Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization

Hengyi Cao (), Oliver Y. Chén, Yoonho Chung, Jennifer K. Forsyth, Sarah C. McEwen, Dylan G. Gee, Carrie E. Bearden, Jean Addington, Bradley Goodyear, Kristin S. Cadenhead, Heline Mirzakhanian, Barbara A. Cornblatt, Ricardo E. Carrión, Daniel H. Mathalon, Thomas H. McGlashan, Diana O. Perkins, Aysenil Belger, Larry J. Seidman, Heidi Thermenos, Ming T. Tsuang, Theo G. M. van Erp, Elaine F. Walker, Stephan Hamann, Alan Anticevic, Scott W. Woods and Tyrone D. Cannon ()
Additional contact information
Hengyi Cao: Yale University
Oliver Y. Chén: Yale University
Yoonho Chung: Yale University
Jennifer K. Forsyth: University of California Los Angeles
Sarah C. McEwen: University of California Los Angeles
Dylan G. Gee: Yale University
Carrie E. Bearden: University of California Los Angeles
Jean Addington: University of Calgary
Bradley Goodyear: University of Calgary
Kristin S. Cadenhead: University of California San Diego
Heline Mirzakhanian: University of California San Diego
Barbara A. Cornblatt: Zucker Hillside Hospital
Ricardo E. Carrión: Zucker Hillside Hospital
Daniel H. Mathalon: University of California San Francisco
Thomas H. McGlashan: Yale University
Diana O. Perkins: University of North Carolina
Aysenil Belger: University of North Carolina
Larry J. Seidman: Harvard Medical School
Heidi Thermenos: Harvard Medical School
Ming T. Tsuang: University of California San Diego
Theo G. M. van Erp: University of California Irvine
Elaine F. Walker: Emory University
Stephan Hamann: Emory University
Alan Anticevic: Yale University
Scott W. Woods: Yale University
Tyrone D. Cannon: Yale University

Nature Communications, 2018, vol. 9, issue 1, 1-9

Abstract: Abstract 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.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-018-06350-7 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06350-7

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-018-06350-7

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().