Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation

Major depressive disorder (MDD) is associated with increased functional connectivity in specific neural networks. Electroconvulsive therapy (ECT), the gold-standard treatment for acute, treatment resistant MDD, but temporal dependencies between networks associated with ECT response have yet to be in...

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Main Authors: Christopher C. Abbott, Nicholas T. Lemke, Shruti eGopal, Robert J Thoma, Juan eBustillo, Vince D Calhoun, Jessica A Turner
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-03-01
Series:Frontiers in Psychiatry
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fpsyt.2013.00010/full
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spelling doaj-fb4533968d4f4c12b696b80b3eba76d02020-11-24T23:26:39ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402013-03-01410.3389/fpsyt.2013.0001042546Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigationChristopher C. Abbott0Nicholas T. Lemke1Shruti eGopal2Shruti eGopal3Robert J Thoma4Juan eBustillo5Vince D Calhoun6Vince D Calhoun7Vince D Calhoun8Vince D Calhoun9Vince D Calhoun10Jessica A Turner11Jessica A Turner12University of New Mexico Health Science CenterUniversity of New Mexico Health Science CenterRochester Institute of TechnologyMind Research NetworkUniversity of New Mexico Health Science CenterUniversity of New Mexico Health Science CenterUniversity of New Mexico Health Science CenterRochester Institute of TechnologyMind Research NetworkUniversity of New MexicoUniversity of New MexicoUniversity of New Mexico Health Science CenterMind Research NetworkMajor depressive disorder (MDD) is associated with increased functional connectivity in specific neural networks. Electroconvulsive therapy (ECT), the gold-standard treatment for acute, treatment resistant MDD, but temporal dependencies between networks associated with ECT response have yet to be investigated. In the present longitudinal, case-control investigation, we used independent component analysis (ICA) to identify distinct networks of brain regions with temporally coherent hemodynamic signal change and functional network connectivity (FNC) to assess component time course correlations across these networks. MDD subjects completed imaging and clinical assessments immediately prior to the ECT series and a minimum of five days after the last ECT treatment. We focused our analysis on four networks affected in MDD: the subcallosal cingulate gyrus, default mode, dorsal lateral prefrontal cortex, and dorsal medial prefrontal cortex. In a sample of ECT subjects (n = 12) with MDD, remission associated with the ECT series reverses the relationship from negative to positive between the posterior default mode and two other networks: the dorsal medial prefrontal cortex and left dorsal lateral prefrontal cortex. Relative to demographically healthy subjects (n = 12), the FNC between the posterior default mode areas and the dorsal medial prefrontal cortex normalizes with ECT response. The FNC changes following treatment did not correlate with symptom improvement; however, a direct comparison between ECT remitters and non-remitters showed the pattern of increased FNC between the posterior default mode and left dorsal lateral prefrontal cortex networks following ECT to be specific to those who responded to the treatment. The differences between ECT remitters and non-remitters suggest that this increased FNC between posterior default mode areas and the left dorsolateral prefrontal cortex is a neural correlate and potential biomarker of recovery from a depressed episode.http://journal.frontiersin.org/Journal/10.3389/fpsyt.2013.00010/fullElectroconvulsive TherapyIndependent Component AnalysisMajor Depressive Disorderfunctional network connectivityresting state fMRI
collection DOAJ
language English
format Article
sources DOAJ
author Christopher C. Abbott
Nicholas T. Lemke
Shruti eGopal
Shruti eGopal
Robert J Thoma
Juan eBustillo
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Jessica A Turner
Jessica A Turner
spellingShingle Christopher C. Abbott
Nicholas T. Lemke
Shruti eGopal
Shruti eGopal
Robert J Thoma
Juan eBustillo
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Jessica A Turner
Jessica A Turner
Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
Frontiers in Psychiatry
Electroconvulsive Therapy
Independent Component Analysis
Major Depressive Disorder
functional network connectivity
resting state fMRI
author_facet Christopher C. Abbott
Nicholas T. Lemke
Shruti eGopal
Shruti eGopal
Robert J Thoma
Juan eBustillo
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Vince D Calhoun
Jessica A Turner
Jessica A Turner
author_sort Christopher C. Abbott
title Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
title_short Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
title_full Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
title_fullStr Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
title_full_unstemmed Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fMRI investigation
title_sort electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state fmri investigation
publisher Frontiers Media S.A.
series Frontiers in Psychiatry
issn 1664-0640
publishDate 2013-03-01
description Major depressive disorder (MDD) is associated with increased functional connectivity in specific neural networks. Electroconvulsive therapy (ECT), the gold-standard treatment for acute, treatment resistant MDD, but temporal dependencies between networks associated with ECT response have yet to be investigated. In the present longitudinal, case-control investigation, we used independent component analysis (ICA) to identify distinct networks of brain regions with temporally coherent hemodynamic signal change and functional network connectivity (FNC) to assess component time course correlations across these networks. MDD subjects completed imaging and clinical assessments immediately prior to the ECT series and a minimum of five days after the last ECT treatment. We focused our analysis on four networks affected in MDD: the subcallosal cingulate gyrus, default mode, dorsal lateral prefrontal cortex, and dorsal medial prefrontal cortex. In a sample of ECT subjects (n = 12) with MDD, remission associated with the ECT series reverses the relationship from negative to positive between the posterior default mode and two other networks: the dorsal medial prefrontal cortex and left dorsal lateral prefrontal cortex. Relative to demographically healthy subjects (n = 12), the FNC between the posterior default mode areas and the dorsal medial prefrontal cortex normalizes with ECT response. The FNC changes following treatment did not correlate with symptom improvement; however, a direct comparison between ECT remitters and non-remitters showed the pattern of increased FNC between the posterior default mode and left dorsal lateral prefrontal cortex networks following ECT to be specific to those who responded to the treatment. The differences between ECT remitters and non-remitters suggest that this increased FNC between posterior default mode areas and the left dorsolateral prefrontal cortex is a neural correlate and potential biomarker of recovery from a depressed episode.
topic Electroconvulsive Therapy
Independent Component Analysis
Major Depressive Disorder
functional network connectivity
resting state fMRI
url http://journal.frontiersin.org/Journal/10.3389/fpsyt.2013.00010/full
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