Skip to main content Skip to main navigation menu Skip to site footer
Articles
Published: 2024-09-05

Effectiveness of neurofeedback-based cognitive training in older adults

Department of Psyhology, Kazimierz Wielki University, Bydgoszcz, Poland
Department of Psyhology, Kazimierz Wielki University, Bydgoszcz, Poland
Department of Psyhology, Kazimierz Wielki University, Bydgoszcz, Poland
Department of Psyhology, Kazimierz Wielki University, Bydgoszcz, Poland
Faculty of Medicine, Andrzej Frycz Modrzewski Krakow University, Kraków, Poland
neurofeedback mild cognitive impairment mild dementia cognitive training

Abstract

The increasing aging of the global population requires strategies that address age-related cognitive decline. This study investigated the impact of neurofeedback (NF) training on cognitive performance in healthy older adults, those with mild cognitive impairments (MCI), and those with mild dementia (MD). Participants engaged in bi-weekly NeuroPlay training over 4 weeks, targeting theta/alpha brainwave frequencies. The results revealed intriguing distinctions: ACE-III scores significantly improved in the MCI (p < 0.001) and MD (p =0.004) groups, signifying robust enhancements in attention, memory, and language. MCI participants displayed notable gains in digit span tests (p =0.014) and participants’ Continuous Performance Task results indicated fewer errors (p =0.003). Meanwhile, reaction times in the Simple Reaction Time task increased (p =0.047) for healthy participants. These findings underscore NF's potential to enhance cognitive functions, particularly in attention-related tasks, suggesting its efficacy as an intervention tool for age-related cognitive decline.

Metrics

Metrics Loading ...

References

  1. Angelakis, E., Stathopoulou, S., Frymiare, J. L., Green, D. L., Lubar, J. F., & Kounios, J. (2007). EEG neurofeedback: A brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Clinical Neuropsychologist, 21(1), 110–129. https://doi.org/10.1080/13854040600744839 DOI: https://doi.org/10.1080/13854040600744839
  2. Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biological Psychology, 95(1), 108–115. https://doi.org/10.1016/j.biopsycho.2013.11.013 DOI: https://doi.org/10.1016/j.biopsycho.2013.11.013
  3. Bárrios, H., Narciso, S., Guerreiro, M., Maroco, J., Logsdon, R., & de Mendonça, A. (2013). Quality of life in patients with mild cognitive impairment. Aging & Mental Health, 17(3), 287–292. https://doi.org/10.1080/13607863.2012.747083 DOI: https://doi.org/10.1080/13607863.2012.747083
  4. Bauer, R. H. (1976). Short-term memory: EEG alpha correlates and the effect of increased alpha. Behavioral Biology, 17(4), 425–433. https://doi.org/10.1016/S0091-6773(76)90793-8 DOI: https://doi.org/10.1016/S0091-6773(76)90793-8
  5. Becerraa, J., Fernandez, T., Roca-Stappunga, M., D´ıaz-Comasb, L., Diaz-Comas, L., Galan, L., Bosch, J., Espino, M., Moreno, A. J., & Harmony, T. (2011). Neurofeedback in Healthy Elderly Human Subjects with Electroencephalographic Risk for Cognitive Disorder. Journal of Alzheimer’s Disease, 28, 1–11. https://doi.org/10.3233/JAD-2011-111055 DOI: https://doi.org/10.3233/JAD-2011-111055
  6. Brito, M. A. de, Fernandes, J. R., Esteves, N. S. A., Müller, V. T., Alexandria, D. B., Pérez, D. I. V., Slimani, M., Brito, C. J., Bragazzi, N. L., & Miarka, B. (2022). The Effect of Neurofeedback on the Reaction Time and Cognitive Performance of Athletes: A Systematic Review and Meta-Analysis. Frontiers in Human Neuroscience, 16(June). https://doi.org/10.3389/fnhum.2022.868450 DOI: https://doi.org/10.3389/fnhum.2022.868450
  7. Cho, B.-H., Kim, S., Shin, D. I., Lee, J. H., Min Lee, S., Young Kim, I., & Kim, S. I. (2004). Neurofeedback Training with Virtual Reality for Inattention and Impulsiveness. CyberPsychology & Behavior, 7(5), 519–526. https://doi.org/10.1089/cpb.2004.7.519 DOI: https://doi.org/10.1089/cpb.2004.7.519
  8. Compos da Paz, V. K., Garcia, A., Campos da Paz Neto, A., & Tomaz, C. (2018). SMR Neurofeedback Training Facilitates Working Memory Performance in Healthy Older Adults: A Behavioral and EEG Study. 12(December), 1–11. https://doi.org/10.3389/fnbeh.2018.00321 DOI: https://doi.org/10.3389/fnbeh.2018.00321
  9. Dodge, H. H., Zhu, J., Mattek, N. C., Bowman, M., Ybarra, O., Wild, K. V., Loewenstein, D. A., & Kaye, J. A. (2015). Web-enabled conversational interactions as a method to improve cognitive functions: Results of a 6-week randomized controlled trial. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 1(1), 1–12. https://doi.org/10.1016/j.trci.2015.01.001 DOI: https://doi.org/10.1016/j.trci.2015.01.001
  10. De, A., & Mondal, S. (2020). Yoga and brain wave coherence: A systematic review for brain function improvement. Heart and Mind, 4(2), 33-39. https://doi.org/10.4103/hm.hm_78_19 DOI: https://doi.org/10.4103/hm.hm_78_19
  11. Egner, T., & Gruzelier, J. H. (2004). EEG biofeedback of low beta band components: Frequency-specific effects on variables of attention and event-related brain potentials. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 115(1), 131–139. https://doi.org/10.1016/s1388-2457(03)00353-5 DOI: https://doi.org/10.1016/S1388-2457(03)00353-5
  12. Foster, J. J., Bsales, E. M., Jaffe, R. J., & Awh, E. (2017). Alpha-Band Activity Reveals Spontaneous Representations of Spatial Position in Visual Working Memory. Current Biology, 27(20), 3216-3223.e6. https://doi.org/10.1016/j.cub.2017.09.031 DOI: https://doi.org/10.1016/j.cub.2017.09.031
  13. Freak-Poli, R., Ryan, J., Neumann, J. T., Tonkin, A., Reid, C. M., Woods, R. L., Nelson, M., Stocks, N., Berk, M., McNeil, J. J., Britt, C., & Owen, A. J. (2021). Social isolation, social support and loneliness as predictors of cardiovascular disease incidence and mortality. BMC Geriatrics, 21(1), 711. https://doi.org/10.1186/s12877-021-02602-2 DOI: https://doi.org/10.1186/s12877-021-02602-2
  14. Gajewski, P. D., & Falkenstein, M. (2014). Age-related effects on ERP and oscillatory EEG-dynamics in a 2-back task. Journal of Psychophysiology, 28(3), 162–177. https://doi.org/10.1027/0269-8803/a000123 DOI: https://doi.org/10.1027/0269-8803/a000123
  15. Gevensleben, H., Holl, B., Albrecht, B., Vogel, C., Schlamp, D., Kratz, O., Studer, P., Rothenberger, A., Moll, G. H., & Heinrich, H. (2009). Is neurofeedback an efficacious treatment for ADHD? A randomised controlled clinical trial. Journal of Child Psychology and Psychiatry and Allied Disciplines, 50(7), 780–789. https://doi.org/10.1111/j.1469-7610.2008.02033.x DOI: https://doi.org/10.1111/j.1469-7610.2008.02033.x
  16. Gomez-Pilar, J., Corralejo, R., Luis, L., & Hornero, R. (2016). Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly. Medical & Biological Engineering & Computing, 54(11). https://doi.org/10.1007/s11517-016-1454-4 DOI: https://doi.org/10.1007/s11517-016-1454-4
  17. Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Reviews, 44, 124–141. https://doi.org/10.1016/j.neubiorev.2013.09.015 DOI: https://doi.org/10.1016/j.neubiorev.2013.09.015
  18. Guo, J., Luo, X., Li, B., Chang, Q., Sun, L., & Song, Y. (2020). Abnormal modulation of theta oscillations in children with attention-deficit/hyperactivity disorder. NeuroImage: Clinical, 27, 102314. https://doi.org/10.1016/j.nicl.2020.102314 DOI: https://doi.org/10.1016/j.nicl.2020.102314
  19. Hanslmayr, S., Sauseng, P., Doppelmayr, M., Schabus, M., & Klimesch, W. (2005). Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Applied Psychophysiology Biofeedback, 30(1), 1–10. https://doi.org/10.1007/s10484-005-2169-8 DOI: https://doi.org/10.1007/s10484-005-2169-8
  20. Heinrich, H., Gevensleben, H., Freisleder, F. J., Moll, G. H., & Rothenberger, A. (2004). Training of slow cortical potentials in attention-deficit/hyperactivity disorder: Evidence for positive behavioral and neurophysiological effects. Biological Psychiatry, 55(7), 772–775. https://doi.org/10.1016/j.biopsych.2003.11.013 DOI: https://doi.org/10.1016/j.biopsych.2003.11.013
  21. Hill, N. T. M., Mowszowski, L., Naismith, S. L., Chadwick, V. L., Valenzuela, M., & Lampit, A. (2017). Computerized cognitive training in older adults with mild cognitive impairment or dementia: A systematic review and meta-analysis. American Journal of Psychiatry, 174(4), 329–340. https://doi.org/10.1176/appi.ajp.2016.16030360 DOI: https://doi.org/10.1176/appi.ajp.2016.16030360
  22. Hsueh, J.-J., Chen, T.-S., Chen, J.-J., & Shaw, F.-Z. (2016). Neurofeedback training of EEG alpha rhythm enhances episodic and working memory. Human Brain Mapping, 37(7), 2662–2675. https://doi.org/10.1002/hbm.23201 DOI: https://doi.org/10.1002/hbm.23201
  23. Jiang, Y., Abiri, R., Zhao, X., & Ros, T. (2017). Tuning Up the Old Brain with New Tricks: Attention Training via Neurofeedback. Frontiers in Aging Neuroscience, 9(52), 1–9. https://doi.org/10.3389/fnagi.2017.00052 DOI: https://doi.org/10.3389/fnagi.2017.00052
  24. Kirmizi-Alsan, E., Bayraktaroglu, Z., Gurvit, H., Keskin, Y. H., Emre, M., & Demiralp, T. (2006). Comparative analysis of event-related potentials during Go/NoGo and CPT: Decomposition of electrophysiological markers of response inhibition and sustained attention. Brain Research, 1104(1), 114–128. https://doi.org/10.1016/j.brainres.2006.03.010 DOI: https://doi.org/10.1016/j.brainres.2006.03.010
  25. Kober, S. E., Witte, M., Stangl, M., Väljamäe, A., Neuper, C., & Wood, G. (2015). Shutting down sensorimotor interference unblocks the networks for stimulus processing: An SMR neurofeedback training study. Clinical Neurophysiology, 126, 82–95. https://doi.org/10.1016/j.clinph.2014.03.031 DOI: https://doi.org/10.1016/j.clinph.2014.03.031
  26. Kourtesis, P., Margioti, E., Demenega, C., Christidi, F., & Abrahams, S. (2020). A comparison of the Greek ACE-III, M-ACE, ACE-R, MMSE, and ECAS in the assessment and identification of Alzheimer’s disease. Journal of the International Neuropsychological Society, 26(8), 825–834. https://doi.org/10.1017/S1355617720000314 DOI: https://doi.org/10.1017/S1355617720000314
  27. Kueider, A. M., Parisi, J. M., Gross, A. L., & Rebok, G. W. (2012). Computerized cognitive training with older adults: A systematic review. PLoS ONE, 7(7). https://doi.org/10.1371/journal.pone.0040588 DOI: https://doi.org/10.1371/journal.pone.0040588
  28. Laborda-Sánchez, F., & Cansino, S. (2021). The Effects of Neurofeedback on Aging-Associated Cognitive Decline: A Systematic Review. Applied Psychophysiology Biofeedback, 46(1), 1–10. https://doi.org/10.1007/s10484-020-09497-6 DOI: https://doi.org/10.1007/s10484-020-09497-6
  29. Lampit, A., Hallock, H., & Valenzuela, M. (2014). Computerized Cognitive Training in Cognitively Healthy Older Adults: A Systematic Review and Meta-Analysis of Effect Modifiers. PLoS Medicine, 11(11). https://doi.org/10.1371/journal.pmed.1001756 DOI: https://doi.org/10.1371/journal.pmed.1001756
  30. Lavy, Y., Dwolatzky, T., Kaplan, Z., Guez, J., & Todder, D. (2019). Neurofeedback Improves Memory and Peak Alpha Frequency in Individuals with Mild Cognitive Impairment. Applied Psychophysiology and Biofeedback, 44(1), 41–49. https://doi.org/10.1007/s10484-018-9418-0 DOI: https://doi.org/10.1007/s10484-018-9418-0
  31. Lecomte, G., & Juhel, J. (2011). The Effects of Neurofeedback Training on Memory Performance in Elderly Subjects. Psychology, 02(08), 846–852. https://doi.org/10.4236/psych.2011.28129 DOI: https://doi.org/10.4236/psych.2011.28129
  32. Liu, X. Y., Li, L., Xiao, J. Q., He, C. Z., Lyu, X. L., Gao, L., Yang, X. W., Cui, X. G., & Fan, L. H. (2016). Cognitive Training in Older Adults with Mild Cognitive Impairment. Biomedical and Environmental Sciences, 29(5), 356–364. https://doi.org/10.3967/bes2016.046
  33. Malhotra, P. A. (2019). Impairments of attention in Alzheimer’s disease. Current Opinion in Psychology, 29, 41–48. https://doi.org/10.1016/j.copsyc.2018.11.002 DOI: https://doi.org/10.1016/j.copsyc.2018.11.002
  34. 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(June), 1–11. https://doi.org/10.3389/fnagi.2020.00147 DOI: https://doi.org/10.3389/fnagi.2020.00147
  35. Mirifar, A., Keil, A., & Ehrlenspiel, F. (2022). Neurofeedback and neural self-regulation: A new perspective based on allostasis. Reviews in the Neurosciences, 33(6), 607–629. https://doi.org/10.1515/revneuro-2021-0133 DOI: https://doi.org/10.1515/revneuro-2021-0133
  36. Murman, D. L. (2015). The Impact of Age on Cognition. Seminars in Hearing, 36(3), 111–121. https://doi.org/10.1055/s-0035-1555115 DOI: https://doi.org/10.1055/s-0035-1555115
  37. Podhorecka, M., Szrajber, R., Andrzejczak, J., Lacko, J., & Lipiński, P. (2021). Virtual Reality-Based Cognitive Stimulation Using Grydsen Software As a Means To Prevent Age-Related Cognitive-Mobility Disorders—A Pilot Observational Study. Human Technology, 17(3), 321–335. https://doi.org/10.14254/1795-6889.2021.17-3.7 DOI: https://doi.org/10.14254/1795-6889.2021.17-3.7
  38. Porciatti, V., Fiorentini, A., Morrone, M. C., & Burr, D. C. (1999). The effects of ageing on reaction times to motion onset. Vision Research, 39(12), 2157–2164. https://doi.org/10.1016/S0042-6989(98)00288-0 DOI: https://doi.org/10.1016/S0042-6989(98)00288-0
  39. Reichert, J. L., Kober, S. E., Schweiger, D., Grieshofer, P., Neuper, C., & Wood, G. (2016). Shutting Down Sensorimotor Interferences after Stroke: A Proof-of-Principle SMR Neurofeedback Study. Frontiers in Human Neuroscience, 10(July), 1–14. https://doi.org/10.3389/fnhum.2016.00348 DOI: https://doi.org/10.3389/fnhum.2016.00348
  40. Reis, J., Portugal, A. M., Fernandes, L., Afonso, N., Pereira, M., Sousa, N., & Dias, N. S. (2016). An Alpha and Theta Intensive and Short Neurofeedback Protocol for Healthy Aging Working-Memory Training. Intensive and Short Neurofeedback Protocol, 8, 1–11. https://doi.org/10.3389/fnagi.2016.00157 DOI: https://doi.org/10.3389/fnagi.2016.00157
  41. Stavropoulos, T. G., Papastergiou, A., Mpaltadoros, L., Nikolopoulos, S., & Kompatsiaris, I. (2020). Iot wearable sensors and devices in elderly care: A literature review. Sensors (Switzerland), 20(10). https://doi.org/10.3390/s20102826 DOI: https://doi.org/10.3390/s20102826
  42. Strehl, U., Aggensteiner, P., Wachtlin, D., Brandeis, D., Albrecht, B., Arana, M., Bach, C., Banaschewski, T., Bogen, T., Flaig-Röhr, A., Freitag, C. M., Fuchsenberger, Y., Gest, S., Gevensleben, H., Herde, L., Hohmann, S., Legenbauer, T., Marx, A. M., Millenet, S., … Holtmann, M. (2017). Neurofeedback of slow cortical potentials in children with attention-deficit/hyperactivity disorder: A multicenter randomized trial controlling for unspecific effects. Frontiers in Human Neuroscience, 11(March), 1–15. https://doi.org/10.3389/fnhum.2017.00135 DOI: https://doi.org/10.3389/fnhum.2017.00135
  43. Surmeli, T., Eralp, E., Mustafazade, I., Kos, H., Özer, G. E., & Surmeli, O. H. (2016). Quantitative EEG Neurometric Analysis-Guided Neurofeedback Treatment in Dementia: 20 Cases. How Neurometric Analysis Is Important for the Treatment of Dementia and as a Biomarker? Clinical EEG and Neuroscience, 47(2), 118–133. https://doi.org/10.1177/1550059415590750 DOI: https://doi.org/10.1177/1550059415590750
  44. 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. https://www.frontiersin.org/articles/10.3389/fnagi.2021.682683 DOI: https://doi.org/10.3389/fnagi.2021.682683
  45. Trammell, J. P., MacRae, P. G., Davis, G., Bergstedt, D., & Anderson, A. E. (2017). The Relationship of Cognitive Performance and the Theta-Alpha Power Ratio Is Age-Dependent: An EEG Study of Short Term Memory and Reasoning during Task and Resting-State in Healthy Young and Old Adults. Frontiers in Aging Neuroscience, 9. https://www.frontiersin.org/articles/10.3389/fnagi.2017.00364 DOI: https://doi.org/10.3389/fnagi.2017.00364
  46. United Nations Department of Economic and Social Affairs Population Division. (2022). World Population Prospects 2022: Summary of Results. In UN DESA/POP/2022/TR/NO. 3.
  47. Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., & Gruzelier, J. (2003). The effect of training distinct neurofeedback protocols on aspects of cognitive performance. International Journal of Psychophysiology, 47, 75–85. https://doi.org/10.9738/INTSURG-D-15-00067.1 DOI: https://doi.org/10.1016/S0167-8760(02)00091-0
  48. Wojciechowski, A., Pyszora, A., Wiśniewska, A., Liberacka-Dwojak, M., & Juszczyk, K. (2021). Virtual Reality Immersive Environments for Motor and Cognitive Training of Elderly People—A Scoping Review. Human Technology, 17(2), 145–163. https://doi.org/10.14254/1795-6889.2021.17-2.4
  49. Woodruff, D. S. (1975). Relationships Among EEG Alpha Frequency, Reaction Time, and Age: A Biofeedback Study. Psychophysiology, 12(6), 673–681. https://doi.org/10.1111/j.1469-8986.1975.tb00073.x DOI: https://doi.org/10.1111/j.1469-8986.1975.tb00073.x
  50. Zając-Lamparska, L., Wiłkość-Dȩbczyńska, M., Wojciechowski, A., Podhorecka, M., Polak-Szabela, A., Warchoł, Ł., Kȩdziora-Kornatowska, K., Araszkiewicz, A., & Izdebski, P. (2019). Effects of virtual reality-based cognitive training in older adults living without and with mild dementia: A pretest-posttest design pilot study. BMC Research Notes, 12(1), 1–8. https://doi.org/10.1186/s13104-019-4810-2 DOI: https://doi.org/10.1186/s13104-019-4810-2

How to Cite

Wiłkość-Dębczyńska, M., Zając-Lamparska, L., Liberacka-Dwojak, M., Kukuła, D., & Werońska, A. (2024). Effectiveness of neurofeedback-based cognitive training in older adults. Human Technology, 20(2), 384–398. https://doi.org/10.14254/1795-6889.2024.20-2.7