The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
What learning theories can teach us in designing neurofeedback treatments
Open accessAbstract
Popular definitions of neurofeedback point out that neurofeedback is a process of operant conditioning which leads to self-regulation of brain activity. Self-regulation of brain activity is considered to be a skill. The aim of this paper is to clarify that not only operant conditioning plays a role in the acquisition of this skill. In order to design the learning process additional references have to be derived from classical conditioning, two-process-theory and in particular from skill learning and research into motivational aspects. The impact of learning by trial and error, cueing of behavior, feedback, reinforcement, and knowledge of results as well as transfer of self-regulation skills into everyday life will be analyzed in this paper. In addition to these learning theory basics this paper tries to summarize the knowledge about acquisition of self-regulation from neurofeedback studies with a main emphasis on clinical populations. As a conclusion it is hypothesized that learning to self-regulate has to be offered in a psychotherapeutic, i.e., behavior therapy framework.
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“Notably, no explicit strategies or instructions were given as, with few exceptions [204], implicit strategies have been shown to produce better outcomes [205–210].”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [206]
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“Manual, rather than automated, thresholding was chosen as it has been reported to lead to better EEG-learning [125, 173, 206, 208].”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [206]
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Cites
Skinner, B. F., & Hull, C. L. (1944) · The American Journal of Psychology · doi:10.2307/1416955 · Cited by 4,061
Executive functions and self-regulation
Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.01.006 · Cited by 1,965
The influence of improvement in one mental function upon the efficiency of other functions. (I).
Woodworth, R. S., & Thorndike, E. L. (1901) · Psychological Review · doi:10.1037/h0074898 · Cited by 1,223
Arns, M., de Ridder, S., Strehl, U., Breteler, M., & Coenen, A. (2009) · Clinical EEG and Neuroscience · doi:10.1177/155005940904000311 · Cited by 794
Self-citationReduced frequency of knowledge of results enhances motor skill learning.
Winstein, C. J., & Schmidt, R. A. (1990) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/0278-7393.16.4.677 · Cited by 708
Fitts, P. M. (1964) · Elsevier eBooks · doi:10.1016/b978-1-4832-3145-7.50016-9 · Cited by 683
Gruzelier, J. H. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.09.015 · Cited by 596
Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills
Koralek, A. C., Jin, X., Long, J. D., II, Costa, R. M., & Carmena, J. M. (2012) · Nature · doi:10.1038/nature10845 · Cited by 390
Strehl, U., Leins, U., Goth, G., Klinger, C., Hinterberger, T., & Birbaumer, N. (2006) · PEDIATRICS · doi:10.1542/peds.2005-2478 · Cited by 315
Self-citationLotte, F., Larrue, F., & Mühl, C. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00568 · Cited by 307
Research works printed but not linked: 8
- Blume, 2012, Neurofeedbacktraining bei Kindern mit einer Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS): Eine Untersuchung der Trainingsverläufe mit dem Versuch der Klassifikation von Lernern und Nicht-Lernern.
- Fitts, 1967, Human Performance.
- Holzapfel, 1998, PräDiktoren der Selbstregulation der Langsamen Hirnpotentiale bei Epilepsie
- Kamiya, 1966, Trained Control of EEG Alpha Frequency in Humans.
- Kisil, 1992, Rückmeldung und Modifikation Langsamer Hirnrindenpotentiale.
- Kisil, 1992, Biofeedback langsamer Hirnpotentiale, Z. Exp. Angew. Psychol., 39, 216
- Neumann, 2001, Gehirn-Computer-Schnittstelle: Einflussfaktoren der Selbstregulation Langsamer Kortikaler Hirnpotentiale.
- Strehl, 2013, Lerntheoretische grundlagen und überlegungen zum neurofeedback, 13
Cited by
Sorted by citations
EEG-Neurofeedback as a Tool to Modulate Cognition and Behavior: A Review Tutorial
Enriquez‐Geppert, S., Huster, R. J., & Herrmann, C. S. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00051 · Cited by 526
A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback
Gaume, A., Vialatte, A., Mora-Sánchez, A., Ramdani, C., & Vialatte, F. B. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.06.012 · Cited by 133
Virtual reality in the application of heart rate variability biofeedback
Rockstroh, C., Blum, J., & Göritz, A. S. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.06.011 · Cited by 139
Neurofeedback: One of today's techniques in psychiatry?
Arns, M., Batail, J.-M., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., Fovet, T., Jardri, R., Le-Van-Quyen, M., Lotte, F., et al. (2017) · L'Encéphale · doi:10.1016/j.encep.2016.11.003 · Cited by 117
Paret, C., Goldway, N., Zich, C., Keynan, J. N., Hendler, T., Linden, D. E. J., & Kadosh, K. C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116107 · Cited by 118
Metadata
- Authors
- Strehl, U.
- Affiliations
- University of Tübingen (DE)
- Corresponding author
- Strehl, Ute
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2014-11-06
- Volume
- 8
- Pages
- 894-894
- ISSN
- 1662-5161 (ISSN-L)
- PMC
- PMC4222234
- OpenAlex
- W2038534511
- Cited by
- 137
- References
- 53
- Citations by year
- 2026: 10 · 2025: 7 · 2024: 10 · 2023: 9 · 2022: 12 · 2021: 13 · 2020: 14 · 2019: 16 · 2018: 15 · 2017: 13 · 2016: 9 · 2015: 7
- FWCI
- 5.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Human Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Deutsche Forschungsgemeinschaft (2503/4-2, STR 597/7-1, 597/7-1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Social Sciences › Psychology › Developmental and Educational Psychology › Behavioral and Psychological Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- neurofeedback, learning theory, operant conditioning, classical conditioning, two-process theory, skill acquisition, self-regulation of brain activity, motivation, trial-and-error learning, feedback, reinforcement, knowledge of results, behavior therapy, clinical populations
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