The Effectiveness of Neurofeedback Training on Cognitive Function Improvement and Quantitative Electroencephalography Features in Poststroke Cognitive Impairment

Authors

DOI:

https://doi.org/10.15540/nr.13.1.2

Keywords:

post-stroke cognitive impairment, neurofeedback training, quantitative electroencephalography, MoCA-INA

Abstract

Background. Poststroke cognitive impairment (PSCI) involves cognitive deficits emerging within 3 months after stroke. Quantitative EEG (qEEG) in PSCI typically shows changes in relative power, delta-alpha ratio, and peak alpha frequency. Neurofeedback training (NFT) is a promising intervention to improve cognitive function and qEEG patterns, though findings remain inconsistent. Nonetheless, even brief NFT interventions may yield meaningful benefits. Methods. This study assessed the effectiveness of five individualized qEEG-guided NFT sessions (30 min each) in 24 PSCI patients, focusing on changes in MoCA-INA scores and qEEG parameters. Results. NFT significantly improved MoCA-INA scores (Z = −4.106, p < .001, effect size = 0.839), particularly in visuospatial/executive and delayed recall domains, with sustained effects 1 month later. QEEG analysis revealed increased temporal alpha (t = −1.875, p = .037, effect size = 0.23) and parietal beta relative power (t = −1.827, p = .040, effect size = 0.11). Greater cognitive gains were observed in patients aged ≤60 years. Conclusion. These findings support the clinical utility of short-term, qEEG-guided NFT in improving cognitive outcomes and modulating neural activity in PSCI patients. The sustained benefits observed suggest potential for long-term therapeutic impact.

References

Ali, J. I., Viczko, J., & Smart, C. M. (2020). Efficacy of neurofeedback interventions for cognitive rehabilitation following brain injury: Systematic review and recommendations for future research. Journal of the International Neuropsychological Society, 26(1), 31–46. https://doi.org/10.1017/s1355617719001061

Andrade, K., Guieysse, T., Razafimahatratra, S., Houmani, N., Klarsfeld, A., Dreyfus, G., Dubois, B., Medani, T., & Vialatte, F. (2022). EEG-neurofeedback for promoting neuromodulation in the elderly: Evidence from a double-blind study. bioRxiv, Article 509227. https://doi.org/10.1101/2022.09.26.509227

Anggraeni, D., Haddani, M., Handayani, S., Nindela, R., & Febrianto, Y. (2024). Effectiveness of neurofeedback training in poststroke cognitive impairment. NeuroRegulation, 11(3), 296–303. https://doi.org/10.15540/nr.11.3.296

Arcos-Burgos, M., Lopera, F., Sepulveda-Falla, D., & Mastronardi, C. (2019). Neural plasticity during aging. Neural Plasticity, 2019, Article 6042132. https://doi.org/10.1155/2019/6042132

Babiloni, C., Arakaki, X., Bonanni, L., Bujan, A., Carrillo, M. C., Del Percio, C., Edelmayer, R. M., Egan, G., Elahh, F. M., Evans, A., Ferri, R., Frisoni, G. B., Güntekin, B., Hainsworth, A., Hampel, H., Jelic, V., Jeong, J., Kim, D. K., Kramberger, M., … Yener, G. (2021). EEG measures for clinical research in major vascular cognitive impairment: Recommendations by an expert panel. Neurobiology of Aging, 103, 78–97. https://doi.org/10.1016/j.neurobiolaging.2021.03.003

Cho, H.-Y., Kim, K.-T., & Jung, J.-H. (2016). Effects of neurofeedback and computer-assisted cognitive rehabilitation on relative brain wave ratios and activities of daily living of stroke patients: A randomized control trial. Journal of Physical Therapy Science, 28(7), 2154–2158. https://doi.org/10.1589/jpts.28.2154

Hadiyoso, S., Zakaria, H., Anam, P. A., & Rajab, T. L. E. (2022). EEG-based spectral dynamic in characterization of poststroke patients with cognitive impairment for early detection of vascular dementia. Journal of Healthcare Engineering, 2022(1), Article 5666229. https://doi.org/10.1155/2022/5666229

Hohenfeld, C., Nellessen, N., Dogan, I., Kuhn, H., Müller, C., & Papa, F., Ketteler, S., Goebel, R., Heinecke, A., Shah, N. J., Schulz, J. B., Reske, M., & Reetz, K. (2017). Cognitive improvement and brain changes after real-time functional MRI neurofeedback training in healthy elderly and prodromal Alzheimer’s disease. Frontiers in Neurology, 8, Article 384. https://doi.org/10.3389/fneur.2017.00384

Jang, J.-H., Kim, J., Park, G., Kim, H., Jung, E.-S., Cha, J.-Y., Kim, C.-Y., Kim, S., Lee, J.-H., & Yoo, H. (2019). Beta wave enhancement neurofeedback improves cognitive functions in patients with mild cognitive impairment. Medicine (Baltimore), 98(50), Article e18357. https://doi.org/10.1097/md.0000000000018357

Kober, S. E., Schweiger, D., Witte, M., Grieshofer, P., Neuper, C., & Wood, G. (2017). Upper alpha based neurofeedback training in chronic stroke: Brain plasticity processes and cognitive effects. Applied Psychophysiology and Biofeedback, 42(1), 69–83. https://doi.org/10.1007/s10484-017-9353-5

Kober, S. E., Schweiger, D., Witte, M., Reichert, J. L., Grieshofer, P., Neuper, C., & Wood, G. (2015). Specific effects of EEG based neurofeedback training on memory functions in post-stroke victims. Journal of NeuroEngineering and Rehabilitation, 12(1), Article 107. https://doi.org/10.1186/s12984-015-0105-6

Lavy, Y., Dwolatzky, T., Kaplan, Z., Guez, J., & Todder, D. (2018). Neurofeedback improves memory and peak alpha frequency in individuals with mild cognitive impairment. Applied Psychophysiology and Biofeedback, 44, 41–49. https://doi.org/10.1007/s10484-018-9418-0

Lin, Y.-R., Hsu, T.-W., Hsu, C.-W., Chen, P.-Y., Tseng, P.-T., & Liang, C.-S. (2024). Effectiveness of electroencephalography neurofeedback for improving working memory and episodic memory in the elderly: A meta-analysis. Medicina, 60(3), 369. https://doi.org/10.3390/medicina60030369

Lujimes, R. E., Pouwel, S., & Boonman, J. (2016). The effectiveness of neurofeedback on cognitive functioning in patients with Alzheimer’s disease: Preliminary results. Neurophysiologie Clinique, 46(3), 179–187. https://doi.org/10.1016/j.neucli.2016.05.069

Madijova, Y. N., Azimoba, N. M., Xusenoa, N. T., & Salikhoa, S. M. (2024). Optimization of cognitive disorders in dementia using the neurofeedback therapy. International Scientific Journal, 3(2), 183–193. https://doi.org/10.5281/zenodo.10714723

Marcos-Martínez, D., Martínez-Cagigal, V., Santamaría-Vázquez, E., Pérez-Velasco, S., & Hornero, R. (2021). Neurofeedback training based on motor imagery strategies increases EEG complexity in elderly population. Entropy, 23(12), 1574. https://doi.org/10.3390/e23121574

Marlats, F., Bao, G., Chevallier, S., Boubaya, M., Djabelkhir-Jemmi, L., Wu, Y.-H., Lenoir, H., Rigaud, A.-S., & Azabou, E. (2020). SMR/theta neurofeedback training improves cognitive performance and EEG activity in elderly with mild cognitive impairment: A pilot study. Frontiers in Aging Neuroscience, 12, Article 147. https://doi.org/10.3389/fnagi.2020.00147

McDonald, M. W., Black, S. E., Copland, D. A., Corbett, D., Dijkhuizen, R. M., Farr, T. D., Jeffers, M. S., Kalaria, R. N., Karayanidis, F., Leff, A. P., Nithianantharajah, J., Pendlebury, S., Quinn, T. J., Clarkson, A. N., & O’Sullivan, M. J. (2019). Cognition in stroke rehabilitation and recovery research: Consensus-based core recommendations from the second stroke recovery and rehabilitation roundtable. International Journal of Stroke, 14(8), 774–782. https://doi.org/10.1177/1747493019873600

Merriman, N. A., Sexton, E., McCabe, G., Walsh, M. E., Rohde, D., Gorman, A., Jeffares, I., Donnelly, N.-A., Pender, N., Williams, D. J., Horgan, F., Doyle, F., Wren, M.-A., Bennett, K. E., & Hickey, A. (2019). Addressing cognitive impairment following stroke: Systematic review and meta-analysis of non-randomised controlled studies of psychological interventions. BMJ Open, 9(2), Article e024429. https://doi.org/10.1136/bmjopen-2018-024429

Nguyen, L., Murphy, K., & Andrews, G. (2019). Cognitive and neural plasticity in old age: A systematic review of evidence from executive functions cognitive training. Ageing Research Reviews, 53, Article 100912. https://doi.org/10.1016/j.arr.2019.100912

Ong, P. A., Muis, A., Rambe, A. S., Widjojo, F. S., Laksmidewi, A. A., & Pramono, A. (2015). Panduan praktik klinik: Diagnosis dan penatalaksanaan demensia. Perhimpunan Dokter Spesialis Saraf Indonesia.

Pauwels, L., Chalavi, S., & Swinnen, S. P. (2018). Aging and brain plasticity. Aging, 10(8), 1789–1790. https://doi.org/10.18632/aging.101514

Petrovic, J., Milosevic, V., Zivkovic, M., Stojanov, D., Milojkovic, O., Kalauzi, A., & Saponjic, J. (2017). Slower EEG alpha generation, synchronization and “flow”—possible biomarkers of cognitive impairment and neuropathology of minor stroke. PeerJ, 5, Article e3839. https://doi.org/10.7717/peerj.3839

Pinter, D., Kober, S. E., Fruhwirth, V., Berger, L., Damulina, A., Khalil, M., Neuper, C., Wood, G., & Enzinger, C. (2021). MRI correlates of cognitive improvement after home-based EEG neurofeedback training in patients with multiple sclerosis: A pilot study. Journal of Neurology, 268(10), 3808–3816. https://doi.org/10.1007/s00415-021-10530-9

Rance, M., Walsh, C., Sukhodolsky, D. G., Pittman, B., Qiu, M., Kichuk, S. A., Wasylink, S., Koller, W. N., Bloch, M., Gruner, P., Scheinost, D., Pittenger, C., & Hampson, M. (2018). Time course of clinical change following neurofeedback. NeuroImage, 181, 807–813. https://doi.org/10.1016/j.neuroimage.2018.05.001

Surmeli, T., Eralp, E., Mustafazade, I., Kos, H., Özer, G. E., & Surmeli, O. H. (2016). Quantitative EEG neurometric analysis–Guided neurofeedback treatment in dementia. Clinical EEG and Neuroscience, 47(2), 118–133. https://doi.org/10.1177/1550059415590750

Tosti, B., Corrado, S., Mancone, S., Di Libero, T., Rodio, A., Andrade, A., & Diotaiuti, P. (2024). Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: A narrative review. Frontiers in Neuroscience, 18, Article 1358481. https://doi.org/10.3389/fnins.2024.1358481

Trambaiolli, L. R., Cassani, R., Mehler, D. M. A., & Falk, T. H. (2021). Neurofeedback and the aging brain: A systematic review of training protocols for dementia and mild cognitive impairment. Frontiers in Aging Neuroscience, 13, Article 682683. https://doi.org/10.3389/fnagi.2021.682683

Tugasworo, D., Agung, L., Retnaningsih, R., Husni, A., Bintoro, A. C., & Wati, A. P. (2023). The correlation of glial fibrillary acid protein level to cognitive function outcome in acute lacunar ischemic stroke patient. Open Access Macedonian Journal of Medical Sciences, 11(B), 330–334. https://doi.org/10.3889/oamjms.2023.11393

Vilou, I., Varka, A., Parisis, D., Afrantou, T., & Ioannidis, P. (2023). EEG-neurofeedback as a potential therapeutic approach for cognitive deficits in patients with dementia, multiple sclerosis, stroke and traumatic brain injury. Life, 13(2), 365. https://doi.org/10.3390/life13020365

Weber, L. A., Ethofer, T., & Ehlis, A.-C. (2020). Predictors of neurofeedback training outcome: A systematic review. NeuroImage: Clinical, 27, Article 102301. https://doi.org/10.1016/j.nicl.2020.102301

Wigton, N., & Krigbaum, G. (2015). A review of qEEG-guided neurofeedback. NeuroRegulation, 2(3), 149–155. https://doi.org/10.15540/nr.2.3.149

Zhou, W., Nan, W., Xiong, K., & Ku, Y. (2024). Alpha neurofeedback training improves visual working memory in healthy individuals. Npj Science of Learning, 9(1), Article 32. https://doi.org/10.1038/s41539-024-00242-w

Zuo, L., Dong, Y., Liao, X., Pan, Y., Xiang, X., Meng, X., Li, H., Zhao, X., Wang, Y., Shi, J., & Wang, Y. (2022). Risk factors for decline in Montreal Cognitive Assessment (MoCA) scores in patients with acute transient ischemic attack and minor stroke. The Journal of Clinical Hypertension, 24(7), 851–857. https://doi.org/10.1111/jch.14453

Downloads

Published

2026-03-31

Issue

Section

Research Papers