Roadmap for Enhancing the Efficiency of Neurofeedback

Authors

DOI:

https://doi.org/10.15540/nr.12.2.112

Keywords:

neurofeedback technology, electroencephalography, individual alpha peak frequency, neuronal activation, feedback presentation

Abstract

This article presents a roadmap of ways to improve the effectiveness of EEG neurofeedback training (NFT) based on a literature review and our own research on internal and external factors affecting NFT outcomes. Here we provide a justification for the expediency of using individually determined EEG indices as a feedback signal, based on an analysis of the alpha peak frequency and the level of neuronal activation. As personalization of the NFT for self-regulation means receiving information from a unique neurophysiological parameter inherent only to this individual, the basic internal socioeconomic, psychological, and physiological factors play an important role in training efficiency. Also, external factors such as the delay and modality of feedback presentation, valence of reinforcement, electrode localization, visual condition, body position, duration, and number of NFT sessions, forehead muscle tension and EMG artifact contamination will be discussed. A rationale for each step of this roadmap will be given from the point of view of how this or that factor can influence the personalization and consequently, the effectiveness of self-regulation training with NFT. The article provides a forward-looking opportunity to optimize NFT, providing a sketch setting out the necessary steps.

References

Acharya, J. N., & Acharya, V. J. (2019). Overview of EEG montages and principles of localization. Journal of Clinical Neurophysiology, 36(5), 325–329. https://doi.org/10.1097/WNP.0000000000000538

Alexeeva, M. V., Balios, N. V., Muravlyova, K. B., Sapina, E. V., & Bazanova, O. M. (2012). Training for voluntarily increasing individual upper α power as a method for cognitive enhancement. Human Physiology, 38(1), 40–48. https://doi.org/10.1134/S0362119711060028

Alkoby, O., Abu-Rmileh, A., Shriki, O., & Todder, D. (2018). Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience, 378, 155–164. https://doi.org/10.1016/j.neuroscience.2016.12.050

Ancoli, S., & Green, K. F. (1977). Authoritarianism, introspection, and alpha wave biofeedback training. Psychophysiology, 14(1), 40–44. https://doi.org/10.1111/j.1469-8986.1977.tb01152.x

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. The Clinical Neuropsychologist, 21(1), 110–129. https://doi.org/10.1080/13854040600744839

Arnold, L. G., & Debeus, R. (2024). Double-blind 2-site randomized clinical trial of neurofeedback for ADHD (Version v1) [Data set]. ICPSR - Interuniversity Consortium for Political and Social Research. https://doi.org/10.3886/E198003V1

Arns, M., Drinkenburg, W., & Leon Kenemans, J. (2012). The effects of QEEG-informed neurofeedback in ADHD: An open-label pilot study. Applied Psychophysiology and Biofeedback, 37(3), 171–180. https://doi.org/10.1007/s10484-012-9191-4

Arns, M., Conners, C. K., & Kraemer, H. C. (2013). A decade of EEG theta/beta ratio research in ADHD: A meta-analysis. Journal of Attention Disorders, 17(5), 374–383. https://doi.org/10.1177/1087054712460087

Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biological Psychology, 95, 108–115. https://doi.org/10.1016/j.biopsycho.2013.11.013

Arza, A., Garzón-Rey, J. M., Lázaro, J., Gil, E., Lopez-Anton, R., de la Camara, C., Laguna, P., Bailon, R., & Aguiló, J. (2019). Measuring acute stress response through physiological signals: Towards a quantitative assessment of stress. Medical & Biological Engineering & Computing, 57(1), 271–287. https://doi.org/10.1007/s11517-018-1879-z

Askovic, M., Soh, N., Elhindi, J., & Harris, A. W. F. (2023). Neurofeedback for post-traumatic stress disorder: Systematic review and meta-analysis of clinical and neurophysiological outcomes. European Journal of Psychotraumatology, 14(2), Article 2257435. https://doi.org/10.1080/20008066.2023.2257435

Azzalini, D., Rebollo, I., & Tallon-Baudry, C. (2019). Visceral signals shape brain dynamics and cognition. Trends in Cognitive Sciences, 23(6), 488–509. https://doi.org/10.1016/j.tics.2019.03.007

Babiloni, C., Del Percio, C., Arendt-Nielsen, L., Soricelli, A., Romani, G. L., Rossini, P. M., & Capotosto, P. (2014). Cortical EEG alpha rhythms reflect task-specific somatosensory and motor interactions in humans. Clinical Neurophysiology, 125(10), 1936–1945. https://doi.org/10.1016/j.clinph.2014.04.021

Babiloni, C., Miniussi, C., Babiloni, F., Carducci, F., Cincotti, F., Del Percio, C., Sirello, G., Fracassi, C., Nobre, A. C., & Rossini, P. M. (2004). Sub-second “temporal attention” modulates alpha rhythms. A high-resolution EEG study. Cognitive Brain Research, 19(3), 259–268. https://doi.org/10.1016/j.cogbrainres.2003.12.010

Baghdadi, G., Soroush, A., Towhidkhah, F., & Rostami, R. (2020). Using the concepts of time-delayed feedback control in biofeedback systems in children with ADD: A preliminary study. Communications in Nonlinear Science and Numerical Simulation, 85, Article 105235. https://doi.org/10.1016/j.cnsns.2020.105235

Banoczi, W. R. (2005). How some drugs affect the electroencephalogram (EEG). American Journal of Electroneurodiagnostic Technology, 45(2), 118–129. https://doi.org/10.1080/1086508X.2005.11079518

Barry, R. J., Clarke, A. R., & Johnstone, S. J. (2011). Caffeine and opening the eyes have additive effects on resting arousal measures. Clinical Neurophysiology, 122(10), 2010–2015. https://doi.org/10.1016/j.clinph.2011.02.036

Barry, R. J., & De Blasio, F. M. (2017). EEG differences between eyes-closed and eyes-open resting remain in healthy ageing. Biological Psychology, 129, 293–304. https://doi.org/10.1016/j.biopsycho.2017.09.010

Bazanova, O. M. (2011). [Individual alpha peak frequency variability and reproducibility in various experimental conditions]. Zhurnal Vysshei Nervnoi Deiatelnosti Imeni I P Pavlova, 61(1), 102–111.

Bazanova, O. M. (2012). Alpha EEG activity depends on the individual dominant rhythm frequency. Journal of Neurotherapy, 16(4), 270–284. https://doi.org/10.1080/10874208.2012.730786

Bazanova, O. M., & Aftanas, L. I. (2010). Individual EEG alpha activity analysis for enhancement neurofeedback efficiency: Two case studies. Journal of Neurotherapy, 14(3), 244–253. https://doi.org/10.1080/10874208.2010.501517

Bazanova, O. M., Auer, T., & Sapina, E. A. (2018). On the efficiency of individualized theta/beta ratio neurofeedback combined with forehead emg training in ADHD children. Frontiers in Human Neuroscience, 12, Article 3. https://doi.org/10.3389/fnhum.2018.00003

Bazanova, O. M., Kholodina, N. V., Nikolenko, E. D., & Payet, J. (2017). Training of support afferentation in postmenopausal women. International Journal of Psychophysiology, 122, 65–74. https://doi.org/10.1016/j.ijpsycho.2017.05.002

Bazanova, O. M., Nikolenko, E. D., & Barry, R. J. (2017). Reactivity of alpha rhythms to eyes opening (the Berger effect) during menstrual cycle phases. International Journal of Psychophysiology, 122, 56–64. https://doi.org/10.1016/j.ijpsycho.2017.05.001

Bazanova, O. M., & Vernon, D. (2014). Interpreting EEG alpha activity. Neuroscience & Biobehavioral Reviews, 44, 94–110. https://doi.org/10.1016/j.neubiorev.2013.05.007

Bazanova, O. M., Vernon, D., Lazareva, O. Yu., Muravlyova, K. B., & Skoraya, M. V. (2013). Influence of biofeedback and self-regulation psychotechniques on the cognitive functions and alpha activity EEG. Bulletin of Siberian Medicine, 12(2), 36–42. https://doi.org/10.20538/1682-0363-2013-2-36-42

Becker, D., Creutzfeldt, O. D., Schwibbe, M., & Wuttke, W. (1982). Changes in physiological, EEG and psychological parameters in women during the spontaneous menstrual cycle and following oral contraceptives. Psychoneuroendocrinology, 7(1), 75–90. https://doi.org/10.1016/0306-4530(82)90057-9

Bernstein, N. A. (1945). [Current problems of neurophysiology]. Fiziologicheskii Zhurnal SSSR Imeni I. M. Sechenova, 31(5–6), 298–311.

Birbaumer, N. (2024). “Your thoughts are (were) free!“: Brain-computer-interfaces, neurofeedback, detection of deception, and the future of mind-reading. Applied Psychophysiology and Biofeedback. https://doi.org/10.1007/s10484-024-09648-z

Blumenstein, B., & Orbach, I. (2014). Biofeedback for sport and performance enhancement. In Oxford Handbooks Editorial Board (Ed.), Oxford handbook topics in psychology (1st ed.). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199935291.013.001

Boynton, T. (2001). Applied research using alpha/theta training for enhancing creativity and well-being. Journal of Neurotherapy, 5(1–2), 5–18. https://doi.org/10.1300/J184v05n01_02

Brötzner, C. P., Klimesch, W., Doppelmayr, M., Zauner, A., & Kerschbaum, H. H. (2014). Resting state alpha frequency is associated with menstrual cycle phase, estradiol and use of oral contraceptives. Brain Research, 1577, 36–44. https://doi.org/10.1016/j.brainres.2014.06.034

Brown, P., RELISH Consortium, & Zhou, Y. (2019). Large expert-curated database for benchmarking document similarity detection in biomedical literature search. Database, 2019, baz085. https://doi.org/10.1093/database/baz085

Bucho, T., Caetano, G., Vourvopoulos, A., Accoto, F., Esteves, I., I Badia, S. B., Rosa, A., & Figueiredo, P. (2019). Comparison of visual and auditory modalities for upper-alpha EEG-neurofeedback. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5960–5966). Berlin, Germany. https://doi.org/10.1109/EMBC.2019.8856671

Cacioppo, J. T. (2004). Feelings and emotions: Roles for electrophysiological markers. Biological Psychology, 67(1–2), 235–243. https://doi.org/10.1016/j.biopsycho.2004.03.009

Castermans, T., Duvinage, M., Cheron, G., & Dutoit, T. (2014). About the cortical origin of the low-delta and high-gamma rhythms observed in EEG signals during treadmill walking. Neuroscience Letters, 561, 166–170. https://doi.org/10.1016/j.neulet.2013.12.059

Chang, L.-J., Lin, J.-F., Lin, C.-F., Wu, K.-T., Wang, Y.-M., & Kuo, C.-D. (2011). Effect of body position on bilateral EEG alterations and their relationship with autonomic nervous modulation in normal subjects. Neuroscience Letters, 490(2), 96–100. https://doi.org/10.1016/j.neulet.2010.12.034

Chernyshev, B. V., Osokina, Ye. S., Ilyushina, N. V., Trunova, M. S., & Chernysheva, Ye. G. (2013). The dependence of the success rate of alpha-training on extraversion and neuroticism. Bulletin of Siberian Medicine, 12(2), 72–79. https://doi.org/10.20538/1682-0363-2013-2-72-79

Chikhi, S., Matton, N., Sanna, M., & Blanchet, S. (2023). Mental strategies and resting state EEG: Effect on high alpha amplitude modulation by neurofeedback in healthy young adults. Biological Psychology, 178, Article 108521. https://doi.org/10.1016/j.biopsycho.2023.108521

Choi, Y.-J., Choi, E.-J., & Ko, E. (2023). Neurofeedback effect on symptoms of posttraumatic stress disorder: A systematic review and meta-analysis. Applied Psychophysiology and Biofeedback, 48(3), 259–274. https://doi.org/10.1007/s10484-023-09593-3

Clark, M., Euler, M. J., King, B. R., Williams, A. M., & Lohse, K. R. (2024). Associations between age-related differences in occipital alpha power and the broadband parameters of the EEG power spectrum: A cross-sectional cohort study. International Journal of Psychophysiology, 195, Article 112272. https://doi.org/10.1016/j.ijpsycho.2023.112272

Collura, T. F. (2010). Conclusion: QEEG-guided neurofeedback in context and in practice. Applied Psychophysiology and Biofeedback, 35(1), 37–38. https://doi.org/10.1007/s10484-009-9108-z

Compton, R. J., Gearinger, D., & Wild, H. (2019). The wandering mind oscillates: EEG alpha power is enhanced during moments of mind-wandering. Cognitive, Affective, & Behavioral Neuroscience, 19(5), 1184–1191. https://doi.org/10.3758/s13415-019-00745-9

Cowley, B., Holmström, É., Juurmaa, K., Kovarskis, L., & Krause, C. M. (2016). Computer enabled neuroplasticity treatment: A clinical trial of a novel design for neurofeedback therapy in adult ADHD. Frontiers in Human Neuroscience, 10, Article 205. https://doi.org/10.3389/fnhum.2016.00205

Crivelli, D., Fronda, G., & Balconi, M. (2019). Neurocognitive enhancement effects of combined mindfulness–Neurofeedback training in sport. Neuroscience, 412, 83–93. https://doi.org/10.1016/j.neuroscience.2019.05.066

D’Angiulli, A., Herdman, A., Stapells, D., & Hertzman, C. (2008). Children’s event-related potentials of auditory selective attention vary with their socioeconomic status. Neuropsychology, 22(3), 293–300. https://doi.org/10.1037/0894-4105.22.3.293

DeGood, D. E., & Redgate, E. S. (1982). Interrelationship of plasma cortisol and other activation indices during EMG biofeedback training. Journal of Behavioral Medicine, 5(2), 213–223. https://doi.org/10.1007/BF00844810

Dessy, E., Mairesse, O., van Puyvelde, M., Cortoos, A., Neyt, X., & Pattyn, N. (2020). Train your brain? Can we really selectively train specific EEG frequencies with neurofeedback training. Frontiers in Human Neuroscience, 14, Article 22. https://doi.org/10.3389/fnhum.2020.00022

Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64(1), 135–168. https://doi.org/10.1146/annurev-psych-113011-143750

Diamond, A., & Ling, D. S. (2016). Conclusions about interventions, programs, and approaches for improving executive functions that appear justified and those that, despite much hype, do not. Developmental Cognitive Neuroscience, 18, 34–48. https://doi.org/10.1016/j.dcn.2015.11.005

Dias, Á. M., Van Deusen, A. M., Oda, E., & Bonfim, M. R. (2012). Clinical efficacy of a new automated hemoencefalographic neurofeedback protocol. The Spanish Journal of Psychology, 15(3), 930–941. https://doi.org/10.5209/rev_SJOP.2012.v15.n3.39385

Dijk, D.-J., & Duffy, J. F. (2020). Novel approaches for assessing circadian rhythmicity in humans: A review. Journal of Biological Rhythms, 35(5), 421–438. https://doi.org/10.1177/0748730420940483

Domingos, C., Peralta, M., Prazeres, P., Nan, W., Rosa, A., & Pereira, J. G. (2021). Session frequency matters in neurofeedback training of athletes. Applied Psychophysiology and Biofeedback, 46(2), 195–204. https://doi.org/10.1007/s10484-021-09505-3

Doppelmayr, M., Klimesch, W., Pachinger, T., & Ripper, B. (1998). Individual differences in brain dynamics: Important implications for the calculation of event-related band power. Biological Cybernetics, 79(1), 49–57. https://doi.org/10.1007/s004220050457

Doppelmayr, M., Klimesch, W., Stadler, W., Pöllhuber, D., & Heine, C. (2002). EEG alpha power and intelligence. Intelligence, 30(3), 289–302. https://doi.org/10.1016/S0160-2896(01)00101-5

Duffy, F. H., Albert, M. S., McAnulty, G., & Garvey, A. J. (1984). Age‐related differences in brain electrical activity of healthy subjects. Annals of Neurology, 16(4), 430–438. https://doi.org/10.1002/ana.410160403

Ebrahimzadeh, E., Saharkhiz, S., Rajabion, L., Oskouei, H. B., Seraji, M., Fayaz, F., Saliminia, S., Sadjadi, S. M., & Soltanian-Zadeh, H. (2022). Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function. Frontiers in Systems Neuroscience, 16, Article 934266. https://doi.org/10.3389/fnsys.2022.934266

Edgar, J. C., Berman, J. I., Liu, S., Chen, Y.-H., Huang, M., Brodkin, E. S., Roberts, T. P. L., & Bloy, L. (2022). Two mechanisms facilitate regional independence between brain regions based on an examination of alpha-band activity in healthy control adult males. International Journal of Psychophysiology, 178, 51–59. https://doi.org/10.1016/j.ijpsycho.2022.06.007

Enders, H., & Nigg, B. M. (2016). Measuring human locomotor control using EMG and EEG: Current knowledge, limitations and future considerations. European Journal of Sport Science, 16(4), 416–426. https://doi.org/10.1080/17461391.2015.1068869

Endsley, M. R. (1988). Design and evaluation for situation awareness enhancement. Proceedings of the Human Factors Society Annual Meeting, 32(2), 97–101. https://doi.org/10.1177/154193128803200221

Endsley, M. R. (2013). Situation awareness. In J. D. Lee, & A. Kirlik (Eds.), The Oxford handbook of cognitive engineering (pp. 88–108). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199757183.001.0001

Enz, N., Schmidt, J., Nolan, K., Mitchell, M., Alvarez Gomez, S., Alkayyali, M., Cambay, P., Gippert, M., Whelan, R., & Ruddy, K. (2022). Self‐regulation of the brain’s right frontal Beta rhythm using a brain‐computer interface. Psychophysiology, 59(11), Article e14115. https://doi.org/10.1111/psyp.14115

Escolano, C., Navarro-Gil, M., Garcia-Campayo, J., Congedo, M., & Minguez, J. (2014). The effects of individual upper alpha neurofeedback in ADHD: An open-label pilot study. Applied Psychophysiology and Biofeedback, 39(3–4), 193–202. https://doi.org/10.1007/s10484-014-9257-6

Escolano, C., Olivan, B., Lopez-del-Hoyo, Y., Garcia-Campayo, J., & Minguez, J. (2012). Double-blind single-session neurofeedback training in upper-alpha for cognitive enhancement of healthy subjects. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 4643–4647. San Diego, CA: IEEE. https://doi.org/10.1109/EMBC.2012.6347002

Fede, S. J., Dean, S. F., Manuweera, T., & Momenan, R. (2020). A guide to literature informed decisions in the design of real time fMRI neurofeedback studies: A systematic review. Frontiers in Human Neuroscience, 14, Article 60. https://doi.org/10.3389/fnhum.2020.00060

Festa, E. K., Bracken, B. K., Desrochers, P. C., Winder, A. T., Strong, P. K., & Endsley, M. R. (2024). EEG and fNIRS are associated with situation awareness (hazard) prediction during a driving task. Ergonomics, 67(12), 1993–2008. https://doi.org/10.1080/00140139.2024.2367163

Flouri, E., Midouhas, E., & Joshi, H. (2014). Family poverty and trajectories of children’s emotional and behavioural problems: The moderating roles of self-regulation and verbal cognitive ability. Journal of Abnormal Child Psychology, 42(6), 1043–1056. https://doi.org/10.1007/s10802-013-9848-3

Fontanari, J. F. (2017). Awareness improves problem-solving performance. Cognitive Systems Research, 45, 52–58. https://doi.org/10.1016/j.cogsys.2017.05.003

Fyfe, E. R., DeCaro, M. S., & Rittle-Johnson, B. (2015). When feedback is cognitively-demanding: The importance of working memory capacity. Instructional Science, 43(1), 73–91. https://doi.org/10.1007/s11251-014-9323-8

Gertz, J., & Lavie, P. (1983). Biological rhythms in arousal indices: A potential confounding effect in EEG biofeedback. Psychophysiology, 20(6), 690–695. https://doi.org/10.1111/j.1469-8986.1983.tb00940.x

Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvestre, M., Reyburn, G., Gilbert, G., Lévesque, J., & Beauregard, M. (2013). Neurofeedback training induces changes in white and gray matter. Clinical EEG and Neuroscience, 44(4), 265–272. https://doi.org/10.1177/1550059413476031

Golonka, K., Gawlowska, M., Mojsa-Kaja, J., & Marek, T. (2019). Psychophysiological characteristics of burnout syndrome: Resting-state EEG analysis. BioMed Research International, 2019(1), Article 3764354. https://doi.org/10.1155/2019/3764354

Goncharova, I. I., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2003). EMG contamination of EEG: Spectral and topographical characteristics. Clinical Neurophysiology, 114(9), 1580–1593. https://doi.org/10.1016/S1388-2457(03)00093-2

Gong, A., Gu, F., Nan, W., Qu, Y., Jiang, C., & Fu, Y. (2021). A review of neurofeedback training for improving sport performance from the perspective of user experience. Frontiers in Neuroscience, 15, Article 638369. https://doi.org/10.3389/fnins.2021.638369

Gorev, A. S., & Semenova, O. A. (2003). Effect of individual features of the CNS on efficiency of relaxation biofeedback training in 9- to 10-year-old children. Human Physiology, 29(4), 437–443. https://doi.org/10.1023/A:1024925422758

Grosselin, F., Breton, A., Yahia-Cherif, L., Wang, X., Spinelli, G., Hugueville, L., Fossati, P., Attal, Y., Navarro-Sune, X., Chavez, M., & George, N. (2021). Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: A double-blind randomized study. Scientific Reports, 11(1), Article 18489. https://doi.org/10.1038/s41598-021-96893-5

Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. III: A review of methodological and theoretical considerations. Neuroscience & Biobehavioral Reviews, 44, 159–182. https://doi.org/10.1016/j.neubiorev.2014.03.015

Güntensperger, D., Thüring, C., Kleinjung, T., Neff, P., & Meyer, M. (2019). Investigating the efficacy of an individualized alpha/delta neurofeedback protocol in the treatment of chronic tinnitus. Neural Plasticity, 2019(1), Article 3540898. https://doi.org/10.1155/2019/3540898

Güntensperger, D., Kleinjung, T., Neff, P., Thüring, C., & Meyer, M. (2020). Combining neurofeedback with source estimation: Evaluation of an sLORETA neurofeedback protocol for chronic tinnitus treatment. Restorative Neurology and Neuroscience, 38(4), 283–299. https://doi.org/10.3233/RNN-200992

Gutmann, B., Hülsdünker, T., Mierau, J., Strüder, H. K., & Mierau, A. (2018). Exercise-induced changes in EEG alpha power depend on frequency band definition mode. Neuroscience Letters, 662, 271–275. https://doi.org/10.1016/j.neulet.2017.10.033

Habes, I., Rushton, S., Johnston, S. J., Sokunbi, M. O., Barawi, K., Brosnan, M., Daly, T., Ihssen, N., & Linden, D. E. J. (2016). FMRI neurofeedback of higher visual areas and perceptual biases. Neuropsychologia, 85, 208–215. https://doi.org/10.1016/j.neuropsychologia.2016.03.031

Halliday, D. M., Conway, B. A., Farmer, S. F., & Rosenberg, J. R. (1998). Using electroencephalography to study functional coupling between cortical activity and electromyograms during voluntary contractions in humans. Neuroscience Letters, 241(1), 5–8. https://doi.org/10.1016/S0304-3940(97)00964-6

Hammond, D. C., & Kirk, L. (2008). First, do no harm: Adverse effects and the need for practice standards in neurofeedback. Journal of Neurotherapy, 12(1), 79–88. https://doi.org/10.1080/10874200802219947

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 and Biofeedback, 30(1), 1–10. https://doi.org/10.1007/s10484-005-2169-8

Hardt, J. V., & Kamiya, J. (1976). Some comments on Plotkin’s self-regulation of electroencephalographic alpha. Journal of Experimental Psychology: General, 105(1), 100–108. https://doi.org/10.1037/0096-3445.105.1.100

Hardt, J. V., & Kamiya, J. (1978). Anxiety change through electroencephalographic alpha feedback seen only in high anxiety subjects. Science, 201(4350), 79–81. https://doi.org/10.1126/science.663641

Harris, A., Melkonian, D., Williams, L., & Gordon, E. (2006). Dynamic spectral analysis findings in first episode and chronic schizophrenia. International Journal of Neuroscience, 116(3), 223–246. https://doi.org/10.1080/00207450500402977

Himmelmeier, L., & Werheid, K. (2024). Neurofeedback training in children with ADHD: A systematic review of personalization and methodological features facilitating training conditions. Clinical EEG and Neuroscience, 55(6), 625–635. https://doi.org/10.1177/15500594241279580

Ibanez, A., Cetkovich, M., Petroni, A., Urquina, H., Baez, S., Gonzalez-Gadea, M. L., Kamienkowski, J. E., Torralva, T., Torrente, F., Strejilevich, S., Teitelbaum, J., Hurtado, E., Guex, R., Melloni, M., Lischinsky, A., Sigman, M., & Manes, F. (2012). The neural basis of decision-making and reward processing in adults with euthymic bipolar disorder or attention-deficit/hyperactivity disorder (ADHD). PLoS ONE, 7(5), Article e37306. https://doi.org/10.1371/journal.pone.0037306

Jefferson, A. L., Gibbons, L. E., Rentz, D. M., Carvalho, J. O., Manly, J., Bennett, D. A., & Jones, R. N. (2011). A life course model of cognitive activities, socioeconomic status, education, reading ability, and cognition. Journal of the American Geriatrics Society, 59(8), 1403–1411. https://doi.org/10.1111/j.1532-5415.2011.03499.x

Jensen, O., Gelfand, J., Kounios, J., & Lisman, J. E. (2002). Oscillations in the alpha band (9–12 Hz) increase with memory load during retention in a short-term memory task. Cerebral Cortex, 12(8), 877–882. https://doi.org/10.1093/cercor/12.8.877

Jobert, M., Wilson, F. J., Roth, T., Ruigt, G. S. F., Anderer, P., Drinkenburg, W. H. I. M., & The IPEG Pharmaco-EEG Guidelines Committee. (2013). Guidelines for the recording and evaluation of pharmaco-sleep studies in man: The International Pharmaco-EEG Society (IPEG). Neuropsychobiology, 67(3), 127–167. https://doi.org/10.1159/000343449

Kadosh, K. C., & Staunton, G. (2019). A systematic review of the psychological factors that influence neurofeedback learning outcomes. NeuroImage, 185, 545–555. https://doi.org/10.1016/j.neuroimage.2018.10.021

Kaiser, A., Aggensteiner, P. M., Blasco Fontecilla, H., Ros, T., Acquaviva, E., Attal, Y., Banaschewski, T., Baumeister, S., Bousquet, E., Bussalb, A., Delhaye, M., Delorme, R., Drechsler, R., Goujon, A., Häge, A., Mayaud, L., Mechler, K., Menache, C., Revol, O., … Brandeis, D. (2024). Limited usefulness of neurocognitive functioning indices as predictive markers for treatment response to methylphenidate or neurofeedback@home in children and adolescents with ADHD. Frontiers in Psychiatry, 14, Article 1331004. https://doi.org/10.3389/fpsyt.2023.1331004

Kaiser, D. A. (2001). Rethinking standard bands. Journal of Neurotherapy, 5(1–2), 87–96. https://doi.org/10.1300/J184v05n01_08

Kamiya, J. (1969). Operant control of the EEG alpha rhythm and some of its reported effects on consciousness. In C. T. Tart (Ed.), Altered states of consciousness, (pp. 519–529).

Katkin, E. S., & Murray, E. N. (1968). Instrumental conditioning of autonomically mediated behavior: Theoretical and methodological issues. Psychological Bulletin, 70(1), 52–68. https://doi.org/10.1037/h0025925

Katsantonis, I. (2024). Exploring age-related differences in metacognitive self-regulation: The influence of motivational factors in secondary school students. Frontiers in Psychology, 15, Article 1383118. https://doi.org/10.3389/fpsyg.2024.1383118

Kerson, C., deBeus, R., Lightstone, H., Arnold, L. E., Barterian, J., Pan, X., & Monastra, V. J. (2020). EEG theta/beta ratio calculations differ between various EEG neurofeedback and assessment software packages: Clinical interpretation. Clinical EEG and Neuroscience, 51(2), 114–120. https://doi.org/10.1177/1550059419888320

Kettlety, S. A., Finley, J. M., & Leech, K. A. (2024). Visuospatial skills explain differences in the ability to use propulsion biofeedback post-stroke. Journal of Neurologic Physical Therapy, 48(4), 207–216. https://doi.org/10.1097/NPT.0000000000000487

Kirschfeld, K. (2005). The physical basis of alpha waves in the electroencephalogram and the origin of the “Berger effect”? Biological Cybernetics, 92(3), 177–185. https://doi.org/10.1007/s00422-005-0547-1

Klimesch, W., Doppelmayr, M., Pachinger, T., & Russegger, H. (1997). Event-related desynchronization in the alpha band and the processing of semantic information. Cognitive Brain Research, 6(2), 83–94. https://doi.org/10.1016/S0926-6410(97)00018-9

Klimesch, W., Doppelmayr, M., Russegger, H., Pachinger, T., & Schwaiger, J. (1998). Induced alpha band power changes in the human EEG and attention. Neuroscience Letters, 244(2), 73–76. https://doi.org/10.1016/S0304-3940(98)00122-0

Klug, M., & Gramann, K. (2021). Identifying key factors for improving ICA‐based decomposition of EEG data in mobile and stationary experiments. European Journal of Neuroscience, 54(12), 8406–8420. https://doi.org/10.1111/ejn.14992

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

Kohl, S. H., Mehler, D. M. A., Lührs, M., Thibault, R. T., Konrad, K., & Sorger, B. (2020). The potential of functional near-infrared spectroscopy-based neurofeedback-A systematic review and recommendations for best practice. Frontiers in Neuroscience, 14, Article 594. https://doi.org/10.3389/fnins.2020.00594

Konareva, I. N. (2005). Modifications of the EEG frequency pattern in humans related to a single neurofeedback session. Neurophysiology, 37(5–6), 388–395. https://doi.org/10.1007/s11062-006-0015-0

Koukkou, M., Federspiel, A., Bräker, E., Hug, C., Kleinlogel, H., Merlo, M. C. G., & Lehmann, D. (2000). An EEG approach to the neurodevelopmental hypothesis of schizophrenia studying schizophrenics, normal controls and adolescents. Journal of Psychiatric Research, 34(1), 57–73. https://doi.org/10.1016/S0022-3956(99)00040-0

Kozlovskaya, I., Dmitrieva, I., Grigorieva, L., Kirenskaya, A., & Kreidich, Yu. (1988). Gravitational mechanisms in the motor system. studies in real and simulated weightlessness. In V. S. Gurfinkel, M. E. Ioffe, J. Massion, & J. P. Roll (Eds.), Stance and motion (pp. 37–48). Springer US. https://doi.org/10.1007/978-1-4899-0821-6_4

Kozlovskaya, I. B., Sayenko, I. V., Sayenko, D. G., Miller, T. F., Khusnutdinova, D. R., & Melnik, K. A. (2007). Role of support afferentation in control of the tonic muscle activity. Acta Astronautica, 60(4–7), 285–294. https://doi.org/10.1016/j.actaastro.2006.08.010

Kripke, D. F. (1974). Ultradian rhythms in sleep an wakefulness. In E. D. Weitzman (Ed.), Advances in sleep research (pp. 305–325). Illus Spectrum Publications, Inc.

Kvamme, T. L., Sarmanlu, M., & Overgaard, M. (2022). Doubting the double-blind: Introducing a questionnaire for awareness of experimental purposes in neurofeedback studies. Consciousness and Cognition, 104, Article 103381. https://doi.org/10.1016/j.concog.2022.103381

Labrague, L. J., McEnroe-Petitte, D. M., Gloe, D., Thomas, L., Papathanasiou, I. V., & Tsaras, K. (2017). A literature review on stress and coping strategies in nursing students. Journal of Mental Health, 26(5), 471–480. https://doi.org/10.1080/09638237.2016.1244721

Lal, S. K. L., Henderson, R. J., Carter, N., Bath, A., Hart, M. G., Langeluddecke, P., & Hunyor, S. N. (1998). Effect of feedback signal and psychological characteristics on blood pressure self‐manipulation capability. Psychophysiology, 35(4), 405–412. https://doi.org/10.1111/1469-8986.3540405

Lavie, P., & Kripke, D. F. (1981). Ultradian circa hours rhythms: A multioscillatory system. Life Sciences, 29(24), 2445–2450. https://doi.org/10.1016/0024-3205(81)90698-6

Li, K., & Brown, J. D. (2023). Dual-modality haptic feedback improves dexterous task execution with virtual EMG-controlled gripper. IEEE Transactions on Haptics, 16(4), 816–825. https://doi.org/10.1109/TOH.2023.3328256

Linkenkaer-Hansen, K., Nikulin, V. V., Palva, S., Ilmoniemi, R. J., & Palva, J. M. (2004). Prestimulus oscillations enhance psychophysical performance in humans. The Journal of Neuroscience, 24(45), 10186–10190. https://doi.org/10.1523/JNEUROSCI.2584-04.2004

Livanov, M. N. (1984). [Rhythms of the electroencephalogram and their functional significance]. Zhurnal Vysshei Nervnoi Deiatelnosti Imeni I P Pavlova, 34(4), 613–626. https://doi.org/10.1007/bf01149484

Lopes da Silva, F. (2013). EEG and MEG: Relevance to Neuroscience. Neuron, 80(5), 1112–1128. https://doi.org/10.1016/j.neuron.2013.10.017

Markiewcz, R. (2017). The use of EEG biofeedback/neurofeedback in psychiatric rehabilitation. Psychiatria Polska, 51(6), 1095–1106. https://doi.org/10.12740/PP/68919

Markovska-Simoska, S., Pop-Jordanova, N., & Georgiev, D. (2008). Simultaneous EEG and EMG biofeedback for peak performance in musicians. Prilozi, 29(1), 239–252.

Matsunaga, K., & Genda, E. (2005). Biographics Art “I know me”: Image generation aiming at EEG control by biofeedback. Journal of Physiological Anthropology and Applied Human Science, 24(1), 139–142. https://doi.org/10.2114/jpa.24.139

Mckenzie, R. E., Ehrisman, W. J., Montgomery, P. S., & Barnes, R. H. (1974). The treatment of headache by means of electroencephalographic biofeedback. Headache: The Journal of Head and Face Pain, 13(4), 164–172. https://doi.org/10.1111/j.1526-4610.1974.hed1304164.x

Mierau, A., Felsch, M., Hülsdünker, T., Mierau, J., Bullermann, P., Weiß, B., & Strüder, H. K. (2016). The interrelation between sensorimotor abilities, cognitive performance and individual EEG alpha peak frequency in young children. Clinical Neurophysiology, 127(1), 270–276. https://doi.org/10.1016/j.clinph.2015.03.008

Min, B., Park, H., Kim, J. I., Lee, S., Back, S., Lee, E., Oh, S., Yun, J.-Y., Kim, B.-N., Kim, Y., Hwang, J., Lee, S., & Kim, J.-H. (2023). The effectiveness of a neurofeedback-assisted mindfulness training program using a mobile app on stress reduction in employees: Randomized controlled trial. JMIR MHealth and UHealth, 11, Article e42851. https://doi.org/10.2196/42851

Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L. A., & PRISMA-P Group (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), Article 1. https://doi.org/10.1186/2046-4053-4-1

Montgomery, D. D. (2001). Change: Detection and modification . Applied Psychophysiology and Biofeedback, 26(3), 215–226. https://doi.org/10.1023/A:1011350204547

Mouchnino, L., Lhomond, O., Morant, C., & Chavet, P. (2017). Plantar sole unweighting alters the sensory transmission to the cortical areas. Frontiers in Human Neuroscience, 11, Article 220. https://doi.org/10.3389/fnhum.2017.00220

Mullaney, K. M., Carpenter, S. K., Grotenhuis, C., & Burianek, S. (2014). Waiting for feedback helps if you want to know the answer: The role of curiosity in the delay-of-feedback benefit. Memory & Cognition, 42(8), 1273–1284. https://doi.org/10.3758/s13421-014-0441-y

Naas, A., Rodrigues, J., Knirsch, J. P., & Sonderegger, A. (2019). Neurofeedback training with a low-priced EEG device leads to faster alpha enhancement but shows no effect on cognitive performance: A single-blind, sham-feedback study. PLoS ONE, 14(9), Article e0211668. https://doi.org/10.1371/journal.pone.0211668

Nan, W., Rodrigues, J. P., Ma, J., Qu, X., Wan, F., Mak, P. I., Mak, P. U., Vai, M. I., & Rosa, A. (2012). Individual alpha neurofeedback training effect on short term memory. International Journal of Psychophysiology, 86(1), 83–87. https://doi.org/10.1016/j.ijpsycho.2012.07.182

Nan, W., Wan, F., Vai, M. I., & Da Rosa, A. C. (2015). Resting and initial beta amplitudes predict learning ability in beta/theta ratio neurofeedback training in healthy young adults. Frontiers in Human Neuroscience, 9, Article 677. https://doi.org/10.3389/fnhum.2015.00677

Nekrasova, J., Bazanova, O., Shunenkov, D., Kanarskiy, M., Borisov, I., & Luginina, E. (2022). Problem of myogenic contamination in electroencephalography. Human Physiology, 48(4), 470–482. https://doi.org/10.1134/S0362119722040090

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

Orekhova, E., Stroganova, T., Posikera, I., & Elam, M. (2006). EEG theta rhythm in infants and preschool children. Clinical Neurophysiology, 117(5), 1047–1062. https://doi.org/10.1016/j.clinph.2005.12.027

Pan, Z., Zhang, C., Su, W., Qi, X., Feng, X., Gao, L., Xu, X., & Liu, J. (2023). Relationship between individual differences in pain empathy and task- and resting-state EEG. NeuroImage, 284, Article 120452. https://doi.org/10.1016/j.neuroimage.2023.120452

Parsons, B., & Faubert, J. (2021). Enhancing learning in a perceptual-cognitive training paradigm using EEG-neurofeedback. Scientific Reports, 11(1), Article 4061. https://doi.org/10.1038/s41598-021-83456-x

Paul, M., Bellebaum, C., Ghio, M., Suchan, B., & Wolf, O. T. (2020). Stress effects on learning and feedback‐related neural activity depend on feedback delay. Psychophysiology, 57(2), Article e13471. https://doi.org/10.1111/psyp.13471

Pérez-Elvira, R., Oltra-Cucarella, J., Carrobles, J. A., Teodoru, M., Bacila, C., & Neamtu, B. (2021). Individual alpha peak frequency, an important biomarker for live z-score training neurofeedback in adolescents with learning disabilities. Brain Sciences, 11(2), Article 167. https://doi.org/10.3390/brainsci11020167

Pérez‐Medina‐Carballo, R., Kosmadopoulos, A., Moderie, C., Boudreau, P., Robert, M., & Boivin, D. B. (2024). Dampened circadian amplitude of EEG power in women after menopause. Journal of Sleep Research, Article e14219. https://doi.org/10.1111/jsr.14219

Petrenko, T. I., Bazanova, O. M., & Kabardov, M. K. (2019). Prospects for using adaptive biofeedback to train musicians. RUDN Journal of Psychology and Pedagogics, 16(4), 495–516. https://doi.org/10.22363/2313-1683-2019-16-4-495-516

Pigott, H. E., Cannon, R., & Trullinger, M. (2021). The fallacy of sham-controlled neurofeedback trials: A reply to Thibault and colleagues (2018). Journal of Attention Disorders, 25(3), 448–457. https://doi.org/10.1177/1087054718790802

Pinho, A. L., de Manzano, Ö., Fransson, P., Eriksson, H., & Ullén, F. (2014). Connecting to create: Expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. The Journal of Neuroscience, 34(18), 6156–6163. https://doi.org/10.1523/JNEUROSCI.4769-13.2014

Pirini, M., Mancini, M., Farella, E., & Chiari, L. (2011). EEG correlates of postural audio-biofeedback. Human Movement Science, 30(2), 249–261. https://doi.org/10.1016/j.humov.2010.05.016

Pourmohammadi, S., & Maleki, A. (2020). Stress detection using ECG and EMG signals: A comprehensive study. Computer Methods and Programs in Biomedicine, 193, Article 105482. https://doi.org/10.1016/j.cmpb.2020.105482

Prfwett, M. J., & Adams, H. E. (1976). Alpha activity suppression and enhancement as a function of feedback and instructions. Psychophysiology, 13(4), 307–310. https://doi.org/10.1111/j.1469-8986.1976.tb03081.x

Probst, T., & Wist, E. R. (1990). Impairment of auditory processing by simultaneous vestibular stimulation: Psychophysical and electrophysiological data. Behavioural Brain Research, 41(1), 1–9. https://doi.org/10.1016/0166-4328(90)90048-J

Quaedflieg, C. W. E. M., Smulders, F. T. Y., Meyer, T., Peeters, F., Merckelbach, H., & Smeets, T. (2016). The validity of individual frontal alpha asymmetry EEG neurofeedback. Social Cognitive and Affective Neuroscience, 11(1), 33–43. https://doi.org/10.1093/scan/nsv090

Rahman, S., Munam, A. M., Hossain, A., Hossain, A. S. M. D., & Bhuiya, R. A. (2023). Socio-economic factors affecting the academic performance of private university students in Bangladesh: A cross-sectional bivariate and multivariate analysis. SN Social Sciences, 3(2), Article 26. https://doi.org/10.1007/s43545-023-00614-w

Rathee, S., Bhatia, D., Punia, V., & Singh, R. (2020). Peak alpha frequency in relation to cognitive performance. Journal of Neurosciences in Rural Practice, 11(3), 416–419. https://doi.org/10.1055/s-0040-1712585

Reichert, J. L., Kober, S. E., Neuper, C., & Wood, G. (2015). Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm. Clinical Neurophysiology, 126(11), 2068–2077. https://doi.org/10.1016/j.clinph.2014.09.032

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. Frontiers in Aging Neuroscience, 8, Article 157. https://doi.org/10.3389/fnagi.2016.00157

Renton, T., Tibbles, A., & Topolovec-Vranic, J. (2017). Neurofeedback as a form of cognitive rehabilitation therapy following stroke: A systematic review. PLoS ONE, 12(5), Article e0177290. https://doi.org/10.1371/journal.pone.0177290

Ros, T., Enriquez-Geppert, S., Zotev, V., Young, K. D., Wood, G., Whitfield-Gabrieli, S., Wan, F., Vuilleumier, P., Vialatte, F., Van De Ville, D., Todder, D., Surmeli, T., Sulzer, J. S., Strehl, U., Sterman, M. B., Steiner, N. J., Sorger, B., Soekadar, S. R., Sitaram, R. … Thibault, R. T. (2020). Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain, 143(6), 1674–1685. https://doi.org/10.1093/brain/awaa009

Samaha, J., & Postle, B. R. (2015). The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25(22), 2985–2990. https://doi.org/10.1016/j.cub.2015.10.007

Schibli, K., Wong, K., Hedayati, N., & D’Angiulli, A. (2017). Attending, learning, and socioeconomic disadvantage: Developmental cognitive and social neuroscience of resilience and vulnerability. Annals of the New York Academy of Sciences, 1396(1), 19–38. https://doi.org/10.1111/nyas.13369

Schlatter, S., Louisy, S., Canada, B., Thérond, C., Duclos, A., Blakeley, C., Lehot, J.-J., Rimmelé, T., Guillot, A., Lilot, M., & Debarnot, U. (2022). Personality traits affect anticipatory stress vulnerability and coping effectiveness in occupational critical care situations. Scientific Reports, 12(1), Article 20965. https://doi.org/10.1038/s41598-022-24905-z

Schoenfeld, W. N. (1970). The theory of reinforcement schedules. Appleton-Century-Crofts.

Schönenberg, M., Wiedemann, E., Schneidt, A., Scheeff, J., Logemann, A., Keune, P. M., & Hautzinger, M. (2017). Neurofeedback, sham neurofeedback, and cognitive-behavioural group therapy in adults with attention-deficit hyperactivity disorder: A triple-blind, randomised, controlled trial. The Lancet Psychiatry, 4(9), 673–684. https://doi.org/10.1016/S2215-0366(17)30291-2

Shackman, A. J., McMenamin, B. W., Slagter, H. A., Maxwell, J. S., Greischar, L. L., & Davidson, R. J. (2009). Electromyogenic artifacts and electroencephalographic inferences. Brain Topography, 22(1), 7–12. https://doi.org/10.1007/s10548-009-0079-4

Sherlin, L. H., Arns, M., Lubar, J., Heinrich, H., Kerson, C., Strehl, U., & Sterman, M. B. (2011). Neurofeedback and basic learning theory: Implications for research and practice. Journal of Neurotherapy, 15(4), 292–304. https://doi.org/10.1080/10874208.2011.623089

Shuda, Q., Bougoulias, M. E., & Kass, R. (2020). Effect of nature exposure on perceived and physiologic stress: A systematic review. Complementary Therapies in Medicine, 53, Article 102514. https://doi.org/10.1016/j.ctim.2020.102514

Slobounov, S., Cao, C., Jaiswal, N., & Newell, K. M. (2009). Neural basis of postural instability identified by VTC and EEG. Experimental Brain Research, 199(1), 1–16. https://doi.org/10.1007/s00221-009-1956-5

Smetanin, N., Belinskaya, A., Lebedev, M., & Ossadtchi, A. (2020). Digital filters for low-latency quantification of brain rhythms in real time. Journal of Neural Engineering, 17(4), Article 046022. https://doi.org/10.1088/1741-2552/ab890f

Smith, T., Panfil, K., Bailey, C., & Kirkpatrick, K. (2019). Cognitive and behavioral training interventions to promote self-control. Journal of Experimental Psychology: Animal Learning and Cognition, 45(3), 259–279. https://doi.org/10.1037/xan0000208

Sokhadze, T. M., Cannon, R. L., & Trudeau, D. L. (2008). EEG biofeedback as a treatment for substance use disorders: Review, rating of efficacy, and recommendations for further research. Applied Psychophysiology and Biofeedback, 33(1), 1–28. https://doi.org/10.1007/s10484-007-9047-5

Steel, A., Silson, E. H., Stagg, C. J., & Baker, C. I. (2016). The impact of reward and punishment on skill learning depends on task demands. Scientific Reports, 6(1), Article 36056. https://doi.org/10.1038/srep36056

Steingrimsson, S., Bilonic, G., Ekelund, A.-C., Larson, T., Stadig, I., Svensson, M., Vukovic, I. S., Wartenerg, C., Wrede, O., & Bernhardsson, S. (2020). Electroencephalography-based neurofeedback as treatment for post-traumatic stress disorder: A systematic review and meta-analysis. European Psychiatry, 63(1), Article e7. https://doi.org/10.1192/j.eurpsy.2019.7

Stoffers, D., Bosboom, J. L. W., Deijen, J. B., Wolters, E. C., Berendse, H. W., & Stam, C. J. (2007). Slowing of oscillatory brain activity is a stable characteristic of Parkinson’s disease without dementia. Brain: A Journal of Neurology, 130(7), 1847–1860. https://doi.org/10.1093/brain/awm034

Strothmann, S. (2024). Neurofeedback training for children with ADHD : Evaluating the effect of personalized and standardized neurofeedback protocols on theta rhythms, beta rhythms and the iAPF [Student thesis]. DiVA. https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23971

Su, K.-H., Hsueh, J.-J., Chen, T., & Shaw, F.-Z. (2021). Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity. Scientific Reports, 11(1), Article 19615. https://doi.org/10.1038/s41598-021-99235-7

Sudakov, K. V. (1997). A systems process of reinforcement. Neuroscience and Behavioral Physiology, 27(4), 370–380. https://doi.org/10.1007/BF02462938

Swerdloff, M. M., & Hargrove, L. J. (2023). Dry EEG measurement of P3 to evaluate cognitive load during sitting, standing, and walking. PLoS ONE, 18(7), Article e0287885. https://doi.org/10.1371/journal.pone.0287885

Tarasov, E. A. (2007). [Boslab computer-based system: A polyfunctional computer biofeedback environment]. Meditsinskaia Tekhnika, (4), 48–51.

Tazaki, M. (2024). A review: Effects of neurofeedback on patients with mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Frontiers in Human Neuroscience, 17, Article 1331436. https://doi.org/10.3389/fnhum.2023.1331436

Tenke, C. E., Kayser, J., Miller, L., Warner, V., Wickramaratne, P., Weissman, M. M., & Bruder, G. E. (2013). Neuronal generators of posterior EEG alpha reflect individual differences in prioritizing personal spirituality. Biological Psychology, 94(2), 426–432. https://doi.org/10.1016/j.biopsycho.2013.08.001

Thatcher, R. W., Walker, R. A., Biver, C. J., North, D. N., & Curtin, R. (2003). Quantitative EEG normative databases: Validation and clinical correlation. Journal of Neurotherapy, 7(3–4), 87–121. https://doi.org/10.1300/J184v07n03_05

Travis, T. A., Kondo, C. Y., & Knott, J. R. (1974). Personality variables and alpha enhancement: A correlative study. British Journal of Psychiatry, 124(583), 542–544. https://doi.org/10.1192/bjp.124.6.542

Tumyalis, A. V., & Aftanas, L. I. (2014). Contribution of neurophysiological endophenotype, individual frequency of EEG alpha oscillations, to mechanisms of emotional reactivity. Bulletin of Experimental Biology and Medicine, 156(6), 711–716. https://doi.org/10.1007/s10517-014-2431-2

Urigüen, J. A., & Garcia-Zapirain, B. (2015). EEG artifact removal—State-of-the-art and guidelines. Journal of Neural Engineering, 12(3), Article 031001. https://doi.org/10.1088/1741-2560/12/3/031001

VaezMousavi, S., Barry, R., Rushby, J., & Clarke, A. (2007). Arousal and activation effects on physiological and behavioral responding during a continuous performance task. Acta Neurobiologiae Experimentalis, 67(4), 461–470. https://doi.org/10.55782/ane-2007-1662

van der Meer, J. N., Pampel, A., Van Someren, E. J. W., Ramautar, J. R., van der Werf, Y. D., Gomez-Herrero, G., Lepsien, J., Hellrung, L., Hinrichs, H., Möller, H. E., & Walter, M. (2016). Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections—A validation of a real-time simultaneous EEG/fMRI correction method. NeuroImage, 125, 880–894. https://doi.org/10.1016/j.neuroimage.2015.10.064

Veilahti, A. V. P., Kovarskis, L., & Cowley, B. U. (2021). Neurofeedback learning is skill acquisition but does not guarantee treatment benefit: Continuous-time analysis of learning-curves from a clinical trial for ADHD. Frontiers in Human Neuroscience, 15, Article 668780. https://doi.org/10.3389/fnhum.2021.668780

Vernon, D., Frick, A., & Gruzelier, J. (2004). Neurofeedback as a treatment for ADHD: A methodological review with implications for future research. Journal of Neurotherapy, 8(2), 53–82. https://doi.org/10.1300/J184v08n02_04

Vernon, D. J. (2005). Can neurofeedback training enhance performance? An evaluation of the evidence with implications for future research. Applied Psychophysiology and Biofeedback, 30(4), 347–364. https://doi.org/10.1007/s10484-005-8421-4

Voetterl, H., van Wingen, G., Michelini, G., Griffiths, K. R., Gordon, E., DeBeus, R., Korgaonkar, M. S., Loo, S. K., Palmer, D., Breteler, R., Denys, D., Arnold, L. E., du Jour, P., van Ruth, R., Jansen, J., van Dijk, H., & Arns, M. (2023). Brainmarker-I differentially predicts remission to various attention-deficit/hyperactivity disorder treatments: A discovery, transfer, and blinded validation study. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 8(1), 52–60. https://doi.org/10.1016/j.bpsc.2022.02.007

Wächter, T., Lungu, O. V., Liu, T., Willingham, D. T., & Ashe, J. (2009). Differential effect of reward and punishment on procedural learning. The Journal of Neuroscience, 29(2), 436–443. https://doi.org/10.1523/JNEUROSCI.4132-08.2009

Wacker, M. S. (1996). Alpha brainwave training and perception of time passing: Preliminary findings. Biofeedback and Self-Regulation, 21(4), 303–309. https://doi.org/10.1007/BF02214430

Wan, F., Nan, W., Vai, M. I., & Rosa, A. (2014). Resting alpha activity predicts learning ability in alpha neurofeedback. Frontiers in Human Neuroscience, 8, Article 500. https://doi.org/10.3389/fnhum.2014.00500

Wang, Y. S., Liu, Z. D., Yue, S., Wang, W. Z., & Tian, F. S. (2018). [Effect of biofeedback therapy on metabolic syndrome under different levels of job stress]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi = Zhonghua Laodong Weisheng Zhiyebing Zazhi = Chinese Journal of Industrial Hygiene and Occupational Diseases, 36(10), 728–733. https://doi.org/10.3760/cma.j.issn.1001-9391.2018.10.002

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

Wood, G., Willmes, K., Koten, J. W., & Kober, S. E. (2024). Fat tails and the need to disclose distribution parameters of qEEG databases. PLoS ONE, 19(1), Article e0295411. https://doi.org/10.1371/journal.pone.0295411

Xiang, M.-Q., Hou, X.-H., Liao, B.-G., Liao, J.-W., & Hu, M. (2018). The effect of neurofeedback training for sport performance in athletes: A meta-analysis. Psychology of Sport and Exercise, 36, 114–122. https://doi.org/10.1016/j.psychsport.2018.02.004

Yamaguchi, H. (1981). Characteristics of alpha-enhancement biofeedback training with eyes closed [dissertation]. Tohoku University.

Yeh, W.-H., Hsueh, J.-J., & Shaw, F.-Z. (2021). Neurofeedback of alpha activity on memory in healthy participants: A systematic review and meta-analysis. Frontiers in Human Neuroscience, 14, Article 562360. https://doi.org/10.3389/fnhum.2020.562360

Zandi Mehran, Y., Firoozabadi, M., & Rostami, R. (2015). Improvement of neurofeedback therapy for improved attention through facilitation of brain activity using local sinusoidal extremely low frequency magnetic field exposure. Clinical EEG and Neuroscience, 46(2), 100–112. https://doi.org/10.1177/1550059414524403

Zhao, W., Van Someren, E. J. W., Li, C., Chen, X., Gui, W., Tian, Y., Liu, Y., & Lei, X. (2021). EEG spectral analysis in insomnia disorder: A systematic review and meta-analysis. Sleep Medicine Reviews, 59, Article 101457. https://doi.org/10.1016/j.smrv.2021.101457

Downloads

Published

2025-06-27

Issue

Vol. 12 No. 2 (2025)

Section

Review Articles

License

Copyright (c) 2025 Olga Bazanova, Ekaterina Nikolenko, Alexander Zakharov, Robert Barry

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:
  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).