Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis-Reference-Cited by-同舟云学术

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Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis

Published:2020 Issue: Volume:27 Page:102284
ISSN:2213-1582
Container-title:NeuroImage: Clinical
language:en
Short-container-title:NeuroImage: Clinical

Author:

Du Yuhui,Hao Hui,Wang Shuhua,Pearlson Godfrey D,Calhoun Vince D.

Funder

National Natural Science Foundation of China

National Institutes of Health

National Science Foundation

Publisher

Elsevier BV

Subject

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

Reference88 articles.

1. Tracking whole-brain connectivity dynamics in the resting state;Allen;Cereb. Cortex,2014

2. Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder;Amann;Acta Psychiatr. Scand.,2016

3. Automatic Bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from FMRI data;Arribas;IEEE Trans. Biomed. Eng.,2010

4. Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain;Auer;Magn. Reson. Imaging,2008

5. An information-maximization approach to blind separation and blind deconvolution;Bell;Neural Comput.,1995

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