Connectomic disturbances underlying insomnia disorder and predictors of treatment response

Connectomic disturbances underlying insomnia disorder and predictors of treatment response

ObjectiveDespite its prevalence, insomnia disorder (ID) remains poorly understood. In this study, we used machine learning to analyze the functional connectivity (FC) disturbances underlying ID, and identify potential predictors of treatment response through recurrent transcranial magnetic stimulati...

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Bibliographic Details
Main Authors: Qian Lu, Wentong Zhang, Hailang Yan, Negar Mansouri, Onur Tanglay, Karol Osipowicz, Angus W. Joyce, Isabella M. Young, Xia Zhang, Stephane Doyen, Michael E. Sughrue, Chuan He
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Human Neuroscience
Subjects:
Insomnia
machine learning
functional connectivity
rTMS
treatment response
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2022.960350/full

Internet

https://www.frontiersin.org/articles/10.3389/fnhum.2022.960350/full

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