Bibliometric analysis of neurofeedback research from 2000 to 2022

Authors

  • Siti Atiyah Ali (1) Centre for Healthcare Science and Technology, Universiti Tunku Abdul Rahman, Bandar Sungai Long, 43000 Kajang, Malaysia (2) Department of Electronic Engineering, Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, 31900, Perak, Malaysia https://orcid.org/0000-0002-8201-7740
  • Mazira Mohamad Ghazali Department of Neuroscience & Brain & Behaviour Cluster, Universiti Sains Malaysia, 16150, Kelantan, Malaysia
  • Nurfaizatul Aisyah Ab Aziz Department of Neuroscience & Brain & Behaviour Cluster, Universiti Sains Malaysia, 16150, Kelantan, Malaysia
  • Humaira Nisar (1) Centre for Healthcare Science and Technology, Universiti Tunku Abdul Rahman, Bandar Sungai Long, 43000 Kajang, Malaysia (2) Department of Electronic Engineering, Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, 31900, Perak, Malaysia

DOI:

https://doi.org/10.31117/neuroscirn.v7i1.265

Keywords:

Neurofeedback, Neurorehabilitation, Neuroscience

Abstract

The application of neurofeedback is gaining increasing interest among neuroscientists as a potential neurorehabilitation approach in cases of various neuro-related functional abnormalities. Discovering the current state of research and identifying gaps in the field of neurofeedback is an essential step in planning and mapping out future research efforts. This bibliometric analysis paper aims to identify the publications and research in neurofeedback from 2000 to 2022. A comprehensive Scopus database search was conducted using the keyword "neurofeedback" and relevant publications from 2000 to 2022 were retrieved. Bibliometric analyses were performed using the Harzing's Publish or Perish and VOSviewer software programmes. The number of retrieved documents was 1835. The number of publications has shown a steadily increasing trend since 2000, with a prominent spike in publications in 2014–2015, indicating a sudden interest in neurofeedback. Among the retrieved documents, 50.3% were related to neuroscience, 23.7% related to medicine, and 13.1% related to psychology. The main contributors to this research come from the United States (24.7%), Germany (13.7%), the United Kingdom (9.4%), and Switzerland (4.9%). Based on the network visualisation of author keywords, the most frequently occurring keywords were neurofeedback, real-time functional magnetic resonance imaging (fMRI), brain-computer interface (BCI), neuromodulation, and neurofeedback training. This bibliometric analysis presents the current status, knowledge base, and future neurofeedback study directions. These findings will benefit future researchers interested in applying neurofeedback as a potential neurorehabilitation approach for a wider population.

References

Adamou, M., Fullen, T., & Jones, S. L. (2020). EEG for Diagnosis of Adult ADHD: A Systematic Review With Narrative Analysis. Frontiers in Psychiatry, 11, 871. https://doi.org/10.3389/fpsyt.2020.00871

Alsharif, A. H., Md Salleh, N. Z., Baharun, R., & Rami Hashem E, A. (2021). Neuromarketing research in the last five years: a bibliometric analysis. Cogent Business & Management, 8(1), 1978620. https://doi.org/10.1080/23311975.2021.1978620

Alsharif, A. H., Md Salleh, N. Z., Alrawad, M., & Lutfi, A. (2023a). Exploring global trends and future directions in advertising research: A focus on consumer behavior. Current Psychology. https://doi.org/10.1007/s12144-023-04812-w

Alsharif, A. H., Md Salleh, N. Z., & Pilelienė, L. (2023b). A Comprehensive Bibliometric Analysis of fNIRS and fMRI Technology in Neuromarketing. Scientific Annals of Economics and Business, 70(3), 459–472. https://doi.org/10.47743/saeb-2023-0031

Alsharif, A. H., Md Salleh, N. Z., Baharun, R., Abuhassna, H., & Alharthi Rami Hashem, E. (2022). A Global Research Trends of Neuromarketing: 2015-2020. Ravista de Communication, 21(1), 15–32. http://dx.doi.org/10.26441/RC21.1-2022-A1

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

Itil, T. M. (1977). Qualitative and Quantitative EEG Findings in Schizophrenia. Schizophrenia Bulletin, 3(1), 61–79. https://doi.org/10.1093/schbul/3.1.61

Janssen, T. W. P., Bink, M., Geladé, K., van Mourik, R., Maras, A., & Oosterlaan, J. (2016). A randomized controlled trial into the effects of neurofeedback, methylphenidate, and physical activity on EEG power spectra in children with ADHD. Journal of Child Psychology and Psychiatry, 57(5), 633–644. https://doi.org/10.1111/jcpp.12517

Lin, C.-L., Chen, Z., Jiang, X., Chen, G. L., & Jin, P. (2022). Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis. Frontiers in Neuroscience, 16, 872532. https://doi.org/10.3389/fnins.2022.872532

Liu, X., Zhao, S., Tan, L., Tan, Y., Wang, Y., Ye, Z., Hou, C., Xu, Y., Liu, S., & Wang, G. (2022). Frontier and hot topics in electrochemiluminescence sensing technology based on CiteSpace bibliometric analysis. Biosensors and Bioelectronics, 201, 113932. https://doi.org/10.1016/j.bios.2021.113932

Loriette, C., Ziane, C., & Ben Hamed, S. (2021). Neurofeedback for cognitive enhancement and intervention and brain plasticity. Revue Neurologique, 177(9), 1133–1144. https://doi.org/10.1016/j.neurol.2021.08.004

Luo, X., Wu, Y., Niu, L., & Huang, L. (2022). Bibliometric Analysis of Health Technology Research: 1990~2020. International Journal of Environmental Research and Public Health, 19(15), 9044. https://doi.org/10.3390/ijerph19159044

Manoj Kumar L., George, R. J., & P.S., A. (2023). Bibliometric Analysis for Medical Research. Indian Journal of Psychological Medicine, 45(3), 277–282. https://doi.org/10.1177/02537176221103617

Marzbani, H., Marateb, H., & Mansourian, M. (2016). Methodological Note: Neurofeedback: A Comprehensive Review on System Design, Methodology and Clinical Applications. Basic and Clinical Neuroscience Journal, 7(2), 143–158. https://doi.org/10.15412/J.BCN.03070208

Newson, J. J., & Thiagarajan, T. C. (2019). EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies. Frontiers in Human Neuroscience, 12. 521. https://doi.org/10.3389/fnhum.2018.00521

Othmer, S. (2015). History of neurofeedback. In Restoring the Brain (pp. 23–50). CRC Press. https://doi.org/10.1201/b18671-4

Picken, C., Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2020). The Theta/Beta Ratio as an Index of Cognitive Processing in Adults With the Combined Type of Attention Deficit Hyperactivity Disorder. Clinical EEG and Neuroscience, 51(3), 167–173. https://doi.org/10.1177/1550059419895142

Szomszor, M., Adams, J., Fry, R., Gebert, C., Pendlebury, D. A., Potter, R. W. K., & Rogers, G. (2021). Interpreting Bibliometric Data. Frontiers in Research Metrics and Analytics, 5, 628703. https://doi.org/10.3389/frma.2020.628703

Tseng, Y.-H., Tamura, K., & Okamoto, T. (2021). Neurofeedback training improves episodic and semantic long-term memory performance. Scientific Reports, 11(1), 17274. https://doi.org/10.1038/s41598-021-96726-5

Tsiamalou, A., Dardiotis, E., Paterakis, K., Fotakopoulos, G., Liampas, I., Sgantzos, M., Siokas, V., & Brotis, A. G. (2022). EEG in Neurorehabilitation: A Bibliometric Analysis and Content Review. Neurology International, 14(4), 1046–1061. https://doi.org/10.3390/neurolint14040084

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

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

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Published

2024-03-16

How to Cite

Ali, S. A., Mohamad Ghazali , M., Ab Aziz, N. A. and Nisar, H. (2024) “Bibliometric analysis of neurofeedback research from 2000 to 2022”, Neuroscience Research Notes, 7(1), pp. 265.1–265.16. doi: 10.31117/neuroscirn.v7i1.265.

Issue

Vol. 7 No. 1 (2024): Regular Issue

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Data Notes

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Copyright (c) 2024 Siti Atiyah Ali, Mazira Mohamad Ghazali , Nurfaizatul Aisyah Ab Aziz, Humaira Nisar

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