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Resting-State Functional Connectivity Impairment in Patients with Major Depressive Episode.
Stoyanov, Drozdstoy; Khorev, Vladimir; Paunova, Rositsa; Kandilarova, Sevdalina; Simeonova, Denitsa; Badarin, Artem; Hramov, Alexander; Kurkin, Semen.
Afiliación
  • Stoyanov D; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria.
  • Khorev V; Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia.
  • Paunova R; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria.
  • Kandilarova S; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria.
  • Simeonova D; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria.
  • Badarin A; Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia.
  • Hramov A; Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia.
  • Kurkin S; Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia.
Int J Environ Res Public Health ; 19(21)2022 10 28.
Article en En | MEDLINE | ID: mdl-36360924
AIM: This study aims to develop new approaches to characterize brain networks to potentially contribute to a better understanding of mechanisms involved in depression. METHOD AND SUBJECTS: We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed investigating functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were developed at a functional network level, using a false discovery rate method. Linear discriminant analysis was used to differentiate between the two groups. RESULTS AND DISCUSSION: Significant differences in functional connectivity (FC) between depressed patients vs. healthy controls was demonstrated, with brain regions including the lingual gyrus, cerebellum, midcingulate cortex and thalamus more prominent in healthy subjects as compared to depression where the orbitofrontal cortex emerged as a key node. Linear discriminant analysis demonstrated that full-connectivity matrices were the most precise in differentiating between depression vs. health subjects. CONCLUSION: The study provides supportive evidence for impaired functional connectivity networks in MDE patients.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trastorno Depresivo Mayor Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2022 Tipo del documento: Article País de afiliación: Bulgaria Pais de publicación: Suiza
Texto completo
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trastorno Depresivo Mayor Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2022 Tipo del documento: Article País de afiliación: Bulgaria Pais de publicación: Suiza