Neuroimaging in Anxiety and Depression: An Integrative Review of fMRI, EEG, and Neural Biomarkers
Keywords:
Neuroimaging, Anxiety Disorders, Depressive Disorders, fMRI, EEG, Neural BiomarkersAbstract
Anxiety and depressive disorders are highly prevalent psychiatric conditions associated with significant disability worldwide. Neuroimaging has advanced understanding of their neural substrates, particularly through functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This integrative review synthesized studies published between 2013 and 2025 retrieved from PubMed, Scopus, Web of Science, and PsycINFO, including adult clinical samples diagnosed with anxiety and/or depressive disorders. Evidence consistently indicates dysregulation within fronto-limbic circuitry and large-scale brain networks, notably involving the amygdala, prefrontal cortex, anterior cingulate cortex, and default mode network. fMRI findings highlight altered functional connectivity and impaired emotional regulation, whereas EEG studies reveal abnormalities in oscillatory activity and event-related potentials linked to attentional bias and cognitive control. Although convergent neural markers emerge across modalities, methodological heterogeneity limits reproducibility and clinical application. Multimodal integration of spatial and temporal neural measures may enhance biomarker reliability and support the development of precision psychiatry approaches.
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References
Brown, O., & Eremenko, P. (2006). The value proposition for fractionated spacecraft. Acta Astronautica, 58(12), 645–657. https://doi.org/10.1016/j.actaastro.2006.02.002
Disner, S. G., Beevers, C. G., Haigh, E. A. P., & Beck, A. T. (2011). Neural mechanisms of the cognitive model of depression. Nature Reviews Neuroscience, 12(8), 467–477. https://doi.org/10.1038/nrn3027
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., … Liston, C. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, 23(1), 28–38. https://doi.org/10.1038/nm.4246
Engel, A. K., & Fries, P. (2010). Beta-band oscillations—signalling the status quo? Current Opinion in Neurobiology, 20(2), 156–165. https://doi.org/10.1016/j.conb.2010.02.015
Etkin, A., & Wager, T. D. (2007). Functional neuroimaging of anxiety: A meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. American Journal of Psychiatry, 164(10), 1476–1488. https://doi.org/10.1176/appi.ajp.2007.07030504
Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700–711. https://doi.org/10.1038/nrn2201
Hamilton, J. P., Farmer, M., Fogelman, P., & Gotlib, I. H. (2015). Depressive rumination, the default-mode network, and the dark matter of clinical neuroscience. Biological Psychiatry, 78(4), 224–230. https://doi.org/10.1016/j.biopsych.2015.02.020
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D., Quinn, K., … Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167(7), 748–751. https://doi.org/10.1176/appi.ajp.2010.09091379
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015). Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72(6), 603–611. https://doi.org/10.1001/jamapsychiatry.2015.0071
Luck, S. J. (2014). An introduction to the event-related potential technique (2nd ed.). MIT Press.
Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003
Moser, J. S., Moran, T. P., Schroder, H. S., Donnellan, M. B., & Yeung, N. (2013). On the relationship between anxiety and error monitoring: A meta-analysis and conceptual framework. Biological Psychology, 93(1), 1–10. https://doi.org/10.1016/j.biopsycho.2012.12.001
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafo, M. R., … Yarkoni, T. (2017). Scanning the horizon: Towards transparent and reproducible neuroimaging research. Nature Reviews Neuroscience, 18(2), 115–126. https://doi.org/10.1038/nrn.2016.167
Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128–2148. https://doi.org/10.1016/j.clinph.2007.04.019
Sheline, Y. I., Price, J. L., Yan, Z., & Mintun, M. A. (2010). Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proceedings of the National Academy of Sciences, 107(24), 11020–11025. https://doi.org/10.1073/pnas.1000446107
Thibodeau, R., Jorgensen, R. S., & Kim, S. (2006). Depression, anxiety, and resting frontal EEG asymmetry: A meta-analytic review. Biological Psychology, 71(1), 1–13. https://doi.org/10.1016/j.biopsycho.2005.01.005
World Health Organization. (2023). Depression and other common mental disorders: Global health estimates. World Health Organization.
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Copyright (c) 2026 Marina CORRÊA FREITAS, Fabrício Veloso (Author)

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Articles published in the Journal of Biomedical & Space Sciences (JBSS) are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Authors retain copyright and grant the journal the right of first publication. Users are free to share and adapt the material provided proper attribution is given to the original author and source. ISSN: 3086-4712