Cortical network mechanisms in subcallosal cingulate deep brain stimulation for depression

medrxiv(2023)

引用 0|浏览2
暂无评分
摘要
Identifying functional biomarkers of clinical success can contribute to therapy optimization, and provide insights into the pathophysiology of treatment-resistant depression and mechanisms underlying the potential restorative effects of subcallosal cingulate deep brain stimulation. Magnetoencephalography data were obtained from 15 individuals who underwent subcallosal cingulate deep brain stimulation for treatment-resistant depression and 25 healthy subjects. The first objective herein was to identify region-specific oscillatory modulations for the identification of discriminative network nodes expressing (i) pathological differences in TRD (responders and non-responders, stimulation-OFF) compared to healthy subjects, which (ii) were counteracted by stimulation in a responder-specific manner. The second objective of this work was to further explore the mechanistic effects of stimulation intensity and frequency. Oscillatory power analyses led to the identification of discriminative regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca’s area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity. The identified discriminative network profile implies modulation of pathological activities in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. This modulated network profile may represent a functional substrate for therapy optimization. Stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or, to an even greater extent, by reducing frequency. ### Competing Interest Statement A.M.L. is a consultant to Abbott, Boston Scientific, Medtronic, and Functional Neuromodulation. L.M. has received honoraria and travel funds from Medtronic (unrelated to this work). All other authors declare no competing interests. ### Funding Statement This work was supported by the Alexander von Humboldt Foundation (M.S.), Canadian Institutes of Health Research (I.E.H.), National Institutes of Health Neurosurgeon Research Career Development Program K12 grant (N.C.R.), Canada Research Chair in Neuroscience (A.M.L.), and New Frontiers in Research Fund NFRFE-2021-00261 (L.M.). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the University Health Network Research Ethics Board (Toronto, Canada). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要