Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression

Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the im...

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Veröffentlicht in:Journal of affective disorders 2023-05, Vol.328, p.141-152
Hauptverfasser: Kyuragi, Yusuke, Oishi, Naoya, Yamasaki, Shimpei, Hazama, Masaaki, Miyata, Jun, Shibata, Mami, Fujiwara, Hironobu, Fushimi, Yasutaka, Murai, Toshiya, Suwa, Taro
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container_start_page 141
container_title Journal of affective disorders
container_volume 328
creator Kyuragi, Yusuke
Oishi, Naoya
Yamasaki, Shimpei
Hazama, Masaaki
Miyata, Jun
Shibata, Mami
Fujiwara, Hironobu
Fushimi, Yasutaka
Murai, Toshiya
Suwa, Taro
description Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the imaging correlates of the electroconvulsive therapy effects on depression using Granger causality analysis and dynamic functional connectivity analyses. We performed advanced analyses of resting-state functional magnetic resonance imaging data at the beginning and intermediate stages and end of the therapeutic course to identify neural markers that reflect or predict the therapeutic effects of electroconvulsive therapy on depression. We demonstrated that information flow between the functional networks analyzed by Granger causality changes during electroconvulsive therapy, and this change was correlated with the therapeutic outcome. Information flow and the dwell time (an index reflecting the temporal stability of functional connectivity) before electroconvulsive therapy are correlated with depressive symptoms during and after treatment. First, the sample size was small. A larger group is needed to confirm our findings. Second, the influence of concomitant pharmacotherapy on our results was not fully addressed, although we expected it to be minimal because only minor changes in pharmacotherapy occurred during electroconvulsive therapy. Third, different scanners were used the groups, although the acquisition parameters were the same; a direct comparison between patient and healthy participant data was not possible. Thus, we presented the data of the healthy participants separately from that of the patients as a reference. These results show the specific properties of functional brain connectivity. •Information flow between networks changes during electroconvulsive therapy (ECT).•This change was correlated with the therapeutic outcome.•Information flow before ECT correlated with depressive symptoms during and after ECT.•Dwell time before ECT correlated with depressive symptoms during and after ECT.
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subjects Brain
Brain Mapping
Depression
Depression - therapy
Dynamic functional connectivity
Electroconvulsive therapy
Electroconvulsive Therapy - methods
Humans
Information flow
Magnetic Resonance Imaging
Resting-state functional magnetic resonance imaging
title Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression
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