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Effects of neurofeedback and working memory-combined training on executive functions in healthy young adults

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Abstract

Given the interest in improving executive functions, the present study examines a promising combination of two training techniques: neurofeedback training (NFT) and working memory training (WMT). NFT targeted increasing the amplitude of individual’s upper Alpha frequency band at the parietal midline scalp location (Pz), and WMT consisted of an established computerized protocol with working memory updating and set-shifting components. Healthy participants (n = 140) were randomly allocated to five combinations of training, including visual search training used as an active control training for the WMT; all five groups were compared to a sixth silent control group receiving no training. All groups were evaluated before and after training for resting-state electroencephalogram (EEG) and behavioral executive function measures. The participants in the silent control group were unaware of this procedure, and received one of the training protocols only after study has ended. Results demonstrated significant improvement in the practice tasks in all training groups including non-specific influence of NFT on resting-state EEG spectral topography. There was only a near transfer effect (improvement in working memory task) for WMT, which remained significant in the delayed post-test (after 1 month), in comparison to silent control group but not in comparison to active control training group. The NFT + WMT combined group showed improved mental rotation ability both in the post-training and in the follow-up evaluations. This improvement, however, did not differ significantly from that in the silent control group. We conclude that the current training protocols, including their combination, have very limited influence on the executive functions that were assessed in this study.

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Notes

  1. Improvement in the training task leads to improvement on tasks that are similar to the one participants were trained on.

  2. Improvement in the training task can be generalized to improvement on tasks that are very different from the one participants were trained on, but still require similar cognitive processes.

  3. Handedness was determined based on the preferred hand for writing, assessed on a three-point scale (1 = right, 2 = left, 3 = either hand/ambidextrous).

  4. The Intelligence Rating Score is a well-established tool for intelligence assessment comprised from four sub-tests presented in a multiple-choice format: (1) the Otis-R, which measures the ability to understand and carry out verbal instructions; (2) Similarities-R, assesses verbal abstraction and categorization; (3) Arithmetic-R, which measures mathematical reasoning, concentration, and concept manipulation; and (4) Raven’s Progressive Matrices-R, that measures non-verbal abstract reasoning and visual-spatial problem-solving abilities. The sum of the scores for the four tests forms a validated measure of general intelligence, scored on a 9-point scale, scaled between 10 and 90, with a 10-point increment at each score (Gal 1986). The correlation between the general intelligence rating score and the WAIS total IQ is > 0.90 (Kaplan et al. 2002).

  5. In general, the test re-test reliability of quantitative EEG is an exponential function of sample length in which 20 s epochs are approximately 0.8 reliable, 40 s approximately 0.9 reliable and 60 s asymptotes at approximately 0.95 reliability (Burgess and Gruzelier 1993; Van Albada and Robinson 2007).

  6. It is important to mention here that this brief executive functions battery provided a relatively reasonable coverage of the executive function domain. However, this coverage was nonetheless incomplete. For example, instead of measuring working memory updating, we indirectly measured other working memory functions. One of them is conceptually related to capacity (“Alternative Cost”). The other (“Tau”) is described in the main text.

  7. In the practice phase, all responses were followed by a feedback (correct/error), see Fig. 2.

  8. The validation of Tau as an index of working memory functioning comes from three sources. One is the correlational studies (e.g., Schmiedeck et al. 2007), showing a high correlation between individual differences in Tau and in working memory. The second is the fact that Tau (and not Sigma or Mu) is strongly influenced by the working memory demands of the task (mapping arbitrariness, especially when the number of alternatives is high, Shahar et al. 2014, see also, 2018). Lastly, mathematical modeling reported in these papers has linked Tau to the rate of retrieval from working memory, with this model being superior to alternative models such as those linking Tau mainly to attentional lapses or to the rate of evidence accumulation.

  9. We considered the first 4 trials of the mental rotation test as practice trials and, therefore, analysis was conducted without them, on 60 trials per participant.

  10. The proportion of discarded trials is the sum of all three evaluations (pre, post, follow-up).

  11. Since two participants from the combined training (NFT + WMT) had extreme NFT results, we calculate the interaction without them and the results remained similar [F (9, 324) = 0.98, p = .461, η2p = .02, BF10 = 0.06, indicating strong support for H0].

  12. Similar results were found after excluding the two participants from the combined training (NFT + active control training group) who had extreme NFT results [F (9, 324) = 0.51, p = .864, η2p = .01, BF10 = 0.02, indicating strong support for H0].

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Acknowledgements

The study was supported by the Israel Defense Forces (IDF) Medical Corps and Directorate of Defense Research & Development, Israeli Ministry of Defense (IMOD DDR&D). We would like to thank Col. Dr. Erez Carmon, Col. Dr. Eyal Fructer and Lut. Idit Oz for their belief in the value of this research and, therefore, supporting this study. Dr. Arik Eisenkraft and Dr. Linn Wagnert-Avraham from the Institute for Research in Military Medicine, the Hebrew University Faculty of Medicine, Jerusalem for their help in purchasing the equipment needed for the study and handling the budget. As well as Mr. Erez Gordon and Prof. Robert Thatcher for advising in regard to analyzing the data.

Funding

The study was supported by the Israel Defense Forces (IDF) Medical Corps and Directorate of Defense Research & Development, Israeli Ministry of Defense (IMOD DDR&D).

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  1. Department of Psychology and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, 84105, Beersheba, Israel

    Shirley Gordon, Dror Garbi, Nitzan Shahar & Nachshon Meiran

  2. Mental Health Center, Beer Sheva, Ministry of Health, Beersheba, Zlotowski, Israel

    Doron Todder

  3. Center for Neuroscience, Ben-Gurion University of the Negev, Beersheba, Israel

    Doron Todder

  4. IDF Medical Corps, Tel Hashomer, Ramat Gan, Israel

    Shirley Gordon, Inbal Deutsch & Dror Garbi

  5. Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Beersheba, Israel

    Oren Alkobi, Oren Shriki & Anat Shkedy-Rabani

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Contributions

SG had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: SG, DT, and NM. Acquisition of data: SG, ID, and NS. Analysis and interpretation of data: all the authors. Drafting of the manuscript: SG, NM, ID and DT. Critical revision of the manuscript for important intellectual content: SG and NM. Statistical analysis: SG, OA, DG, NM and AS-R.

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Gordon, S., Todder, D., Deutsch, I. et al. Effects of neurofeedback and working memory-combined training on executive functions in healthy young adults. Psychological Research 84, 1586–1609 (2020). https://doi.org/10.1007/s00426-019-01170-w

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