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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Bibliografiska uppgifter

Huvudupphov:	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
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Frontiers Media S.A. 2022-08-01
Serie:	Frontiers in Human Neuroscience
Ämnen:	Insomnia machine learning functional connectivity rTMS treatment response
Länkar:	https://www.frontiersin.org/articles/10.3389/fnhum.2022.960350/full
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