Poster No:
2097
Submission Type:
Abstract Submission
Authors:
Hsin-Yu Kan1, Shih-Jen Tsai2, Hsin-Jung Tsai1
Institutions:
1National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Taipei Veterans General Hospital, Taipei, Taiwan
First Author:
Co-Author(s):
Introduction:
Depression is a leading global cause of disability, contributing to significant healthcare costs and socioeconomic burdens. It is well established that depression and insomnia frequently co-occur, with both disorders linked to elevated high-frequency EEG activity in the brain. In this study, we prospectively applied EEG-based neurofeedback to investigate whether modulating cortical activity could improve self-reported sleep quality and reduce insomnia severity in patients with major depression. Additionally, the relationship between resting-state EEG activity, depressive symptoms, and insomnia was examined.
Methods:
Patients diagnosed with major depressive disorder (MDD) were enrolled and randomly assigned to either the high-frequency inhibition group (experimental group) or the low-frequency enhancement group (control group). Both groups completed 12 neurofeedback sessions over six weeks. Depression severity was assessed using the Hamilton Depression Rating Scale (HAMD) before and after the intervention by an independent psychiatrist blinded to group allocation. Self-reported measures included sleep quality (Pittsburgh Sleep Quality Index, PSQI), insomnia severity (Insomnia Severity Index, ISI), and depressive symptoms (Patient Health Questionnaire-9, PHQ-9; Beck Depression Inventory, BDI). These assessments were conducted at baseline and after 4, 8, and 12 sessions (post-intervention). Prior to each neurofeedback session, a 150-s resting-state EEG was recorded from the C4 electrode under eyes-closed conditions. EEG measures included the absolute power and relative power of the beta-band (15–30 Hz) or theta-band (5–8 Hz). Mean power values were derived from a cluster of four resting-state EEG recordings taken at the same evaluation time points. To examine the relationships among sleep quality, depressive symptoms, and resting-state EEG features, Spearman's correlation analysis was performed.
Results:
Sixteen patients with mild to moderate depression were randomized into experimental and control groups, with no significant baseline differences in demographics, depression severity, or insomnia measures (PSQI, p = 0.25; ISI, p = 0.3). Post-intervention, the experimental group showed a trend toward improved sleep quality (PSQI, p = 0.065) and significant reductions in depression severity (HAMD, p = 0.013; PHQ-9, p = 0.03; BDI, p = 0.011). At baseline, a significant positive correlation between the absolute beta power and BDI scores was found (r = 0.8, p = 0.01), and relative beta power also positively correlated with PHQ-9 (r = 0.822, p = 0.007). After 4 sessions, absolute beta power further should a positive correlation with PHQ-9 (r = 0.872, p = 0.002). After 12 training sessions, absolute beta power significantly correlated with HAMD (r = 0.804, p = 0.009), PHQ-9 (r = 0.749, p = 0.02), and BDI (r = 0.8, p = 0.01). The absolute beta power exhibited a downward trend (p = 0.068) after 12 training sessions in the experimental group. Moreover, the beta-band power of EEG also correlated with insomnia severity among depressive patients over time. A significant positive correlation with insomnia severity at baseline (relative beta power with ISI, r = 0.762, p = 0.017) and after 4 sessions (absolute beta power with ISI, r = 0.675, p = 0.046) were observed. However, in the control group, depressive symptoms showed a significant decrease (PHQ-9, p = 0.027; BDI, p = 0.018) at post-intervention, but no significant differences in sleep quality or EEG power were found.
Conclusions:
EEG-based neurofeedback targeting high-frequency inhibition may improve sleep quality and reduce insomnia severity in patients with MDD. Significant correlations between beta power and insomnia severity suggest that modulating high-frequency EEG activity could alleviate sleep disturbances associated with depression. These findings support neurofeedback as a potential therapeutic tool for addressing sleep issues in this population.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Novel Imaging Acquisition Methods:
EEG
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 1
Keywords:
Electroencephaolography (EEG)
Psychiatric Disorders
Sleep
Other - Neurofeedback
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
EEG/ERP
Other, Please specify
-
Neurofeedback
Provide references using APA citation style.
Tsai, H. J., Yang, W. C., Tsai, S. J., Lin, C. H., & Yang, A. C. (2021). Remission of depression is associated with asymmetric hemispheric variation in EEG complexity before antidepressant treatment. Journal of affective disorders, 281, 872–879. https://doi.org/10.1016/j.jad.2020.11.041
Tsai, H. J., Yang, W. C., Tsai, S. J., Lin, C. H., & Yang, A. C. (2023). Right-side frontal-central cortical hyperactivation before the treatment predicts outcomes of antidepressant and electroconvulsive therapy responsivity in major depressive disorder. Journal of psychiatric research, 161, 377–385. https://doi.org/10.1016/j.jpsychires.2023.03.023https://doi.org/10.1016/j.jpsychires.2023.03.023
Wang, S. Y., Lin, I. M., Fan, S. Y., Tsai, Y. C., Yen, C. F., Yeh, Y. C., Huang, M. F., Lee, Y., Chiu, N. M., Hung, C. F., Wang, P. W., Liu, T. L., & Lin, H. C. (2019). The effects of alpha asymmetry and high-beta down-training neurofeedback for patients with the major depressive disorder and anxiety symptoms. Journal of affective disorders, 257, 287–296. https://doi.org/10.1016/j.jad.2019.07.026
Chen, T. C., & Lin, I. M. (2020). The learning effects and curves during high beta down-training neurofeedback for patients with major depressive disorder. Journal of affective disorders, 266, 235–242. https://doi.org/10.1016/j.jad.2020.01.175
Patil, A. U., Lin, C., Lee, S. H., Huang, H. W., Wu, S. C., Madathil, D., & Huang, C. M. (2023). Review of EEG-based neurofeedback as a therapeutic intervention to treat depression. Psychiatry research. Neuroimaging, 329, 111591. https://doi.org/10.1016/j.pscychresns.2023.111591
Dobbins, I. C. S., Bastos, M., Ratis, R. C., Silva, W. C. F. N. D., & Bonini, J. S. (2023). Effects of neurofeedback on major depressive disorder: a systematic review. Einstein (Sao Paulo, Brazil), 21, eRW0253. https://doi.org/10.31744/einstein_journal/2023RW0253
Recio-Rodriguez, J. I., Fernandez-Crespo, M., Sanchez-Aguadero, N., Gonzalez-Sanchez, J., Garcia-Yu, I. A., Alonso-Dominguez, R., Chiu, H. Y., Tsai, P. S., Lee, H. C., & Rihuete-Galve, M. I. (2024). Neurofeedback to enhance sleep quality and insomnia: a systematic review and meta-analysis of randomized clinical trials. Frontiers in neuroscience, 18, 1450163. https://doi.org/10.3389/fnins.2024.1450163
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