Literature DB >> 30952030

Network neurobiology of electroconvulsive therapy in patients with depression.

Preeti Sinha1, R Venkateswara Reddy2, Prerna Srivastava1, Urvakhsh M Mehta1, Rose Dawn Bharath3.   

Abstract

Graph theory, a popular analytic tool for resting state fMRI (rsfMRI) has provided important insights in the neurobiology of depression. We aimed to analyze the changes in the network measures of segregation and integration associated with the administration of ECT in patients with depression and to correlate with both clinical response and cognitive deficits. Changes in normalised clustering coefficient (γ), path length (λ) and small-world (σ) index were explored in 17 patients with depressive episode before 1st and after 6th brief-pulse bifrontal ECT (BFECT) sessions. Significant brain regions were then correlated with differences in clinical and cognitive scales. There was significantly increased γ and σ despite significant increase in λ in several brain regions after ECT in patients with depression. The brain areas revealing significant differences in γ before and after ECT were medial left superior frontal gyrus, left paracentral lobule, right pallidum and left inferior frontal operculum; correlating with changes in verbal fluency, HAM-D scores and delayed verbal memory (last two regions) respectively. BFECT reorganized the brain network topology in patients with depression and made it more segregated and less integrated; these correlated with clinical improvement and associated cognitive deficits.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Brain networks; Cognitive deficits; Depression; Electroconvulsive therapy; Graph theory analysis; Neurobiology

Mesh:

Year:  2019        PMID: 30952030     DOI: 10.1016/j.pscychresns.2019.03.008

Source DB:  PubMed          Journal:  Psychiatry Res Neuroimaging        ISSN: 0925-4927            Impact factor:   2.376


  6 in total

1.  Changes in the amplitude of low-frequency fluctuations in specific frequency bands in major depressive disorder after electroconvulsive therapy.

Authors:  Xin-Ke Li; Hai-Tang Qiu; Jia Hu; Qing-Hua Luo
Journal:  World J Psychiatry       Date:  2022-05-19

Review 2.  Electroconvulsive Therapy in Psychiatric Disorders: A Narrative Review Exploring Neuroendocrine-Immune Therapeutic Mechanisms and Clinical Implications.

Authors:  Milagros Rojas; Daniela Ariza; Ángel Ortega; Manuel E Riaño-Garzón; Mervin Chávez-Castillo; José Luis Pérez; Lorena Cudris-Torres; María Judith Bautista; Oscar Medina-Ortiz; Joselyn Rojas-Quintero; Valmore Bermúdez
Journal:  Int J Mol Sci       Date:  2022-06-22       Impact factor: 6.208

3.  Electroconvulsive Therapy-Induced Changes in Functional Brain Network of Major Depressive Disorder Patients: A Longitudinal Resting-State Electroencephalography Study.

Authors:  Shuting Sun; Peng Yang; Huayu Chen; Xuexiao Shao; Shanling Ji; Xiaowei Li; Gongying Li; Bin Hu
Journal:  Front Hum Neurosci       Date:  2022-05-18       Impact factor: 3.473

4.  Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms.

Authors:  Preeti Sinha; Himanshu Joshi; Dhruva Ithal
Journal:  Front Hum Neurosci       Date:  2021-01-21       Impact factor: 3.169

Review 5.  The Neurobiological Basis of Cognitive Side Effects of Electroconvulsive Therapy: A Systematic Review.

Authors:  Adriana Bassa; Teresa Sagués; Daniel Porta-Casteràs; Pilar Serra; Erika Martínez-Amorós; Diego J Palao; Marta Cano; Narcís Cardoner
Journal:  Brain Sci       Date:  2021-09-26

6.  Modulation of functional network properties in major depressive disorder following electroconvulsive therapy (ECT): a resting-state EEG analysis.

Authors:  Aron T Hill; Itay Hadas; Reza Zomorrodi; Daphne Voineskos; Faranak Farzan; Paul B Fitzgerald; Daniel M Blumberger; Zafiris J Daskalakis
Journal:  Sci Rep       Date:  2020-10-13       Impact factor: 4.379

  6 in total

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