Cadenhead, Kristin S.7; Mirzakhanian, Heline7; Cornblatt, Barbara A.8; Carrion, Ricardo E.8; Mathalon, Daniel H.9; McGlashan, Thomas H.10; Perkins, Diana O.11; Belger, Aysenil11; Seidman, Larry J.12; Thermenos, Heidi12; Tsuang, Ming T.7; van Erp, Theo G. M.13; Walker, Elaine F.14; Hamann, Stephan14; Anticevic, Alan10; Woods, Scott W.10; Cannon, Tyrone D.1,10 | |
2018-09-21 | |
发表期刊 | NATURE COMMUNICATIONS
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ISSN | 2041-1723 |
出版年 | 2018 |
卷号 | 9 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Canada |
英文摘要 | Understanding the fundamental alterations in brain functioning that lead to psychotic disorders remains a major challenge in clinical neuroscience. In particular, it is unknown whether any state-independent biomarkers can potentially predict the onset of psychosis and distinguish patients from healthy controls, regardless of paradigm. Here, using multi-paradigm fMRI data from the North American Prodrome Longitudinal Study consortium, we show that individuals at clinical high risk for psychosis display an intrinsic "trait-like" abnormality in brain architecture characterized as increased connectivity in the cerebello-thalamo-cortical circuitry, a pattern that is significantly more pronounced among converters compared with non-converters. This alteration is significantly correlated with disorganization symptoms and predictive of time to conversion to psychosis. Moreover, using an independent clinical sample, we demonstrate that this hyperconnectivity pattern is reliably detected and specifically present in patients with schizophrenia. These findings implicate cerebello-thalamo-cortical hyperconnectivity as a robust state-independent neural signature for psychosis prediction and characterization. |
领域 | 资源环境 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000445269100001 |
WOS关键词 | ULTRA-HIGH-RISK ; DEFAULT-MODE NETWORK ; POSITRON-EMISSION-TOMOGRAPHY ; ELEVATED CLINICAL RISK ; COGNITIVE DYSMETRIA ; NMDA RECEPTOR ; MENTAL STATE ; HUMAN BRAIN ; SCHIZOPHRENIA ; CONNECTIVITY |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/204075 |
专题 | 资源环境科学 |
作者单位 | 1.Yale Univ, Dept Psychol, New Haven, CT 06511 USA; 2.Univ Calif Los Angeles, Dept Psychol, Los Angeles, CA 90095 USA; 3.Univ Calif Los Angeles, Dept Psychiat & Biobehav Sci, Los Angeles, CA 90095 USA; 4.Univ Calgary, Dept Psychiat, Calgary, AB T2N 1N4, Canada; 5.Univ Calgary, Dept Radiol, Calgary, AB T2N 1N4, Canada; 6.Univ Calgary, Dept Clin Neurosci, Calgary, AB T2N 1N4, Canada; 7.Univ Calif San Diego, Dept Psychiat, San Diego, CA 92093 USA; 8.Zucker Hillside Hosp, Dept Psychiat Res, Glen Oaks, NY 11004 USA; 9.Univ Calif San Francisco, Dept Psychiat, San Francisco, CA 94143 USA; 10.Yale Univ, Dept Psychiat, New Haven, CT 06510 USA; 11.Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27599 USA; 12.Harvard Med Sch, Beth Israel Deaconess Med Ctr, Dept Psychiat, Boston, MA 02115 USA; 13.Univ Calif Irvine, Dept Psychiat & Human Behav, Irvine, CA 92697 USA; 14.Emory Univ, Dept Psychol, Atlanta, GA 30322 USA |
推荐引用方式 GB/T 7714 | Cao, Hengyi,Chen, Oliver Y.,Chung, Yoonho,et al. Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization[J]. NATURE COMMUNICATIONS,2018,9. |
APA | Cao, Hengyi.,Chen, Oliver Y..,Chung, Yoonho.,Forsyth, Jennifer K..,McEwen, Sarah C..,...&Cannon, Tyrone D..(2018).Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization.NATURE COMMUNICATIONS,9. |
MLA | Cao, Hengyi,et al."Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization".NATURE COMMUNICATIONS 9(2018). |
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