Mu-Suppression Neurofeedback Training Targeting the Mirror Neuron System: A Pilot Study.
EEG
Mirror Neuron System
Mu Suppression
Neurofeedback
Journal
Applied psychophysiology and biofeedback
ISSN: 1573-3270
Titre abrégé: Appl Psychophysiol Biofeedback
Pays: Germany
ID NLM: 9712383
Informations de publication
Date de publication:
13 May 2024
13 May 2024
Historique:
medline:
13
5
2024
pubmed:
13
5
2024
entrez:
13
5
2024
Statut:
aheadofprint
Résumé
Neurofeedback training (NFT) is a promising adjuvant intervention method. The desynchronization of mu rhythm (8-13 Hz) in the electroencephalogram (EEG) over centro-parietal areas is known as a valid indicator of mirror neuron system (MNS) activation, which has been associated with social skills. Still, the effect of neurofeedback training on the MNS requires to be well investigated. The present study examined the possible impact of NFT with a mu suppression training protocol encompassing 15 NFT sessions (45 min each) on 16 healthy neurotypical participants. In separate pre- and post-training sessions, 64-channel EEG was recorded while participants (1) observed videos with various types of movements (including complex goal-directed hand movements and social interaction scenes) and (2) performed the "Reading the Mind in the Eyes Test" (RMET). EEG source reconstruction analysis revealed statistically significant mu suppression during hand movement observation across MNS-attributed fronto-parietal areas after NFT. The frequency analysis showed no significant mu suppression after NFT, despite the fact that numerical mu suppression appeared to be visible in a majority of participants during goal-directed hand movement observation. At the behavioral level, RMET accuracy scores did not suggest an effect of NFT on the ability to interpret subtle emotional expressions, although RMET response times were reduced after NFT. In conclusion, the present study exhibited preliminary and partial evidence that mu suppression NFT can induce mu suppression in MNS-attributed areas. More powerful experimental designs and longer training may be necessary to induce substantial and consistent mu suppression, particularly while observing social scenarios.
Identifiants
pubmed: 38739182
doi: 10.1007/s10484-024-09643-4
pii: 10.1007/s10484-024-09643-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Adolphs, R. (2003). Cognitive neuroscience of human social behaviour. Nature Reviews Neuroscience, 4(3), 165–178. https://doi.org/10.1038/nrn1056
doi: 10.1038/nrn1056
pubmed: 12612630
Alcala-Lopez, D., Vogeley, K., Binkofski, F., & Bzdok, D. (2019). Building blocks of social cognition: Mirror, mentalize, share? Cortex, 118, 4–18. https://doi.org/10.1016/j.cortex.2018.05.006
doi: 10.1016/j.cortex.2018.05.006
pubmed: 29903609
American Psychiatric, A., & American Psychiatric Association, D. S. M. T. F. (2013). Diagnostic and statistical manual of mental disorders : DSM-5 [1 online resource (xliv, 947 pages)](Fifth edition ed.). Retrieved from http://dsm.psychiatryonline.org/book.aspx?bookid=556
Avanzini, P., Fabbri-Destro, M., Dalla Volta, R., Daprati, E., Rizzolatti, G., & Cantalupo, G. (2012). The Dynamics of Sensorimotor Cortical Oscillations during the Observation of Hand Movements: An EEG Study. Plos One, 7(5), ARTN e37534. https://doi.org/10.1371/journal.pone.0037534
doi: 10.1371/journal.pone.0037534
Baron-Cohen, S., Wheelwright, S., Hill, J., Raste, Y., & Plumb, I. (2001). The “Reading the Mind in the Eyes” test revised version: A study with normal adults, and adults with Asperger syndrome or high-functioning autism. Journal of Child Psychology and Psychiatry, 42(2), 241–251. https://doi.org/10.1111/1469-7610.00715
doi: 10.1111/1469-7610.00715
pubmed: 11280420
Berger, H. (1929). Über das Elektrenkephalogramm des Menschen. Archiv Für Psychiatrie Und Nervenkrankheiten, 87(1), 527–570. https://doi.org/10.1007/BF01797193
doi: 10.1007/BF01797193
Britton, J. C., Phan, K. L., Taylor, S. F., Welsh, R. C., Berridge, K. C., & Liberzon, I. (2006). Neural correlates of social and nonsocial emotions: An fMRI study. NeuroImage, 31(1), 397–409. https://doi.org/10.1016/j.neuroimage.2005.11.027
doi: 10.1016/j.neuroimage.2005.11.027
pubmed: 16414281
Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. https://doi.org/10.1007/s00429-008-0195-z
doi: 10.1007/s00429-008-0195-z
pubmed: 18651173
Caspers, S., Amunts, K., & Zilles, K. (2012). Chapter 28 - Posterior Parietal Cortex: Multimodal Association Cortex. In J. K. Mai & G. Paxinos (Eds.), The Human Nervous System (Third Edition) (1036–1055)
Coben, R. (2008). Assessment guided neurofeedback for ASD: EEG analyses. Applied Psychophysiology and Biofeedback, 33(3), 176–176.
Coben, R., Sherlin, L., Hudspeth, W., McKeon, K., & Ricca, R. (2014). Connectivity-Guided EEG Biofeedback for Autism Spectrum Disorder: Evidence of Neurophysiological Changes (Vol. 1).
Cortese, S., Ferrin, M., Brandeis, D., Holtmann, M., Aggensteiner, P., Daley, D., & Zuddas, A. (2016). Neurofeedback for Attention-Deficit/Hyperactivity Disorder: Meta-Analysis of Clinical and Neuropsychological Outcomes From Randomized Controlled Trials. Journal of the American Academy of Child and Adolescent Psychiatry, 55(6), 444–455. https://doi.org/10.1016/j.jaac.2016.03.007
doi: 10.1016/j.jaac.2016.03.007
pubmed: 27238063
Datko, M., Pineda, J. A., & Muller, R. A. (2018). Positive effects of neurofeedback on autism symptoms correlate with brain activation during imitation and observation. European Journal of Neuroscience, 47(6), 579–591. https://doi.org/10.1111/ejn.13551
doi: 10.1111/ejn.13551
pubmed: 28245068
Falck-Ytter, T., Gredeback, G., & von Hofsten, C. (2006). Infants predict other people’s action goals. Nature Neuroscience, 9(7), 878–879. https://doi.org/10.1038/nn1729
doi: 10.1038/nn1729
pubmed: 16783366
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146
doi: 10.3758/bf03193146
pubmed: 17695343
Fox, N. A., Bakermans-Kranenburg, M. J., Yoo, K. H., Bowman, L. C., Cannon, E. N., Vanderwert, R. E.,...van Ijzendoorn, M. H. (2016). Assessing Human Mirror Activity With EEG Mu Rhythm: A Meta-Analysis. Psychological Bulletin, 142(3), 291–313. https://doi.org/10.1037/bul0000031
Freitag, C. M., Retz-Junginger, P., Retz, W., Seitz, C., Palmason, H., Meyer, J., & von Gontard, A. (2007). German adaptation of the autism-spectrum quotient (AQ): Evaluation and short version AQ-k. Zeitschrift Fur Klinische Psychologie Und Psychotherapie, 36(4), 280–289. https://doi.org/10.1026/1616-3443.36.4.280
doi: 10.1026/1616-3443.36.4.280
Friedrich, E. V. C., Sivanathan, A., Lim, T., Suttie, N., Louchart, S., Pillen, S., & Pineda, J. A. (2015). An effective neurofeedback intervention to improve social interactions in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 45(12), 4084–4100. https://doi.org/10.1007/s10803-015-2523-5
doi: 10.1007/s10803-015-2523-5
pubmed: 26210513
Gallese, V., Fadiga, L., Fogassi, L., & Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119, 593–609. https://doi.org/10.1093/brain/119.2.593
doi: 10.1093/brain/119.2.593
pubmed: 8800951
Grafton, S. T., & Hamilton, A. F. D. (2007). Evidence for a distributed hierarchy of action representation in the brain. Human Movement Science, 26(4), 590–616. https://doi.org/10.1016/j.humov.2007.05.009
doi: 10.1016/j.humov.2007.05.009
pubmed: 17706312
pmcid: 2042582
Haut, S. R., Gursky, J. M., & Privitera, M. (2019). Behavioral interventions in epilepsy. Current Opinion in Neurology, 32(2), 227–236. https://doi.org/10.1097/Wco.0000000000000661
doi: 10.1097/Wco.0000000000000661
pubmed: 30694921
Iacoboni, M., & Dapretto, M. (2006). The mirror neuron system and the consequences of its dysfunction. Nature Reviews Neuroscience, 7(12), 942–951. https://doi.org/10.1038/nrn2024
doi: 10.1038/nrn2024
pubmed: 17115076
Jackson, A., Mavoori, J., & Fetz, E. E. (2006). Long-term motor cortex plasticity induced by an electronic neural implant. Nature, 444(7115), 56–60. https://doi.org/10.1038/nature05226
doi: 10.1038/nature05226
pubmed: 17057705
Kilavik, B. E., Zaepffel, M., Brovelli, A., MacKay, W. A., & Riehle, A. (2013). The ups and downs of beta oscillations in sensorimotor cortex. Experimental Neurology, 245, 15–26. https://doi.org/10.1016/j.expneurol.2012.09.014
doi: 10.1016/j.expneurol.2012.09.014
pubmed: 23022918
Kloosterboer, S. M., de Winter, B. C. M., Reichart, C. G., Kouijzer, M. E. J., de Kroon, M. M. J., van Daalen, E., & Koch, B. C. P. (2020). Risperidone plasma concentrations are associated with side effects and effectiveness in children and adolescents with autism spectrum disorder. British Journal of Clinical Pharmacology. https://doi.org/10.1111/bcp.14465
doi: 10.1111/bcp.14465
pubmed: 32643213
Kouijzer, M. E. J., de Moor, J. M. H., Gerrits, B. J. L., Buitelaar, J. K., & van Schie, H. T. (2009a). Long-term effects of neurofeedback treatment in autism. Research in Autism Spectrum Disorders, 3(2), 496–501. https://doi.org/10.1016/j.rasd.2008.10.003
doi: 10.1016/j.rasd.2008.10.003
Kouijzer, M. E. J., de Moor, J. M. H., Gerrits, B. J. L., Congedo, M., & van Schie, H. T. (2009b). Neurofeedback improves executive functioning in children with autism spectrum disorders. Research in Autism Spectrum Disorders, 3(1), 145–162. https://doi.org/10.1016/j.rasd.2008.05.001
doi: 10.1016/j.rasd.2008.05.001
LaMarca, K., Gevirtz, R., Lincoln, A. J., & Pineda, J. A. (2023). Brain-Computer Interface Training of mu EEG Rhythms in Intellectually Impaired Children with Autism: A Feasibility Case Series. Applied Psychophysiology and Biofeedback. https://doi.org/10.1007/s10484-022-09576-w
doi: 10.1007/s10484-022-09576-w
pubmed: 36607454
Lepage, J. F., & Theoret, H. (2006). EEG evidence for the presence of an action observation-execution matching system in children. European Journal of Neuroscience, 23(9), 2505–2510. https://doi.org/10.1111/j.1460-9568.2006.04769.x
doi: 10.1111/j.1460-9568.2006.04769.x
pubmed: 16706857
Marshall, P. J., & Meltzoff, A. N. (2011). Neural mirroring systems: Exploring the EEG mu rhythm in human infancy. Developmental Cognitive Neuroscience, 1(2), 110–123. https://doi.org/10.1016/j.dcn.2010.09.001
doi: 10.1016/j.dcn.2010.09.001
pubmed: 21528008
McPheeters, M. L., Warren, Z., Sathe, N., Bruzek, J. L., Krishnaswami, S., Jerome, R. N., & Veenstra-VanderWeele, J. (2011). A Systematic Review of Medical Treatments for Children With Autism Spectrum Disorders. Pediatrics, 127(5), E1312–E1321. https://doi.org/10.1542/peds.2011-0427
doi: 10.1542/peds.2011-0427
pubmed: 21464191
Molenberghs, P., Johnson, H., Henry, J. D., & Mattingley, J. B. (2016). Understanding the minds of others: A neuroimaging meta-analysis. Neuroscience and Biobehavioral Reviews, 65, 276–291. https://doi.org/10.1016/j.neubiorev.2016.03.020
doi: 10.1016/j.neubiorev.2016.03.020
pubmed: 27073047
Muthukumaraswamy, S. D., & Johnson, B. W. (2004). Changes in rolandic mu rhythm during observation of a precision grip. Psychophysiology, 41(1), 152–156. https://doi.org/10.1046/j.1469-8986.2003.00129.x
doi: 10.1046/j.1469-8986.2003.00129.x
pubmed: 14693010
Oberman, L. M., Hubbard, E. M., McCleery, J. P., Altschuler, E. L., Ramachandran, V. S., & Pineda, J. A. (2005). EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Cognitive Brain Research, 24(2), 190–198. https://doi.org/10.1016/j.cogbrainres.2005.01.014
doi: 10.1016/j.cogbrainres.2005.01.014
pubmed: 15993757
Pandina, G., Ring, R. H., Bangerter, A., & Ness, S. (2020). Current Approaches to the Pharmacologic Treatment of Core Symptoms Across the Lifespan of Autism Spectrum Disorder. Child and Adolescent Psychiatric Clinics of North America, 29(2), 301. https://doi.org/10.1016/j.chc.2019.12.004
doi: 10.1016/j.chc.2019.12.004
pubmed: 32169264
Pfurtscheller, G., & da Silva, F. H. L. (1999). Event-related EEG/MEG synchronization and desynchronization: Basic principles. Clinical Neurophysiology, 110(11), 1842–1857. https://doi.org/10.1016/S1388-2457(99)00141-8
doi: 10.1016/S1388-2457(99)00141-8
pubmed: 10576479
Pineda, J. A., Brang, D., Hecht, E., Edwards, L., Carey, S., Bacon, M., & Rork, A. (2008). Positive behavioral and electrophysiological changes following neurofeedback training in children with autism. Research in Autism Spectrum Disorders, 2(3), 557–581. https://doi.org/10.1016/j.rasd.2007.12.003
doi: 10.1016/j.rasd.2007.12.003
Pineda, J. A., Carrasco, K., Datko, M., Pillen, S., & Schalles, M. (2014). Neurofeedback training produces normalization in behavioural and electrophysiological measures of high-functioning autism. Philosophical Transactions of the Royal Society B-Biological Sciences, 369(1644), 10. https://doi.org/10.1098/rstb.2013.0183
doi: 10.1098/rstb.2013.0183
Ritterband-Rosenbaum, A., Herskind, A., Li, X., Willerslev-Olsen, M., Olsen, M. D., Farmer, S. F., & Nielsen, J. B. (2017). A critical period of corticomuscular and EMG-EMG coherence detection in healthy infants aged 9–25weeks. Journal of Physiology-London, 595(8), 2699–2713. https://doi.org/10.1113/Jp273090
doi: 10.1113/Jp273090
Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169–192. https://doi.org/10.1146/annurev.neuro.27.070203.144230
doi: 10.1146/annurev.neuro.27.070203.144230
pubmed: 15217330
Rizzolatti, G., Cattaneo, L., Fabbri-Destro, M., & Rozzi, S. (2014). Cortical Mechanisms Underlying the Organization of Goal-Directed Actions and Mirror Neuron-Based Action Understanding. Physiological Reviews, 94(2), 655–706. https://doi.org/10.1152/physrev.00009.2013
doi: 10.1152/physrev.00009.2013
pubmed: 24692357
Schurz, M., Radua, J., Aichhorn, M., Richlan, F., & Perner, J. (2014). Fractionating theory of mind: A meta-analysis of functional brain imaging studies. Neuroscience and Biobehavioral Reviews, 42, 9–34. https://doi.org/10.1016/j.neubiorev.2014.01.009
doi: 10.1016/j.neubiorev.2014.01.009
pubmed: 24486722
Shindo, K., Kawashima, K., Ushiba, J., Ota, N., Ito, M., Ota, T., & Liu, M. G. (2011). Effects of Neurofeedback Training with an Electroencephalogram-Based Brain-Computer Interface for Hand Paralysis in Patients with Chronic Stroke: A Preliminary Case Series Study. Journal of Rehabilitation Medicine, 43(10), 951–957. https://doi.org/10.2340/16501977-0859
doi: 10.2340/16501977-0859
pubmed: 21947184
Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., & Sulzer, J. (2017). Closed-loop brain training: The science of neurofeedback. Nature Reviews Neuroscience, 18(2), 86–100. https://doi.org/10.1038/nrn.2016.164
doi: 10.1038/nrn.2016.164
pubmed: 28003656
Tadel, F., Baillet, S., Mosher, J. C., Pantazis, D., & Leahy, R. M. (2011). Brainstorm: a user-friendly application for MEG/EEG analysis. Computational intelligence and neuroscience, 2011, 879716. https://doi.org/10.1155/2011/879716
doi: 10.1155/2011/879716
pubmed: 21584256
pmcid: 3090754
Thompson, L., Thompson, M., & Reid, A. (2010). Neurofeedback Outcomes in Clients with Asperger’s Syndrome. Applied Psychophysiology and Biofeedback, 35(1), 63–81. https://doi.org/10.1007/s10484-009-9120-3
doi: 10.1007/s10484-009-9120-3
pubmed: 19908142
Trambaiolli, L. R., Cassani, R., Mehler, D. M. A., & Falk, T. H. (2021). Neurofeedback and the Aging Brain: A Systematic Review of Training Protocols for Dementia and Mild Cognitive Impairment. Frontiers in Aging Neuroscience, 13, ARTN 682683. https://doi.org/10.3389/fnagi.2021.682683
doi: 10.3389/fnagi.2021.682683
Umilta, M. A., Kohler, E., Gallese, V., Fogassi, L., Fadiga, L., Keysers, C., & Rizzolatti, G. (2001). I know what you are doing: A neurophysiological study. Neuron, 31(1), 155–165. https://doi.org/10.1016/S0896-6273(01)00337-3
doi: 10.1016/S0896-6273(01)00337-3
pubmed: 11498058
Uusitalo, M. A., & Ilmoniemi, R. J. (1997). Signal-space projection method for separating MEG or EEG into components. Medical and Biological Engineering & Computing, 35(2), 135–140. https://doi.org/10.1007/Bf02534144
doi: 10.1007/Bf02534144
Van Doren, J., Arns, M., Heinrich, H., Vollebregt, M. A., Strehl, U., & Loo, S. K. (2019). Sustained effects of neurofeedback in ADHD: A systematic review and meta-analysis. European Child & Adolescent Psychiatry, 28(3), 293–305. https://doi.org/10.1007/s00787-018-1121-4
doi: 10.1007/s00787-018-1121-4
Weber, L. A., Ethofer, T., & Ehlis, A. C. (2020). Predictors of neurofeedback training outcome: A systematic review. Neuroimage-Clinical, 27, ARTN 102301. https://doi.org/10.1016/j.nicl.2020.102301
doi: 10.1016/j.nicl.2020.102301
Young, K. D., Siegle, G. J., Zotev, V., Phillips, R., Misaki, M., Yuan, H., & Bodurka, J. (2017). Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effectson Symptoms and Autobiographical Memory Recall. American Journal of Psychiatry, 174(8), 748–755. https://doi.org/10.1176/appi.ajp.2017.16060637
doi: 10.1176/appi.ajp.2017.16060637
pubmed: 28407727