Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/116782
Full metadata record
DC FieldValueLanguage
dc.contributor.authorArgyelan, Miklos-
dc.contributor.authorDeng, Zhi-De-
dc.contributor.authorOusdal, Olga Therese-
dc.contributor.authorOltedal, Leif-
dc.contributor.authorAngulo, Brian-
dc.contributor.authorBaradits, Mate-
dc.contributor.authorSpitzberg, Andrew J.-
dc.contributor.authorKessler, Ute-
dc.contributor.authorSartorius, Alexander-
dc.contributor.authorDols, Annemiek-
dc.contributor.authorNarr, Katherine L.-
dc.contributor.authorEspinoza, Randall-
dc.contributor.authorvan Waarde, Jeroen A.-
dc.contributor.authorTendolkar, Indira-
dc.contributor.authorvan Eijndhoven, Philip-
dc.contributor.authorvan Wingen, Guido A.-
dc.contributor.authorTakamiya, Akihiro-
dc.contributor.authorKishimoto, Taishiro-
dc.contributor.authorJorgensen, Martin B.-
dc.contributor.authorJorgensen, Anders-
dc.contributor.authorPaulson, Olaf B.-
dc.contributor.authorYrondi, Antoine-
dc.contributor.authorPéran, Patrice-
dc.contributor.authorSoriano-Mas, Carles-
dc.contributor.authorCardoner, Narcis-
dc.contributor.authorCano, Marta-
dc.contributor.authorvan Diermen, Linda-
dc.contributor.authorSchrijvers, Didier-
dc.contributor.authorBelge, Jean-Baptiste-
dc.contributor.authorEmsell, Louise-
dc.contributor.authorBouckaert, Filip-
dc.contributor.authorVandenbulcke, Mathieu-
dc.contributor.authorKiebs, Maximilian-
dc.contributor.authorHurlemann, René-
dc.contributor.authorMulders, Peter C. R.-
dc.contributor.authorRedlich, Ronny-
dc.contributor.authorDannlowski, Udo-
dc.contributor.authorKavakbasi, Erhan-
dc.contributor.authorKritzer, Michael D.-
dc.contributor.authorEllard, Kristen K.-
dc.contributor.authorCamprodon, Joan A.-
dc.contributor.authorPetrides, Georgios-
dc.contributor.authorMalhotra, Anil K.-
dc.contributor.authorAbbott, Christopher C.-
dc.date.accessioned2024-10-07T16:45:41Z-
dc.date.available2024-10-07T16:45:41Z-
dc.date.issued2024-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/118741-
dc.identifier.urihttp://dx.doi.org/10.25673/116782-
dc.description.abstractNeurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = −2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.eng
dc.language.isoeng-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subject.ddc610-
dc.titleElectroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depressioneng
dc.typeArticle-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleMolecular psychiatry-
local.bibliographicCitation.volume29-
local.bibliographicCitation.issue2-
local.bibliographicCitation.pagestart229-
local.bibliographicCitation.pageend237-
local.bibliographicCitation.publishernameSpringer Nature-
local.bibliographicCitation.publisherplace[London]-
local.bibliographicCitation.doi10.1038/s41380-023-02318-2-
local.subject.keywordsDepression, Predictive markers-
local.openaccesstrue-
dc.identifier.ppn1878067966-
cbs.publication.displayform2024-
local.bibliographicCitation.year2024-
cbs.sru.importDate2024-10-07T16:44:25Z-
local.bibliographicCitationEnthalten in Molecular psychiatry - [London] : Springer Nature, 1997-
local.accessrights.dnbfree-
Appears in Collections:Open Access Publikationen der MLU

Files in This Item:
File Description SizeFormat 
s41380-023-02318-2.pdf2.23 MBAdobe PDFThumbnail
View/Open