Literature DB >> 25275678

Internetwork dynamic connectivity effectively differentiates schizophrenic patients from healthy controls.

Hui Shen1, Zhenfeng Li, Ling-Li Zeng, Lin Yuan, Fanglin Chen, Zhening Liu, Dewen Hu.   

Abstract

Increasingly more neuroimaging studies have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and dysconnectivity of intrinsic connectivity networks. Previous studies have assumed temporal stationarity of resting-state functional connectivity, whereas temporal dynamics have rarely been explored. Here, we utilized resting-state functional MRI with a sliding window approach to measure the amplitude of low-frequency fluctuations (ALFFs) in functional connectivity in 24 patients with schizophrenia and 25 healthy controls. We found that there were significant differences in the ALFFs of specific connections, the majority of which were located between the intrinsic connectivity networks. Importantly, the experimental results of a multivariate pattern analysis of these ALFF measures showed that 81.3% (P<0.0009) of the participants were correctly classified as either schizophrenic patients or healthy controls by leave-one-out cross-validation. Our results show significant abnormality in the dynamics of internetwork functional connectivity in schizophrenia, which contributes toward the characterization and differentiation of schizophrenic patients, and may be used as a potential biomarker.

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Year:  2014        PMID: 25275678     DOI: 10.1097/WNR.0000000000000267

Source DB:  PubMed          Journal:  Neuroreport        ISSN: 0959-4965            Impact factor:   1.837


  14 in total

1.  Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

Authors:  Gal Raz; Lavi Shpigelman; Yael Jacob; Tal Gonen; Yoav Benjamini; Talma Hendler
Journal:  Hum Brain Mapp       Date:  2016-08-01       Impact factor: 5.038

2.  Altered time-varying local spontaneous brain activity pattern in patients with high myopia: a dynamic amplitude of low-frequency fluctuations study.

Authors:  Xiaopan Zhang; Liang Liu; Xuemin Jin; Shaoqiang Han; Fan Yang; Yinhuan Xu; Bingqian Zhou; Jingli Chen; Yong Zhang; Baohong Wen; Jingliang Cheng
Journal:  Neuroradiology       Date:  2022-08-12       Impact factor: 2.995

Review 3.  Neural and metabolic basis of dynamic resting state fMRI.

Authors:  Garth J Thompson
Journal:  Neuroimage       Date:  2017-09-09       Impact factor: 6.556

4.  Abnormalities of intrinsic regional brain activity in first-episode and chronic schizophrenia: a meta-analysis of resting-state functional MRI

Authors:  Jiaying Gong; Junjing Wang; Xiaomei Luo; Guanmao Chen; Huiyuan Huang; Ruiwang Huang; Li Huang; Ying Wang
Journal:  J Psychiatry Neurosci       Date:  2020-01-01       Impact factor: 6.186

Review 5.  Functional Magnetic Resonance Imaging Methods.

Authors:  Jingyuan E Chen; Gary H Glover
Journal:  Neuropsychol Rev       Date:  2015-08-07       Impact factor: 7.444

Review 6.  Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data.

Authors:  Jingyuan E Chen; Mikail Rubinov; Catie Chang
Journal:  Neuroimaging Clin N Am       Date:  2017-09-01       Impact factor: 2.264

7.  The intensity and connectivity of spontaneous brain activity in a language network relate to aging and language.

Authors:  Haoyun Zhang; Xiaoxiao Bai; Michele T Diaz
Journal:  Neuropsychologia       Date:  2021-02-08       Impact factor: 3.139

8.  The default mode network as a biomarker for monitoring the therapeutic effects of meditation.

Authors:  Rozalyn Simon; Maria Engström
Journal:  Front Psychol       Date:  2015-06-09

9.  Towards a brain-based predictome of mental illness.

Authors:  Barnaly Rashid; Vince Calhoun
Journal:  Hum Brain Mapp       Date:  2020-05-06       Impact factor: 5.038

10.  Predicting individual brain maturity using dynamic functional connectivity.

Authors:  Jian Qin; Shan-Guang Chen; Dewen Hu; Ling-Li Zeng; Yi-Ming Fan; Xiao-Ping Chen; Hui Shen
Journal:  Front Hum Neurosci       Date:  2015-07-16       Impact factor: 3.169

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