Literature DB >> 25570258

Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.

Yuhui Du, Jingyu Liu, Jing Sui, Hao He, Godfrey D Pearlson, Vince D Calhoun.   

Abstract

Schizophrenia, schizoaffective and bipolar disorders share some common symptoms. However, the biomarkers underlying those disorders remain unclear. In fact, there is still controversy about the schizoaffective disorder with respect to its validity of independent category and its relationship with schizophrenia and bipolar disorders. In this paper, based on brain functional networks extracted from resting-state fMRI using a recently proposed group information guided ICA (GIG-ICA) method, we explore the biomarkers for discriminating healthy controls, schizophrenia patients, bipolar patients, and patients with two symptom defined subsets of schizoaffective disorder, and then investigate the relationship between different groups. The results demonstrate that the discriminating regions mainly including frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insular and supramarginal cortices perform well in distinguishing the different diagnostic groups. The results also suggest that schizoaffective disorder may be an independent disorder, although its subtype characterized by depressive episodes shares more similarity with schizophrenia.

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Year:  2014        PMID: 25570258     DOI: 10.1109/EMBC.2014.6943890

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  14 in total

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Journal:  Psychiatr Q       Date:  2016-12

4.  A novel 5D brain parcellation approach based on spatio-temporal encoding of resting fMRI data from deep residual learning.

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Journal:  J Neurosci Methods       Date:  2022-01-11       Impact factor: 2.987

5.  A Perspective on a Possible Relation Between the Psychopathology of the Schizophrenia/Schizoaffective Spectrum and Unconjugated Bilirubin: A Longitudinal Protocol Study.

Authors:  João Gama Marques; Filipe Arantes-Gonçalves
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6.  Identifying dynamic functional connectivity biomarkers using GIG-ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder.

Authors:  Yuhui Du; Godfrey D Pearlson; Dongdong Lin; Jing Sui; Jiayu Chen; Mustafa Salman; Carol A Tamminga; Elena I Ivleva; John A Sweeney; Matcheri S Keshavan; Brett A Clementz; Juan Bustillo; Vince D Calhoun
Journal:  Hum Brain Mapp       Date:  2017-03-10       Impact factor: 5.038

7.  Artifact removal in the context of group ICA: A comparison of single-subject and group approaches.

Authors:  Yuhui Du; Elena A Allen; Hao He; Jing Sui; Lei Wu; Vince D Calhoun
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Review 8.  The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.

Authors:  Vince D Calhoun; Robyn Miller; Godfrey Pearlson; Tulay Adalı
Journal:  Neuron       Date:  2014-10-22       Impact factor: 17.173

9.  Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

Authors:  Biao Cai; Pascal Zille; Julia M Stephen; Tony W Wilson; Vince D Calhoun; Yu Ping Wang
Journal:  IEEE Trans Med Imaging       Date:  2018-05       Impact factor: 10.048

10.  A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders.

Authors:  Yuhui Du; Godfrey D Pearlson; Jingyu Liu; Jing Sui; Qingbao Yu; Hao He; Eduardo Castro; Vince D Calhoun
Journal:  Neuroimage       Date:  2015-07-26       Impact factor: 6.556

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