Literature DB >> 33510782

Brain Networks Connectivity in Mild to Moderate Depression: Resting State fMRI Study with Implications to Nonpharmacological Treatment.

Dmitry D Bezmaternykh1, Mikhail Ye Melnikov1, Andrey A Savelov2, Lyudmila I Kozlova1, Evgeniy D Petrovskiy2, Kira A Natarova3, Mark B Shtark1.   

Abstract

Network mechanisms of depression development and especially of improvement from nonpharmacological treatment remain understudied. The current study is aimed at examining brain networks functional connectivity in depressed patients and its dynamics in nonpharmacological treatment. Resting state fMRI data of 21 healthy adults and 51 patients with mild or moderate depression were analyzed with spatial independent component analysis; then, correlations between time series of the components were calculated and compared between-group (study 1). Baseline and repeated-measure data of 14 treated (psychotherapy or fMRI neurofeedback) and 15 untreated depressed participants were similarly analyzed and correlated with changes in depression scores (study 2). Aside from diverse findings, studies 1 and 2 both revealed changes in within-default mode network (DMN) and DMN to executive control network (ECN) connections. Connectivity in one pair, initially lower in depression, decreased in no treatment group and was inversely correlated with Montgomery-Asberg depression score change in treatment group. Weak baseline connectivity in this pair also predicted improvement on Montgomery-Asberg scale in both treatment and no treatment groups. Coupling of another pair, initially stronger in depression, increased in therapy though was unrelated to improvement. The results demonstrate possible role of within-DMN and DMN-ECN functional connectivity in depression treatment and suggest that neural mechanisms of nonpharmacological treatment action may be unrelated to normalization of initially disrupted connectivity.
Copyright © 2021 Dmitry D. Bezmaternykh et al.

Entities:  

Year:  2021        PMID: 33510782      PMCID: PMC7822653          DOI: 10.1155/2021/8846097

Source DB:  PubMed          Journal:  Neural Plast        ISSN: 1687-5443            Impact factor:   3.599


  56 in total

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Authors:  Yu Chen; Chun Wang; Xueling Zhu; Yarong Tan; Yuan Zhong
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2.  Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder.

Authors:  Allison C Nugent; Stephen E Robinson; Richard Coppola; Maura L Furey; Carlos A Zarate
Journal:  Neuroimage       Date:  2015-05-30       Impact factor: 6.556

3.  Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus.

Authors:  Michael D Greicius; Benjamin H Flores; Vinod Menon; Gary H Glover; Hugh B Solvason; Heather Kenna; Allan L Reiss; Alan F Schatzberg
Journal:  Biol Psychiatry       Date:  2007-01-08       Impact factor: 13.382

4.  Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

Authors:  Matthew D Sacchet; Tiffany C Ho; Colm G Connolly; Olga Tymofiyeva; Kaja Z Lewinn; Laura Km Han; Eva H Blom; Susan F Tapert; Jeffrey E Max; Guido Kw Frank; Martin P Paulus; Alan N Simmons; Ian H Gotlib; Tony T Yang
Journal:  Neuropsychopharmacology       Date:  2016-05-26       Impact factor: 7.853

5.  Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

Authors:  Ilya M Veer; Christian F Beckmann; Marie-José van Tol; Luca Ferrarini; Julien Milles; Dick J Veltman; André Aleman; Mark A van Buchem; Nic J van der Wee; Serge A R B Rombouts
Journal:  Front Syst Neurosci       Date:  2010-09-20

6.  The effects of serotonin modulation on medial prefrontal connectivity strength and stability: A pharmacological fMRI study with citalopram.

Authors:  D Arnone; T Wise; C Walker; P J Cowen; O Howes; S Selvaraj
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2018-02-01       Impact factor: 5.067

7.  Meta-analytically informed network analysis of resting state FMRI reveals hyperconnectivity in an introspective socio-affective network in depression.

Authors:  Leonhard Schilbach; Veronika I Müller; Felix Hoffstaedter; Mareike Clos; Roberto Goya-Maldonado; Oliver Gruber; Simon B Eickhoff
Journal:  PLoS One       Date:  2014-04-23       Impact factor: 3.240

Review 8.  Frontal EEG Asymmetry of Mood: A Mini-Review.

Authors:  Massimiliano Palmiero; Laura Piccardi
Journal:  Front Behav Neurosci       Date:  2017-11-06       Impact factor: 3.558

9.  Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

Authors:  Yicheng Long; Hengyi Cao; Chaogan Yan; Xiao Chen; Le Li; Francisco Xavier Castellanos; Tongjian Bai; Qijing Bo; Guanmao Chen; Ningxuan Chen; Wei Chen; Chang Cheng; Yuqi Cheng; Xilong Cui; Jia Duan; Yiru Fang; Qiyong Gong; Wenbin Guo; Zhenghua Hou; Lan Hu; Li Kuang; Feng Li; Kaiming Li; Tao Li; Yansong Liu; Qinghua Luo; Huaqing Meng; Daihui Peng; Haitang Qiu; Jiang Qiu; Yuedi Shen; Yushu Shi; Tianmei Si; Chuanyue Wang; Fei Wang; Kai Wang; Li Wang; Xiang Wang; Ying Wang; Xiaoping Wu; Xinran Wu; Chunming Xie; Guangrong Xie; Haiyan Xie; Peng Xie; Xiufeng Xu; Hong Yang; Jian Yang; Jiashu Yao; Shuqiao Yao; Yingying Yin; Yonggui Yuan; Aixia Zhang; Hong Zhang; Kerang Zhang; Lei Zhang; Zhijun Zhang; Rubai Zhou; Yiting Zhou; Junjuan Zhu; Chaojie Zou; Yufeng Zang; Jingping Zhao; Calais Kin-Yuen Chan; Weidan Pu; Zhening Liu
Journal:  Neuroimage Clin       Date:  2020-01-07       Impact factor: 4.881

10.  Reliability, Convergent Validity and Time Invariance of Default Mode Network Deviations in Early Adult Major Depressive Disorder.

Authors:  Katie L Bessette; Lisanne M Jenkins; Kristy A Skerrett; Jennifer R Gowins; Sophie R DelDonno; Jon-Kar Zubieta; Melvin G McInnis; Rachel H Jacobs; Olusola Ajilore; Scott A Langenecker
Journal:  Front Psychiatry       Date:  2018-06-08       Impact factor: 4.157

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  1 in total

1.  Altered effective connectivity in sensorimotor cortices is a signature of severity and clinical course in depression.

Authors:  Dipanjan Ray; Dmitry Bezmaternykh; Mikhail Mel'nikov; Karl J Friston; Moumita Das
Journal:  Proc Natl Acad Sci U S A       Date:  2021-09-30       Impact factor: 12.779

  1 in total

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