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Cited by 225EEG and Brain-Computer InterfacesNeural dynamics and brain functionFree Will and Agency

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Learning to modulate one’s own brain activity: The effect of spontaneous mental strategies

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Kober, Silvia E., Witte, Matthias, Ninaus, Manuel, Neuper, Christa, Wood, Guilherme·2013·Frontiers in Human Neuroscience
DOI 10.3389/fnhum.2013.00695PMC PMC3798979
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Abstract

Using neurofeedback (NF), individuals can learn to modulate their own brain activity, in most cases electroencephalographic (EEG) rhythms. Although a large body of literature reports positive effects of NF training on behavior and cognitive functions, there are hardly any reports on how participants can successfully learn to gain control over their own brain activity. About one third of people fail to gain significant control over their brain signals even after repeated training sessions. The reasons for this failure are still largely unknown. In this context, we investigated the effects of spontaneous mental strategies on NF performance. Twenty healthy participants performed either a SMR (sensorimotor rhythm, 12-15 Hz) based or a Gamma (40-43 Hz) based NF training over ten sessions. After the first and the last training session, they were asked to write down which mental strategy they have used for self-regulating their EEG. After the first session, all participants reported the use of various types of mental strategies such as visual strategies, concentration, or relaxation. After the last NF training session, four participants of the SMR group reported to employ no specific strategy. These four participants showed linear improvements in NF performance over the ten training sessions. In contrast, participants still reporting the use of specific mental strategies in the last NF session showed no changes in SMR based NF performance over the ten sessions. This effect could not be observed in the Gamma group. The Gamma group showed no prominent changes in Gamma power over the NF training sessions, regardless of the mental strategies used. These results indicate that successful SMR based NF performance is associated with implicit learning mechanisms. Participants stating vivid reports on strategies to control their SMR probably overload cognitive resources, which might be counterproductive in terms of increasing SMR power.

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Figure 1 Mental strategies used during the first (NF S01) and the last (NF S10) NF training session, presented separately for each participant of the SMR (subject code in black font color) and Gamma group (subject code in gray font color).
Figure 1 Mental strategies used during the first (NF S01) and the last (NF S10) NF training session, presented separately for each participant of the SMR (subject code in black font color) and Gamma group (subject code in gray font color).CC BY · PubMed Central
Figure 2 Means and standard deviations of z-transformed SMR power (12–15 Hz) values during the first and tenth NF training session, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group).
Figure 2 Means and standard deviations of z-transformed SMR power (12–15 Hz) values during the first and tenth NF training session, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group).CC BY · PubMed Central
Figure 3 Means and standard deviations of z-transformed SMR (12–15 Hz) power (NF performance) over the ten NF training sessions, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group) of the SMR group and the results of the regression analyses.
Figure 3 Means and standard deviations of z-transformed SMR (12–15 Hz) power (NF performance) over the ten NF training sessions, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group) of the SMR group and the results of the regression analyses.CC BY · PubMed Central
Figure 4 Means and standard deviations of z-transformed Gamma (40–43 Hz) power (NF performance) over the ten NF training sessions, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group) of the Gamma group and the results of the regression analyses. Note that only standard deviations for the strategy group are plotted since only one participant was present in the no strategy group.
Figure 4 Means and standard deviations of z-transformed Gamma (40–43 Hz) power (NF performance) over the ten NF training sessions, presented separately for participants reporting to use a specific mental strategy in the tenth NF session (strategy group) and participants reporting no specific mental strategy in the tenth NF session (no strategy group) of the Gamma group and the results of the regression analyses. Note that only standard deviations for the strategy group are plotted since only one participant was present in the no strategy group.CC BY · PubMed Central
Figure 5 Z-transformed SMR power for the SMR group (left panel) and z-transformed Gamma power for the Gamma group (right panel) during first (gray bars) and tenth (black bars) NF training session, presented separately for different mental strategies used to control one's own EEG signal. Note that no error bars are plotted since only single participants were present in several categories.
Figure 5 Z-transformed SMR power for the SMR group (left panel) and z-transformed Gamma power for the Gamma group (right panel) during first (gray bars) and tenth (black bars) NF training session, presented separately for different mental strategies used to control one's own EEG signal. Note that no error bars are plotted since only single participants were present in several categories.CC BY · PubMed Central

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Metadata

Authors
Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G.
Affiliations
University of Graz (AT)
Corresponding author
Wood, Guilherme
ORCID
Venue
Frontiers in Human Neuroscience
Publisher
Frontiers Media SA
Published
2013
Volume
7
Pages
695-695
ISSN
1662-5161 (ISSN-L)
DOI
10.3389/fnhum.2013.00695
PMC
PMC3798979
OpenAlex
W2041078369
Cited by
225
References
62
Citations by year
2026: 15 · 2025: 11 · 2024: 17 · 2023: 22 · 2022: 24 · 2021: 21 · 2020: 22 · 2019: 14 · 2018: 21 · 2017: 17 · 2016: 11 · 2015: 13 · 2014: 16 · 2013: 1
FWCI
7.44
Type
journal article
Language
en
Open access
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)
  • Unipub UB Graz (Universität Graz) (submittedVersion, cc-by)
Funders
European Commission (287320)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Social Sciences › Arts and Humanities › Philosophy › Free Will and Agency
Keywords
neurofeedback, self-regulation of brain activity, sensorimotor rhythm, gamma band, implicit learning, cognitive resource allocation

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