The Do's and Don'ts of Neurofeedback Training: A Review of the Controlled Studies Using Healthy Adults
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The goal of EEG neurofeedback (EEG-NFB) training is to induce changes in the power of targeted EEG bands to produce beneficial changes in cognitive or motor function. The effectiveness of different EEG-NFB protocols can be measured using two dependent variables: (1) changes in EEG activity and (2) behavioral changes of a targeted function (for therapeutic applications the desired changes should be long-lasting). To firmly establish a causal link between these variables and the selected protocol, similar changes should not be observed when appropriate control paradigms are used. The main objective of this review is to evaluate the evidence, reported in the scientific literature, which supports the validity of various EEG-NFB protocols. Our primary concern is to highlight the role that uncontrolled nonspecific factors can play in the results generated from EEG-NFB studies. Nonspecific factors are often ignored in EEG-NFB designs or the data are not presented, which means conclusions should be interpreted cautiously. As an outcome of this review we present a do's and don'ts list, which can be used to develop future EEG-NFB methodologies, based on the small set of experiments in which the proper control groups have excluded non-EEG-NFB related effects. We found two features which positively correlated with the expected changes in power of the trained EEG band(s): (1) protocols which focused on training a smaller number of frequency bands and (2) a bigger number of electrodes used for neurofeedback training. However, we did not find evidence in support of the positive relationship between power changes of a trained frequency band(s) and specific behavioral effects.
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The extrapolation from neurofeedback to SMR BCI is not straightforward because neurofeedback typically exerts lesser demands, requiring control over predefined brain signals by direct observation, while SMR BCIs are complex pattern-recognition systems feeding back transformations of multivariate brain activity.
“However, this extrapolation is by no means straightforward, as neurofeedback typically exerts lesser demands, requiring control over predefined brain signals by direct observation [56], while SMR BCIs are complex pattern-recognition systems feeding back transformations of multivariate brain activity [46].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [56]
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- Authors
- Rogala, J., Jurewicz, K., Paluch, K., Kublik, E., Cetnarski, R., & Wróbel, A.
- Affiliations
- Instytut Biologii Doświadczalnej im. Marcelego Nenckiego (PL)
- Corresponding author
- Rogala, Jacek
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2016-06-17
- Volume
- 10
- Pages
- 301-301
- ISSN
- 1662-5161 (ISSN-L)
- PMC
- PMC4911408
- OpenAlex
- W2426762202
- Cited by
- 115
- References
- 74
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 6 · 2023: 15 · 2022: 12 · 2021: 14 · 2020: 14 · 2019: 13 · 2018: 10 · 2017: 12
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Human Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Narodowe Centrum Nauki (2012/07/B/NZ7/04383)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Neurology › Transcranial Magnetic Stimulation Studies
- Keywords
- neurofeedback, EEG band power, non-specific effects, control groups, electrode number, behavioral effects, healthy adults, causal inference
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