Improving cognitive control: Is theta neurofeedback training associated with proactive rather than reactive control enhancement?

cognitive control executive functions frontal-midline theta neurofeedback training working memory

Journal

Psychophysiology
ISSN: 1540-5958
Titre abrégé: Psychophysiology
Pays: United States
ID NLM: 0142657

Informations de publication

Date de publication:
05 2022
Historique:
revised: 28 04 2021
received: 09 10 2020
accepted: 11 05 2021
pubmed: 8 7 2021
medline: 13 4 2022
entrez: 7 7 2021
Statut: ppublish

Résumé

Frontal-midline (FM) theta activity (4-8 Hz) is proposed to reflect a mechanism for cognitive control that is needed for working memory retention, manipulation, and interference resolution. Modulation of FM theta activity via neurofeedback training (NFT) demonstrated transfer to some but not all types of cognitive control. Therefore, the present study investigated whether FM theta NFT enhances performance and modulates underlying EEG characteristics in a delayed match to sample (DMTS) task requiring mainly proactive control and a color Stroop task requiring mainly reactive control. Moreover, temporal characteristics of transfer were explored over two posttests. Across seven 30-min NFT sessions, an FM theta training group exhibited a larger FM theta increase compared to an active control group who upregulated randomly chosen frequency bands. In a posttest performed 13 days after the last training session, the training group showed better retention performance in the DMTS task. Furthermore, manipulation performance was associated with NFT theta increase for the training but not the control group. Contrarily, behavioral group differences and their relation to FM theta change were not significant in the Stroop task, suggesting that NFT is associated with proactive but not reactive control enhancement. Transfer to both tasks at a posttest one day after training was not significant. Behavioral improvements were not accompanied by changes in FM theta activity, indicating no training-induced modulation of EEG characteristics. Together, these findings suggest that NFT supports transfer to cognitive control that manifests late after training but that other training-unspecific factors may also contribute to performance enhancement.

Identifiants

pubmed: 34231223
doi: 10.1111/psyp.13873
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e13873

Subventions

Organisme : Wellcome Trust
ID : AC1710IF09
Pays : United Kingdom

Informations de copyright

© 2021 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.

Références

Alkoby, O., Abu-Rmileh, A., Shriki, O., & Todder, D. (2018). Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience, 378, 155-164. https://doi.org/10.1016/j.neuroscience.2016.12.050
Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., Kong, E., Larraburo, Y., Rolle, C., Johnston, E., & Gazzaley, A. (2013). Video game training enhances cognitive control in older adults. Nature, 501(7465), 97-101. https://doi.org/10.1038/nature12486
Berger, B., Minarik, T., Griesmayr, B., Stelzig-Schoeler, R., Aichhorn, W., & Sauseng, P. (2016). Brain oscillatory correlates of altered executive functioning in positive and negative symptomatic schizophrenia patients and healthy controls. Frontiers in Psychology, 7, 1-14. https://doi.org/10.3389/fpsyg.2016.00705
Braver, T. S. (2012). The variable nature of cognitive control: A dual mechanisms framework. Trends in Cognitive Sciences, 16(2), 106-113. https://doi.org/10.1016/j.tics.2011.12.010
Braver, T. S., & Cohen, J. D. (2001). Working memory, cognitive control, and the prefrontal cortex: Computational and empirical studies. Cognitive Processing, 2(1), 25-55.
Braver, T. S., Kizhner, A., Tang, R., Freund, M. C., & Etzel, J. A. (2020). The dual mechanisms of cognitive control (DMCC) project. BioRxiv. https://doi.org/10.1101/2020.09.18.304402
Buschkuehl, M., Jaeggi, S. M., & Jonides, J. (2012). Neuronal effects following working memory training. Developmental Cognitive Neuroscience, 2, S167-S179. https://doi.org/10.1016/j.dcn.2011.10.001
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414-421. https://doi.org/10.1016/j.tics.2014.04.012
Cavanagh, J. F., Zambrano-Vazquez, L., & Allen, J. J. B. (2012). Theta lingua franca: A common mid-frontal substrate for action monitoring processes. Psychophysiology, 49(2), 220-238. https://doi.org/10.1111/j.1469-8986.2011.01293.x
Cohen, M. X., & Cavanagh, J. F. (2011). Single-trial regression elucidates the role of prefrontal theta oscillations in response conflict. Frontiers in Psychology, 2, 1-12. https://doi.org/10.3389/fpsyg.2011.00030
Cooper, P. S., Wong, A. S. W., Fulham, W. R., Thienel, R., Mansfield, E., Michie, P. T., & Karayanidis, F. (2015). Theta frontoparietal connectivity associated with proactive and reactive cognitive control processes. NeuroImage, 108, 354-363. https://doi.org/10.1016/j.neuroimage.2014.12.028
Cooper, P. S., Wong, A. S. W., McKewen, M., Michie, P. T., & Karayanidis, F. (2017). Frontoparietal theta oscillations during proactive control are associated with goal-updating and reduced behavioral variability. Biological Psychology, 129, 253-264. https://doi.org/10.1016/j.biopsycho.2017.09.008
Dahlin, E., Neely, A. S., Larsson, A., Bäckman, L., & Nyberg, L. (2008). Transfer of learning after updating training mediated by the striatum. Science, 320(5882), 1510-1512. https://doi.org/10.1126/science.1155466
Davelaar, E. J. (2018). Mechanisms of neurofeedback: A computation-theoretic approach. Neuroscience, 378, 175-188. https://doi.org/10.1016/j.neuroscience.2017.05.052
Dessy, E., Van Puyvelde, M., Mairesse, O., Neyt, X., & Pattyn, N. (2018). Cognitive performance enhancement: Do biofeedback and neurofeedback work? Journal of Cognitive Enhancement, 2(1), 12-42. https://doi.org/10.1007/s41465-017-0039-y
Enriquez-Geppert, S., Huster, R. J., Figge, C., & Herrmann, C. S. (2014). Self-regulation of frontal-midline theta facilitates memory updating and mental set shifting. Frontiers in Behavioral Neuroscience, 8, 1-13. https://doi.org/10.3389/fnbeh.2014.00420
Enriquez-Geppert, S., Huster, R. J., & Herrmann, C. S. (2017). EEG-neurofeedback as a tool to modulate cognition and behavior: A review tutorial. Frontiers in Human Neuroscience, 11, 1-19. https://doi.org/10.3389/fnhum.2017.00051
Eschmann, K. C. J., Bader, R., & Mecklinger, A. (2018). Topographical differences of frontal-midline theta activity reflect functional differences in cognitive control abilities. Brain and Cognition, 123, 57-64. https://doi.org/10.1016/j.bandc.2018.02.002
Eschmann, K. C. J., Bader, R., & Mecklinger, A. (2020). Improving episodic memory: Frontal-midline theta neurofeedback training increases source memory performance. NeuroImage, 222, 117219. https://doi.org/10.1016/j.neuroimage.2020.117219
Gaume, A., Vialatte, A., Mora-Sánchez, A., Ramdani, C., & Vialatte, F. B. (2016). A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback. Neuroscience & Biobehavioral Reviews, 68, 891-910. https://doi.org/10.1016/j.neubiorev.2016.06.012
Gonthier, C., Braver, T. S., & Bugg, J. M. (2016). Dissociating proactive and reactive control in the Stroop task. Memory and Cognition, 44(5), 778-788. https://doi.org/10.3758/s13421-016-0591-1
Griefahn, B., Kunemund, C., Brode, P., & Mehnert, P. (2001). The validity of a German version of the morningness-eveningness-questionnaire developed by Horne and Östberg. Somnologie, 5(2), 71-80. https://doi.org/10.1046/j.1439-054X.2001.01149.x
Griesmayr, B., Berger, B., Stelzig-Schoeler, R., Aichhorn, W., Bergmann, J., & Sauseng, P. (2014). EEG theta phase coupling during executive control of visual working memory investigated in individuals with schizophrenia and in healthy controls. Cognitive, Affective, & Behavioral Neuroscience, 14(4), 1340-1355. https://doi.org/10.3758/s13415-014-0272-0
Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. III: A review of methodological and theoretical considerations. Neuroscience and Biobehavioral Reviews, 44, 159-182. https://doi.org/10.1016/j.neubiorev.2014.03.015
Hanslmayr, S., Pastötter, B., Bäuml, K.-H., Gruber, S., Wimber, M., & Klimesch, W. (2008). The electrophysiological dynamics of interference during the Stroop task. Journal of Cognitive Neuroscience, 20(2), 215-225. https://doi.org/10.1162/jocn.2008.20020
Helfrich, R. F., & Knight, R. T. (2016). Oscillatory dynamics of prefrontal cognitive control. Trends in Cognitive Sciences, 20(12), 916-930. https://doi.org/10.1016/j.tics.2016.09.007
Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174-180. https://doi.org/10.1016/j.tics.2012.01.006
Hsieh, L.-T., & Ranganath, C. (2014). Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval. NeuroImage, 85, 721-729. https://doi.org/10.1016/j.neuroimage.2013.08.003
Jensen, O., & Tesche, C. D. (2002). Frontal theta activity in humans increases with memory load in a working memory task. European Journal of Neuroscience, 15, 1395-1399. https://doi.org/10.1046/j.1460-9568.2002.01975.x
Jonides, J. (2004). How does practice makes perfect? Nature Neuroscience, 7(1), 10-11. https://doi.org/10.1038/nn0104-10
Karbach, J., & Kray, J. (2009). How useful is executive control training? Age differences in near and far transfer of task-switching training. Developmental Science, 12(6), 978-990. https://doi.org/10.1111/j.1467-7687.2009.00846.x
Kelly, A. C., & Garavan, H. (2005). Human functional neuroimaging of brain changes associated with practice. Cerebral Cortex, 15(8), 1089-1102. https://doi.org/10.1093/cercor/bhi005
Klimesch, W., Freunberger, R., Sauseng, P., & Gruber, W. (2008). A short review of slow phase synchronization and memory: Evidence for control processes in different memory systems? Brain Research, 1235, 31-44. https://doi.org/10.1016/j.brainres.2008.06.049
Klingberg, T. (2010). Training and plasticity of working memory. Trends in Cognitive Sciences, 14(7), 317-324. https://doi.org/10.1016/j.tics.2010.05.002
Lindenberger, U., Wenger, E., & Lövdén, M. (2017). Towards a stronger science of human plasticity. Nature Reviews Neuroscience, 18(5), 261-262. https://doi.org/10.1038/nrn.2017.44
Lövdén, M., Bäckman, L., Lindenberger, U., Schaefer, S., & Schmiedek, F. (2010). A theoretical framework for the study of adult cognitive plasticity. Psychological Bulletin, 136(4), 659-676. https://doi.org/10.1037/a0020080
Lustig, C., & Flegal, K. E. (2008). Targeting latent function: Encouraging effective encoding for successful memory training and transfer. Psychology and Aging, 23(4), 754-764. https://doi.org/10.1037/a0014295
Mahalanobis, P. C. (1936). On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India B. Biological Sciences, 2(1), 49-55.
Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49(2), 270-291. https://doi.org/10.1037/a0028228
Morrison, A. B., & Chein, J. M. (2011). Does working memory training work? The promise and challenges of enhancing cognition by training working memory. Psychonomic Bulletin & Review, 18(1), 46-60. https://doi.org/10.3758/s13423-010-0034-0
Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., & Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12(2), 241-268. https://doi.org/10.3758/s13415-011-0083-5
Nigbur, R., Ivanova, G., & Stürmer, B. (2011). Theta power as a marker for cognitive interference. Clinical Neurophysiology, 122(11), 2185-2194. https://doi.org/10.1016/j.clinph.2011.03.030
Ninaus, M., Kober, S. E., Witte, M., Koschutnig, K., Stangl, M., Neuper, C., Wood, G., & Jasinska, A. J. (2013). Neural substrates of cognitive control under the belief of getting neurofeedback training. Frontiers in Human Neuroscience, 7, 1-10. https://doi.org/10.3389/fnhum.2013.00914
Ofen-Noy, N., Dudai, Y., & Karni, A. (2003). Skill learning in mirror reading: How repetition determines acquisition. Cognitive Brain Research, 17(2), 507-521. https://doi.org/10.1016/S0926-6410(03)00166-6
Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97-113. https://doi.org/10.1016/0028-3932(71)90067-4
Onton, J., Delorme, A., & Makeig, S. (2005). Frontal midline EEG dynamics during working memory. NeuroImage, 27(2), 341-356. https://doi.org/10.1016/j.neuroimage.2005.04.014
Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., Howard, R. J., & Ballard, C. G. (2010). Putting brain training to the test. Nature, 465(7299), 775-778. https://doi.org/10.1038/nature09042
Reiner, M., Rozengurt, R., & Barnea, A. (2014). Better than sleep: Theta neurofeedback training accelerates memory consolidation. Biological Psychology, 95, 45-53. https://doi.org/10.1016/j.biopsycho.2013.10.010
Reis, J., Portugal, A. M., Fernandes, L., Afonso, N., Pereira, M., Sousa, N., & Dias, N. S. (2016). An alpha and theta intensive and short neurofeedback protocol for healthy aging working-memory training. Frontiers in Aging Neuroscience, 8, 1-11. https://doi.org/10.3389/fnagi.2016.00157
Ros, T., Baars, B. J., Lanius, R. A., & Vuilleumier, P. (2014). Tuning pathological brain oscillations with neurofeedback: A systems neuroscience framework. Frontiers in Human Neuroscience, 8, 1-22. https://doi.org/10.3389/fnhum.2014.01008
Rozengurt, R., Barnea, A., Uchida, S., & Levy, D. A. (2016). Theta EEG neurofeedback benefits early consolidation of motor sequence learning. Psychophysiology, 53(7), 965-973. https://doi.org/10.1111/psyp.12656
Rozengurt, R., Shtoots, L., Sheriff, A., Sadka, O., & Levy, D. A. (2017). Enhancing early consolidation of human episodic memory by theta EEG neurofeedback. Neurobiology of Learning and Memory, 145, 165-171. https://doi.org/10.1016/j.nlm.2017.10.005
Sauseng, P., Griesmayr, B., Freunberger, R., & Klimesch, W. (2010). Control mechanisms in working memory: A possible function of EEG theta oscillations. Neuroscience & Biobehavioral Reviews, 34(7), 1015-1022. https://doi.org/10.1016/j.neubiorev.2009.12.006
Sauseng, P., Hoppe, J., Klimesch, W., Gerloff, C., & Hummel, F. C. (2007). Dissociation of sustained attention from central executive functions: Local activity and interregional connectivity in the theta range. European Journal of Neuroscience, 25(2), 587-593. https://doi.org/10.1111/j.1460-9568.2006.05286.x
Schneiders, J. A., Opitz, B., Krick, C. M., & Mecklinger, A. (2011). Separating intra-modal and across-modal training effects in visual working memory: An fMRI investigation. Cerebral Cortex, 21(11), 2555-2564. https://doi.org/10.1093/cercor/bhr037
Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103-186. https://doi.org/10.1177/1529100616661983
Töllner, T., Wang, Y., Makeig, S., Müller, H. J., Jung, T.-P., & Gramann, K. (2017). Two independent frontal midline theta oscillations during conflict detection and adaptation in a Simon-type manual reaching task. Journal of Neuroscience, 37(9), 2504-2515. https://doi.org/10.1523/JNEUROSCI.1752-16.2017
Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley.
Veltman, D. J., Rombouts, S. A. R. B., & Dolan, R. J. (2003). Maintenance versus manipulation in verbal working memory revisited: An fMRI study. NeuroImage, 18(2), 247-256. https://doi.org/10.1016/S1053-8119(02)00049-6
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
Wang, J.-R., & Hsieh, S. (2013). Neurofeedback training improves attention and working memory performance. Clinical Neurophysiology, 124(12), 2406-2420. https://doi.org/10.1016/j.clinph.2013.05.020
Wenger, E., Brozzoli, C., Lindenberger, U., & Lövdén, M. (2017). Expansion and renormalization of human brain structure during skill acquisition. Trends in Cognitive Sciences, 21(12), 930-939. https://doi.org/10.1016/j.tics.2017.09.008
Wenger, E., Kühn, S., Verrel, J., Mårtensson, J., Bodammer, N. C., Lindenberger, U., & Lövdén, M. (2017). Repeated structural imaging reveals nonlinear progression of experience-dependent volume changes in human motor cortex. Cerebral Cortex, 27(5), 2911-2925. https://doi.org/10.1093/cercor/bhw141
Zuure, M. B., Hinkley, L. B., Tiesinga, P. H. E., Nagarajan, S. S., & Cohen, M. X. (2020). Multiple midfrontal thetas revealed by source separation of simultaneous MEG and EEG. Journal of Neuroscience, 40(40), 7702-7713. https://doi.org/10.1523/JNEUROSCI.0321-20.2020
Zysset, S., Mu, K., Lohmann, G., & Von Cramon, D. Y. (2001). Color-word matching Stroop task: Separating interference and response conflict. NeuroImage, 36(1), 29-36. https://doi.org/10.1006/nimg.2000.0665

Auteurs

Kathrin C J Eschmann (KCJ)

Experimental Neuropsychology Unit, Department of Psychology, Saarland University, Saarbrücken, Germany.
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.

Axel Mecklinger (A)

Experimental Neuropsychology Unit, Department of Psychology, Saarland University, Saarbrücken, Germany.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH