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Title
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Movement, mood and cognition : preliminary insights into the therapeutic effects of electroconvulsive therapy for depression through a resting-state connectivity analysis
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Author
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Abstract
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| Background: Electroconvulsive therapy (ECT) is a highly effective treatment for depression but how it achieves its clinical effects remains unclear. Methods: We set out to study the brain & rsquo;s response to ECT from a large-scale brain-network perspective. Using a voxelwise analysis, we looked at resting-state functional connectivity before and after a course of ECT at the whole-brain and the between- and within-network levels in 17 patients with a depressive episode. Using a groupindependent component analysis approach, we focused on four networks known to be affected in depression: the salience network (SN), the default mode network (DMN), the cognitive executive network (CEN), and a subcortical network (SCN). Our clinical measures included mood, cognition, and psychomotor symptoms. Results: We found ECT to have increased the connectivity of the left CEN with the left angular gyrus and left middle frontal gyrus as well as its within-network connectivity. Both the right CEN and the SCN showed increased connectivity with the precuneus and the anterior DMN with the left amygdala. Finally, improvement of psychomotor retardation was positively correlated with an increase of within-posterior DMN connectivity. Limitations: The limitations of our study include its small sample size and the lack of a control dataset to confirm our findings. Conclusion: Our voxelwise data demonstrate that ECT induces a significant increase of connectivity across the whole brain and at the within-network level. Furthermore, we provide the first evidence on the association between an increase of within-posterior DMN connectivity and an improvement of psychomotor retardation, a core symptom of depression. |
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Language
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English
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Source (journal)
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Journal of affective disorders. - Amsterdam
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Publication
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Amsterdam
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2021
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ISSN
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0165-0327
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DOI
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10.1016/J.JAD.2021.04.069
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Volume/pages
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290
(2021)
, p. 117-127
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ISI
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000663776700015
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Pubmed ID
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33993078
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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