Actualidades en Psicología ISSN Impreso: 0258-6444 ISSN electrónico: 2215-3535

OAI: https://revistas.ucr.ac.cr/index.php/actualidades/oai
Application of a mental imagery protocol for the promotion of implicit learning in university students
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Keywords

aprendizaje implícito
imaginería mental
tarea de tiempo de reacción serial
electroencefalografía
ondas Mu
implicit learning
mental imagery
serial reaction time task
electroencephalography
Mu waves

How to Cite

Mora-Benambourg, J. M., & Marín-Picado, B. (2024). Application of a mental imagery protocol for the promotion of implicit learning in university students . Actualidades En Psicología, 38(136), 77–87. https://doi.org/10.15517/ap.v38i136.49097

Abstract

Objective. The improvement of cognitive skills has become an issue of particular interest nowadays. It is still being determined if techniques like mental imagery (MI) could generate cognitive enhancement via modulation of neural brain activity. This study aimed to provide information on the impact of mental imagery on implicit motor learning. Method. To test this hypothesis, an MI protocol was applied to an experimental group before performing an implicit learning (IL) task, while a control group received a sham feedback protocol. In addition, to have empirical evidence of cortical activation during MI, we made an electroencephalographic (EEG) record of motor cortex activity during baseline and during the task associated with IL. Results. The ANCOVA models all together show how the MI protocol does impact the IL process, but not as clearly as expected.

https://doi.org/10.15517/ap.v38i136.49097
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References

Aliño, M., Gadea, M., & Espert, R. (2016). A critical view of neurofeedback experimental designs: sham and control as necessary conditions. International Journal Neurology and Neurotherapy, 3(1), 1-2. https://doi.org/10.23937/2378-3001/3/1/1041

BrainMaster Technologies, Inc. (2012). BrainMaster 2.5 Software User Manual. BrainMaster Technologies, Inc.

Benedek, M., Bergner, S., Könen, T., Fink, A., & Neubauer, A. (2011). EEG alpha synchronization is related to top-down processing in convergent and divergent thinking. Neuropsychologia, 49(12), 3505-3511. https://doi.org/10.1016/j.neuropsychologia.2011.09.004

Bostrom, N., & Sandberg, A. (2009). Cognitive Enhancement: Methods, ethics, regulatory challenges. Science and Engineering Ethics, 15(3), 311-341. https://doi.org/10.1007/s11948-009-9142-5

Caligiore, D., Mustile, M., Spalletta, G., & Baldassarre, G. (2017). Action observation and motor imagery for rehabilitation in Parkinson´s disease: A systematic review and integrative hypothesis. Neuroscience and Biobehavioral Reviews, 72, 210-222. http://dx.doi.org/10.1016/j.neubiorev.2016.11.005

Curran, T., & Schacter, D. (2001). Implicit learning and memory: Psychological and neural aspects. International Encyclopedia of the Social & Behavior Sciences, 7237-7241. https://doi.org/10.1016/B0-08-043076-7/03513-0

Dahm, S. & Rieger, M. (2016). Is there symmetry in motor imagery? Exploring different versions of the mental chronometry paradigm. Attention, Perception, & Psychophysics, 78, 1794-1805. https://doi.org/10.3758/s13414-016-1112-9

Dubljević, V., Venero, C., & Knafo, S. (2015). What is Cognitive Enhancement? En S. Knafo & C. Venero (Eds.), Cognitive Enhancement: Pharmacologic, Environmental and Genetic Factors (pp. 1-9). Academic Press.

Gallant, C., Drumheller, A., & Mckelvie, S. (2016). Effect of improper soccer heading on serial reaction time task performance. Current Psychology, 36, 286-296. https://doi.org/10.1007/s12144-016-9414-6

Gentili, R., & Papaxanthis, C. (2015). Laterality effects in motor learning by mental practice in right handers. Neuroscience, 297, 231-242. http://dx.doi.org/10.1016/j.neuroscience.2015.02.055

Hardwick, R. M., Caspers, S., Eickhoff, S. B., & Swinnen, S. P. (2018). Neural correlates of action: Comparing meta-analyses of imagery, observation, and execution. Neuroscience & Biobehavioral Reviews, 94, 31-44. https://doi.org/10.1016/j.neubiorev.2018.08.003

Helwig, N.E. (2018). eegkit: Toolkit for Electroencephalography Data. https://CRAN.R-project.org/package=eegkit

López-Ramón, M., Introzzi, I., & Richard’s, M. (2009). La independencia del aprendizaje implícito con respecto a la inteligencia general en niños de edad escolar. Anales de Psicología, 25(1), 112-122. https://revistas.um.es/analesps/article/view/71561

Kim, Y., Park, E., Lee, A., Im, C., & Kim, Y. (2018). Changes in network connectivity during motor imagery and execution. PLoS ONE, 13(1), e0190715. https://doi.org/10.1371/journal.pone.0190715

Ladda, A. M., Lebon, F., & Lotze, M. (2021). Using motor imagery practice for improving motor performance - A review. Brain and Cognition, 150, 105705. https://doi.org/10.1016/j.bandc.2021.105705

Leap Motion Developer (2016, 28 de julio). API Overview. https://developer.leapmotion.com/documentation/v2/python/devguide/Leap_Overview.html

Lebon, F., Horn, U., Domin, M., & Lotze, M. (2018). Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation. Human Brain Mapping, 39(4), 1805-1813. https://doi.org/10.1002/hbm.23956

Lewkowicz, D., Delevoye-Turrell, Y., Bailly, D., Andry, P., & Gaussier, P. (2013). Reading motor intention through mental imagery. Adaptative Behavior, 21(5), 315-420. https://doi.org/10.1177/1059712313501347

Marcuse, L., Fields, M., & Yoo, J. (2016). Rowan’s Primer of EEG. Elsevier.

Nissen, M., & Bullemer, P. (1987). Attentional requirements of learning: evidence from performance measures. Cognitive Psychology, 19(1), 1-32. https://doi.org/10.1016/0010-0285(87)90002-8

Poldrack, R., Sabb, F. W., Foerde, K., Tom, S. M., Asarnow, R. F., Bookheimer, S. Y., & Knowlton, B. J. (2005). The neural correlates of motor skill automaticity. Journal of Neuroscience, 25(22), 5356-5364. https://doi.org/10.1523/JNEUROSCI.3880-04.2005

R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/.

Racine, E., Sattler, S., & Boehlen, W. (2021). Cognitive enhancement: Unanswered questions about human psychology and social behavior. Science and Engineering Ethics, 27(19), 1-25. https://doi.org/10.1007/s11948-021-00294-w

Reber, J., Batterink, L., Thompson, K., & Reuveni, B. (2019). Implicit learning: history and applications. En A. Cleeremans, V. Allakhverdov & M. Kuvaldina (Eds.), Implicit Learning: 50 Years (pp. 16-37). Routledge.

Revelle, W. (2018). psych: Procedures for Psychological, Psychometric, and Personality Research. Northwestern University, Evanston, Illinois. https://CRAN.R-project.org/package=psych

Robertson, E. (2007). The serial reaction time task: Implicit motor skill learning? The Journal of Neuroscience, 27(38), 1073-1075. https://doi.org/10.1523/JNEUROSCI.2747-07.2007

Ros, T., Munneke, M., Parkinson, L., & Gruzelier, J. (2014). Neurofeedback facilitation of implicit motor learning. Biological Psychology, 95, 54-58. http://dx.doi.org/10.1016/j.biopsycho.2013.04.013

Schack, T., Essig, K., Frank, C., & Koester, D. (2014). Mental representation and motor imagery training. Frontiers in Human Neuroscience, 8, 1-10. https://doi.org/110.3389/fnhum.2014.00328

Toth, A. J., McNeill, E., Hayes, K., Moran, A. P., & Campbell, M. (2020). Does mental practice still enhance performance? A 24 year follow-up and meta-analytic replication and extension. Psychology of Sport and Exercise, 48, 101672. https://doi.org/10.1016/j.psychsport.2020.101672

Van Dyck, D., Deconinck, N., Aeby, A., Baijot, S., Coquelet, N., Trotta, N., Rovai, A., Goldman, S., Urbain, C., Wens, V., & De Tiège, X. (2021). Resting-state functional brain connectivity is related to subsequent procedural learning skills in school-aged children. NeuroImage, 240, 118368. https://doi.org/10.1016/j.neuroimage.2021.118368

Vinicius M., Catelli, A., & Cagy M. (2010). EEG changes during sequences of visual and khinesthetic motor imaginery. Arq Neuropsiquiat., 68(4), 556-561. https://doi.org/10.1590/s0004-282x2010000400015

Unsworth, N., & Engle, R. (2005). Individual differences in working memory capacity and learning: Evidence from the serial reaction time task. Memory & Cognition, 33(2), 213-220. https://doi.org/10.3758/bf03195310

Wilkinson, L., Teo, J., Obeso, I., Rothwell, J., & Jahanshashi, M. (2010). The contribution of primary motor cortex is essential for probabilistic implicit sequence learning: evidence from theta burst magnetic stimulation. Journal of Cognitive Neuroscience, 22(3), 427-436. https://doi.org/10.1162/jocn.2009.21208

Williams, J., Pearce, A. J., Loporto, M., Morris, T., & Holmes, P. S. (2012). The relationship between corticospinal excitability during motor imagery and motorimagery ability. Behavioural Brain Research, 226(2), 369–375. https://doi.org/10.1016/j.bbr.2011.09.014

Wiestler, T., & Diedrichsen, J. (2013). Skill learning strengthens cortical representations of motor sequences. eLlife, 2, e00801. https://doi.org/10.7554/eLife.00801

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Copyright (c) 2024 José Manuel Mora-Benambourg, Bradly Marín-Picado

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