Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development-Reference-Cited by-同舟云学术

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Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development

Published:2021-12 Issue:12 Volume:6 Page:1125-1134
ISSN:2451-9022
Container-title:Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
language:en
Short-container-title:Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

Author:

Morgan Sarah E.^ORCID,Young Jonathan,Patel Ameera X.,Whitaker Kirstie J.,Scarpazza Cristina^ORCID,van Amelsvoort Thérèse^ORCID,Marcelis Machteld,van Os Jim,Donohoe Gary,Mothersill David,Corvin Aiden,Arango Celso,Mechelli Andrea^ORCID,van den Heuvel Martijn,Kahn René S.,McGuire Philip,Brammer Michael,Bullmore Edward T.^ORCID

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Science Foundation Ireland

Aard- en Levenswetenschappen, Nederlandse Organisatie voor Wetenschappelijk Onderzoek

MQ: Transforming Mental Health

Alan Turing Institute

European Research Council

National Institute for Health Research

European Commission

Publisher

Elsevier BV

Subject

Biological Psychiatry,Neurology (clinical),Cognitive Neuroscience,Radiology, Nuclear Medicine and imaging

Reference49 articles.

1. Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls;Arbabshirani;Neuroimage,2017

2. Using machine learning and structural neuroimaging to detect first episode psychosis: Reconsidering the evidence;Vieira;Schizophr Bull,2019

3. Detecting schizophrenia at the level of the individual: Relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based metrics;Lei;Psychol Med,2020

4. Multi-center machine learning in imaging psychiatry: A meta-model approach;Dluhoš;Neuroimage,2017

5. Benchmarking functional connectome-based predictive models for resting-state fMRI;Dadi;Neuroimage,2019

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