NEUROBIOLOGY OF MAJOR DEPRESSIVE DISORDER: THE ROLE OF THE DEFAULT MODE NETWORK AS A THERAPEUTIC TARGET
Abstract
Background: Major depressive disorder (MDD) is a complex psychiatric disorder associated with anomalies in large-scale brain connectivity, notably within the Default Mode Network (DMN). Objective: To narratively review the literature on DMN alterations in MDD, its interaction with the Salience Network (SN) and Central Executive Network (CEN) and evaluate therapeutic perspectives. Methods: A narrative literature review was conducted using PubMed, Scopus, Web of Science, Embase, and PsycINFO databases, focusing on functional connectivity via rs-fMRI, biomarkers, and neuromodulation. Results and Discussion: The literature indicates that individuals with MDD exhibit intra-network hyperconnectivity within the DMN, which correlates with rumination and emotional dysregulation. A systemic imbalance is evidenced due to inter-network failures in the triple network model (DMN-SN-CEN). Modulations by therapeutic interventions and Artificial Intelligence (AI) precision help identify biotypes, showing an association with the restoration of these functional pathways. Conclusion: Understanding MDD as a connectivity disorder offers new paradigms. The DMN emerges as a promising biomarker for precision psychiatry. However, its consolidated clinical application requires control of physiological noise and longitudinal studies focused on the continuous spectrum and patients' biological heterogeneity.
Author Biographies
Medical student and scholarship holder affiliated with the scientific initiation program at FAMESC University Center (UniFamesc), Bom Jesus do Itabapoana, Rio de Janeiro, Brazil.
Psychiatrist, professor, and advisor of a scientific initiation program affiliated with FAMESC University Center (UniFamesc), Bom Jesus do Itabapoana, Rio de Janeiro, Brazil.
References
ANDREWS-HANNA, J. R.; SMALLWOOD, J.; SPRENG, R. N. The default mode network and self-generated thought: component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, v. 1316, n. 1, p. 29–52, 2014.
BECKMANN, C. F.; DELUCA, M.; DEVLIN, J. T.; SMITH, S. M. Investigations into resting-state connectivity using independent component analysis. Philosophical Transactions of the Royal Society B: Biological Sciences, v. 360, n. 1457, p. 1001-1013, 2005.
BELZUNG, C.; WILLNER, P.; PHILLIPS, M. L. Neurobiology of depression: from novel insights to therapeutic strategies. Neuropharmacology, v. 191, p. 108562, 2021.
DINGA, R. et al. Evaluating the evidence for biotypes of depression: Methodological replication and extension of Drysdale et al. (2017). NeuroImage: Clinical, v. 22, p. 101796, 2019.
DRYSDALE, A. T. et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, v. 23, n. 1, p. 28–38, 2017.
DUMAN, R. S.; SANACORA, G.; KRYSTAL, J. H. Altered connectivity in depression: GABA and glutamate neurotransmitter deficits and reversal by novel treatments. Neuron, v. 102, n. 1, p. 75–90, 2019.
GRISANZIO, K. et al. Transdiagnostic symptom clusters and associations with brain, behavior, and daily function in mood, anxiety, and trauma disorders. JAMA Psychiatry, v. 75, n. 2, p. 201-209, 2018.
HAMILTON, J. P.; FARMER, M.; FOGELMAN, P.; GOTLIB, I. H. Default-mode network connectivity during rumination in major depression: a multimodal neuroimaging study. NeuroImage: Clinical, v. 11, p. 476–485, 2015.
KAISER, R. H.; ANDREWS-HANNA, J. R.; WAGER, T. D.; PIZZAGALLI, D. A. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry, v. 72, n. 6, p. 603–611, 2015.
LISTON, C. et al. Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological Psychiatry, v. 76, n. 7, p. 517–526, 2014.
MALHI, G. S.; MANN, J. J. Depression. The Lancet, v. 392, n. 10161, p. 2299–2312, 2018.
MENON, V. Large-scale brain networks and psychopathology: a unifying triple network model. Trends in Cognitive Sciences, v. 15, n. 10, p. 483–506, 2019.
MULDERS, P. C.; VAN EIJNDHOVEN, P. F.; SCHENE, A. H.; BECKMANN, C. F.; TENDOLKAR, I. Resting-state functional connectivity in major depressive disorder: a review. Neuroscience & Biobehavioral Reviews, v. 56, p. 330–344, 2015.
NORTON, D. J.; MCBAIN, R. K.; PIZZAGALLI, D. A.; ÖNGÜR, D.; CHEN, Y. Resting-state default mode network connectivity in major depressive disorder. Psychiatry Research: Neuroimaging, v. 263, p. 23–32, 2017.
RAICHLE, M. E. The brain’s default mode network. Annual Review of Neuroscience, v. 38, p. 433–447, 2015.
RANTALA, M. J. et al. Depression subtyping based on evolutionary psychiatry: proximate mechanisms and ultimate functions. Brain, Behavior, and Immunity, v. 69, p. 603-617, 2018.
RUSH, A. J. et al. Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design. Controlled Clinical Trials, v. 25, n. 1, p. 119–142, 2004.
SEELEY, W. W. et al. Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, v. 27, n. 9, p. 2349–2356, 2007.
SHELINE, Y. I.; PRICE, J. L.; YAN, Z.; MINTUN, M. A. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proceedings of the National Academy of Sciences, v. 107, n. 24, p. 11020–11025, 2010.
SIDDIQI, S. H. et al. Brain network mechanisms of transcranial magnetic stimulation in depression. Biological Psychiatry, v. 91, n. 8, p. 706–716, 2022.
WANG, X. et al. Aberrant default mode network in patients with major depressive disorder: a meta-analysis. Journal of Affective Disorders, v. 253, p. 29–38, 2019.
WILLIAMS, L. M. et al. Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety. Nature Medicine, v. 30, p. 1-10, jun. 2024.
WORLD HEALTH ORGANIZATION. Depression. Geneva: World Health Organization, 2023. Disponível em: https://www.who.int/news-room/fact-sheets/detail/depression Acesso em: 24 fev. 2025.
ZHOU, H. X. et al. Rumination and default mode network subsystems connectivity in major depressive disorder. NeuroImage: Clinical, v. 26, p. 102212, 2020.
License
Copyright (c) 2026 RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218
This work is licensed under a Creative Commons Attribution 4.0 International License.
Os direitos autorais dos artigos/resenhas/TCCs publicados pertecem à revista RECIMA21, e seguem o padrão Creative Commons (CC BY 4.0), permitindo a cópia ou reprodução, desde que cite a fonte e respeite os direitos dos autores e contenham menção aos mesmos nos créditos. Toda e qualquer obra publicada na revista, seu conteúdo é de responsabilidade dos autores, cabendo a RECIMA21 apenas ser o veículo de divulgação, seguindo os padrões nacionais e internacionais de publicação.