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 |
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container_title | Journal of affective disorders |
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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. |
doi_str_mv | 10.1016/j.jad.2023.02.060 |
format | Article |
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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.</description><identifier>ISSN: 0165-0327</identifier><identifier>EISSN: 1573-2517</identifier><identifier>DOI: 10.1016/j.jad.2023.02.060</identifier><identifier>PMID: 36801417</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>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</subject><ispartof>Journal of affective disorders, 2023-05, Vol.328, p.141-152</ispartof><rights>2023 The Authors</rights><rights>Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-af4e4f7cc11ccb6fa004d1d3b567342f5309fa6be8a7bc2639472488ce7c3ceb3</citedby><cites>FETCH-LOGICAL-c396t-af4e4f7cc11ccb6fa004d1d3b567342f5309fa6be8a7bc2639472488ce7c3ceb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jad.2023.02.060$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36801417$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kyuragi, Yusuke</creatorcontrib><creatorcontrib>Oishi, Naoya</creatorcontrib><creatorcontrib>Yamasaki, Shimpei</creatorcontrib><creatorcontrib>Hazama, Masaaki</creatorcontrib><creatorcontrib>Miyata, Jun</creatorcontrib><creatorcontrib>Shibata, Mami</creatorcontrib><creatorcontrib>Fujiwara, Hironobu</creatorcontrib><creatorcontrib>Fushimi, Yasutaka</creatorcontrib><creatorcontrib>Murai, Toshiya</creatorcontrib><creatorcontrib>Suwa, Taro</creatorcontrib><title>Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression</title><title>Journal of affective disorders</title><addtitle>J Affect Disord</addtitle><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.</description><subject>Brain</subject><subject>Brain Mapping</subject><subject>Depression</subject><subject>Depression - therapy</subject><subject>Dynamic functional connectivity</subject><subject>Electroconvulsive therapy</subject><subject>Electroconvulsive Therapy - methods</subject><subject>Humans</subject><subject>Information flow</subject><subject>Magnetic Resonance Imaging</subject><subject>Resting-state functional magnetic resonance imaging</subject><issn>0165-0327</issn><issn>1573-2517</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kMtO3DAUQC1EBVPgA7pBXrJJ6kdiJ-qqQkCRkLqha8uxr4tHiR3sZND8PR4NdNmVZd9zj-SD0DdKakqo-L6tt9rWjDBeE1YTQU7QhraSV6yl8hRtCtNWhDN5jr7mvCWEiF6SM3TORUdoQ-UGvT4GF9OkFx8DdmN8wzpYbPdBT95gtwZzmOgRmxgClMvOL3ts1-TDXwxjeUmxjHbrmP0O8PICSc977AOeixPCkvGbX16whTlBzsV1ib44PWa4-jgv0J_7u-fbX9XT74fH259PleG9WCrtGmicNIZSYwbhNCGNpZYPrZC8Ya7lpHdaDNBpORgmeN9I1nSdAWm4gYFfoJujd07xdYW8qMlnA-OoA8Q1KyZl18uulCooPaImxZwTODUnP-m0V5SoQ2m1VaW0OpRWhKlSuuxcf-jXYQL7b-MzbQF-HAEon9x5SCqbEsSA9alkUzb6_-jfAYKskjo</recordid><startdate>20230501</startdate><enddate>20230501</enddate><creator>Kyuragi, Yusuke</creator><creator>Oishi, Naoya</creator><creator>Yamasaki, Shimpei</creator><creator>Hazama, Masaaki</creator><creator>Miyata, Jun</creator><creator>Shibata, Mami</creator><creator>Fujiwara, Hironobu</creator><creator>Fushimi, Yasutaka</creator><creator>Murai, Toshiya</creator><creator>Suwa, Taro</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20230501</creationdate><title>Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression</title><author>Kyuragi, Yusuke ; Oishi, Naoya ; Yamasaki, Shimpei ; Hazama, Masaaki ; Miyata, Jun ; Shibata, Mami ; Fujiwara, Hironobu ; Fushimi, Yasutaka ; Murai, Toshiya ; Suwa, Taro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-af4e4f7cc11ccb6fa004d1d3b567342f5309fa6be8a7bc2639472488ce7c3ceb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Brain</topic><topic>Brain Mapping</topic><topic>Depression</topic><topic>Depression - therapy</topic><topic>Dynamic functional connectivity</topic><topic>Electroconvulsive therapy</topic><topic>Electroconvulsive Therapy - methods</topic><topic>Humans</topic><topic>Information flow</topic><topic>Magnetic Resonance Imaging</topic><topic>Resting-state functional magnetic resonance imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kyuragi, Yusuke</creatorcontrib><creatorcontrib>Oishi, Naoya</creatorcontrib><creatorcontrib>Yamasaki, Shimpei</creatorcontrib><creatorcontrib>Hazama, Masaaki</creatorcontrib><creatorcontrib>Miyata, Jun</creatorcontrib><creatorcontrib>Shibata, Mami</creatorcontrib><creatorcontrib>Fujiwara, Hironobu</creatorcontrib><creatorcontrib>Fushimi, Yasutaka</creatorcontrib><creatorcontrib>Murai, Toshiya</creatorcontrib><creatorcontrib>Suwa, Taro</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of affective disorders</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kyuragi, Yusuke</au><au>Oishi, Naoya</au><au>Yamasaki, Shimpei</au><au>Hazama, Masaaki</au><au>Miyata, Jun</au><au>Shibata, Mami</au><au>Fujiwara, Hironobu</au><au>Fushimi, Yasutaka</au><au>Murai, Toshiya</au><au>Suwa, Taro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression</atitle><jtitle>Journal of affective disorders</jtitle><addtitle>J Affect Disord</addtitle><date>2023-05-01</date><risdate>2023</risdate><volume>328</volume><spage>141</spage><epage>152</epage><pages>141-152</pages><issn>0165-0327</issn><eissn>1573-2517</eissn><abstract>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.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>36801417</pmid><doi>10.1016/j.jad.2023.02.060</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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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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