Effect of Training with Transcranial Electrical Stimulation with Random Noise on Brain Waves and Temporal/Spatial Components in Learning a Perceptual-Motor Task

Document Type : Original Article

Authors

Department of Motor Behavior and sport psychology, Faculty of Sport Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran

Abstract

Purpose: The present study aimed to investigate the effects of combining tRNS with exercise on brain waves and the enhancement of temporal and spatial components in perceptual-motor task learning.
Methods: This semi-experimental research utilized a pretest-acquisition-posttest design. Based on the literature review, 30 male students (mean age 22.62 ± 62) were randomly divided into three experimental groups (1- tRNS combined with motor training, 2- sham tRNS combined with motor training, 3- motor training). Participants completed a movement task of drawing a circle in three phases: pretest (10 trials), intervention (one day after pretest; 6 sessions with 5 blocks of 10 attempts each), post-test (one day after intervention, 10 trials). Each trial ended after drawing 20 laps of the circle. Data were analyzed using descriptive statistics, Shapiro-Wilk test for data distribution normality, one-way analysis of variance with repeated measurements, Bonferroni follow-up test, Kruskal-Wallis, and Friedman tests.
Results: Statistical analysis using SPSS software revealed that tRNS improved beta rhythm and sensorimotor rhythm (SMR) power (P=0.001). Additionally, tRNS significantly reduced spatial error and movement execution time (P=0.001). The effect of tRNS on movement time was observed after six sessions, while the effect on spatial error was evident after three sessions.
Conclusion: The results suggest that tRNS is an effective approach to decrease movement errors, enhance movement timing, and improve fine motor performance. Three training sessions with tRNS were adequate to reduce spatial error, but more sessions were required to reduce temporal error.
 

Keywords

Main Subjects


  1. Sternad D. It’s not (only) the mean that matters: variability, noise and exploration in skill learning. Behavioral Sciences, 2018, 20:183–195. Retrieved from. https://doi.org/10.1016/j.cobeha.2018.01.004
  2. Huber ME, Kuznetsov N, Sternad D. Persistence of reduced neuromotor noise in long-term motor skill learning. Journal of Neurophysiology, 2016, 116(6), 2922-35. https://doi.org/10.1152%2Fjn.00263.2016
  3. Cohen RG, Sternad D. Variability in motor learning: relocating, channeling and reducing noise. Exp Brain Res, 2009, 193(1): 69–83. 1007/s00221-008-1596-1.
  4. He K, Liang Y, Abdollahi F, Bittman MF, Kording K, Wei K The statistical determinants of the speed of motor learning. PloS Comput Biol, 2016, 12(9):e1005023. https://doi.org/10.1371/journal.pcbi.1005023
  5. Van der Kooij K, van Mastrigt NM, Cashaback JG. Failure induces task-irrelevant exploration during a stencil task. Experimental Brain Research, 2023, 1-10.

https://doi.org/10.1007/s00221-023-06548-2

  1. Hatfield BD, Hillman CH. The psychophysiology of sport: A mechanistic understanding of the psychology of superior performance. Handbook of sport psychology, 2001, 2, 362-386.
  2. Hatfield BD. Brain dynamics and motor behavior: A case for efficiency and refinement for superior performance. Kinesiology Review, 2018, 7(1), 42–50. https://doi.org/10.1123/kr.2017-0056
  3. Cheng MY, Hung CL, Huang CJ, Chang YK, Lo LC, Shen C, Hung TM. Expert-novice differences in SMR activity during dart throwing. Biological Psychology, 2015, 110, 212–218.

https://doi.org/10.1016/j.biopsycho.2015.08.003

  1. Cooke A. Readying the head and steadying the heart: A review of cortical and cardiac studies of preparation for action in sport. International Review of Sport and Exercise Psychology, 2013, 6(1), 122–138. https://doi.org/10.1080/1750984X.2012. 724438
  2. Hamilos AS et al. Dynamic dopaminergic activity controls the timing of self-timed movement. bioRxiv 05.13.094904; https://doi.org/10.1101/2020.05.13.094904
  3. Pearce JM, Hall G. The influence of context-reinforcer associations on instrumental performance. Animal Learning & Behavior 1979, 7, 504–508. https://doi.org/10.3758/BF03209710
  4. Shadmehr R, Smith MA, Krakauer JW. Error correction, sensory prediction, and adaptation in motor control. Annual review of neuroscience. 2010, 89-108.

https://doi.org/10.1146/annurev-neuro-060909-153135

  1. López-Moliner J, Vullings C, Madelain L. et al. Prediction and final temporal errors are used for trial-to-trial motor corrections. Sci Rep 2019, 9, 19230. https://doi.org/10.1038/s41598-019-55560-6
  2. Van Beers RJ, Brenner E, Smeets JB. Random walk of motor planning in task-irrelevant dimensions. Journal of neurophysiology, 2013, 109(4), 969-977. https://doi.org/10.1152/jn.00706.2012
  3. Burge J, Ernst MO, Banks MS. The statistical determinants of adaptation rate in human reaching. Journal ofVisionn, 2008, 8(4), 1-19.

https://doi.org/10.1167/8.4.20

  1. Kording K, Tenenbaum J, Shadmehr, R. The dynamics of memory as a consequence of optimal adaptation to a changing body. Nat Neurosci 2007, 10, 779–786. https://doi.org/10.1038/nn1901
  2. Crossman ER. A theory of the acquisition of speed-skill. Ergonomics, 1959, 2: 153–166. https://doi.org/10.1080/00140135908930419
  3. Churchland MM, Byron MY, Ryu SI, Santhanam G, Shenoy KV. Neural variability in the premotor cortex provides a signature of motor preparation. Journal of Neuroscience, 2006, 26(14), 3697-712.
  4. Ramezani H, Fallah Mohammadi Z, Namdar Tajari S, Khanbabaie R. The Acute Effect of Post-Activation Potentiation with Transcranial Random Noise Stimulation on Some Electrophysiological and Functional Variables of Athletic Men. Sport Physiology. 2020; 11(44): 31-54. In Persian 22089/spj.2019.7691.194
  5. Vera M, Lyzhko E, Schmanke T, Andreas SF, Christine M. Siniatchkin M. 1 mA cathodal tDCS shows excitatory effects in children and adolescents: Insights from TMS evoked N100 potential. Brain Research Bulletin, 2018, S036192301730374X 1016/j.brainresbull.2018.03.018
  6. Okano H, Tsubota K, Shimmura S, Omoto M, Kishino A, Maeda M. Therapeutic agent for corneal sensory nerve damage containing semaphorin inhibitor as active ingredient. Google Patents; 2014.
  7. Inukai Y, Saito K, Sasaki R, Tsuiki S, Miyaguchi S, Kojima S, Mitsuhiro M, Naofumi O, Onishi, H. Comparison of three non-invasive transcranial electrical stimulation methods for increasing cortical excitability. Frontiers in human neuroscience, 2016, 10, 668. 3389/fnhum.2016.00668
  8. Yeh TC, Huang CY, Chung YA., Im JJ, Lin YY, Ma CC, Chang HA. High-frequency transcranial random noise stimulation modulates gamma-band EEG source-based large-scale functional network connectivity in patients with schizophrenia: A randomized, double-blind, sham-controlled clinical trial. Journal of Personalized Medicine, 2022, 12(10), 1617. 3390/jpm12101617
  9. Potok W, Bächinger M, Van der Groen O, Cretu AL, Wenderoth N. Transcranial random noise stimulation acutely lowers the response threshold of human motor circuits. Journal of Neuroscience, 2021, 41(17), 3842-3853. 1523/jneurosci.2961-20.2021
  10. Andrea A, Christoph H. Transcranial alternating current and random noise stimulation: Possible mechanisms. Neu Plas. 2016; 12:30-7.
  11. Chaieb L, Antal A, Paulus W. Transcranial random noise stimulation-induced plasticity is NMDA-receptor independent but sodium-channel blocker and benzodiazepines sensitive. Frontiers Neuros, 2015, 9, 125.
  12. Latash M. There is no motor redundancy in human movements. There is motor abundance. Motor cont, 2000, 4(3), 259-261.
  13. Battaglini L, Contemori G, Fertonani A, Miniussi C, Coccaro A, Casco C. Excitatory and inhibitory lateral interactions effects on contrast detection are modulated by tRNS. Scientific reports. 2019; 9(1):19274.

https://doi.org/10.1038%2Fs41598-019-55602-z

  1. Yamaguchi T, Moriya K, Tanabe S, Kondo K, Otaka Y, Tanaka S. Transcranial direct-current stimulation combined with attention increases cortical excitability and improves motor learning in healthy volunteers. Journal of Neuroengineering and Rehabilitation, 2020, 17(1), 1-13. 1186/s12984-020-00665-7
  2. Hall J, Guyton H. Textbook of Medical Physiology (12th). Philadelphia, PA: Saunders/Elsevier. 2011, 686‎. 978-1-4160-4574-8.
  3. Schubotz RI, von Cramon D. Functional-anatomical concepts of human premotor cortex: evidence from fMRI and PET studies. Neuroimage, 2003, 20, S120. https://doi.org/10.1016/j.neuroimage.2003.09.014
  4. Cheng MY, Wang KP, Koester D, Schack T. Miss your putts? The key EEG index to achieve superior performance in golf putting. Presented at the Asia Conference on Kinesiology 2018, Taichung, Taiwan.
  5. Kantak SS, Mummidisetty CK, Stinear JW. Primary motor and premotor cortex in implicit sequence learning–evidence for competition between implicit and explicit human motor memory systems. Eur. J. Neurosci. 2012, 36, 2710–2715. https://doi.org/10.1111/j.1460-9568.2012.08175.x
  6. Kaminski E, Engelhardt M, Hoff M, Steele C, Villringer A, Ragert P. TDCS effects on pointing task learning in young and old adults. Scientific reports, 2021, 11(1),1-13. https://doi.org/10.1038/s41598-021-82275-4
  7. van Beers RJ. Motor learning is optimally tuned to the properties of motor noise. Neuron 2009; 63: 406–17. https://doi.org/10.1016/j.neuron.2009.06.025
  8. Smits-Engelsman BC, Wilson PH. Age-related changes in motor imagery from early childhood to adulthood: Probing the internal representation of speed-accuracy trade-offs. Human Movement Science, 2013, 32(5), 1151-1162. 1016/j.humov.2012.06.006
  9. Cohen EJ, Wei K, Minciacchi D. Examining modifications of execution strategies during a continuous task. Scientific reports, 2021, 11,1-14. https://doi.org/10.1038/s41598-021-84369-5
  10. Smith MJ, Keel JC, Greenberg BD, Adams LF, Schmidt PJ, Rubinow DA, Wassermann EM.Menstrual cycle effects on cortical excitability. Neurology 1999, 53:2069 –2072.
  11. Smith MJ, Adams LF, Schmidt PJ, Rubinow DR, Wassermann EM. Effects of ovarian hormones on human cortical excitability. Ann Neurol, 2002, 51:599 –603.
  12. Inghilleri M, Conte A, Curra A, Frasca V, Lorenzano C, Berardelli A. Ovarian hormones and cortical excitability. An rTMS study in humans. Clin Neurophysiol, 2004, 115:1063–68. 1016/j.clinph.2003.12.003
  13. Sale MV, Ridding MC, Nordstrom S. Factors influencing the magnitude and reproducibility of corticomotor excitability changes induced by paired associative stimulation. Exp Brain Res, 2007, 181: 615 – 626.

https://doi.org/10.1007/s00221-007-0960-x

  1. Doostan M, Namazizadeh M, Sheikh M, Naghdi N. The Effect of Change in Different Characteristics in Movements of Two Hands on Transfer of Asymmetrical Bimanual Movement to Its Converse Pattern. Motor Behavior. 2016; 8 (24): 133-52. In Persian

 https://doi.org/10.22089/mbj.2016.759

  1. Monastero R, Baschi R, Nicoletti A, Pilati L, Pagano L, Cicero CE, Brighina F. Transcranial random noise stimulation over the primary motor cortex in PD-MCI patients: a crossover, randomized, sham-controlled study. Journal of Neural Transmission, 2020, 127(12), 1589-1597. https://doi.org/10.1007/s00702-020-02255-2
  2. Cohen EJ, Wei K, Minciacchi D. Visuomotor perturbation in a continuous circle tracing task: Novel approach for quantifying motor adaptation. Sci. Rep. 2019, 9, 18679. https://doi.org/10.1038/s41598-019-55241-4
  3. Fertonani A, Cornelia P, Carlo M. Random noise stimulation improves neuroplasticity in perceptual learning. Neu sci. 2011; 31(43):15416-23.
  4. Classen J, Liepert J, Wise SP, Hallett M, Cohen LG. Rapid plasticity of human cortical movement representation induced by practice. Journal of Neurophysiology, 1998, 79(2), 1117-1123.
  5. Kong J, Wang Z, Leiser J, Minicucci D, Edwards R, Kirsch I, Gollub RL. Enhancing treatment of osteoarthritis knee pain by boosting expectancy: a functional neuroimaging study. NeuroImage: Clinical, 2018, 18, 325-334.

 https://doi.org/10.1016/j.nicl.2018.01.021

  1. Bertollo M, di Fronso S, Conforto S, Schmid M, Bortoli L, Comani S, Robazza C. Proficient brain for optimal performance: the MAP model perspective. PeerJ, 2016, 4, e2082. https://doi.org/10.7717/peerj.2082
  2. Wang KP, Cheng MY, Chen TT, Chang YK, Huang CJ, Feng J, Ren J. Experts’ successful psychomotor performance was characterized by effective switch of motor and attentional control. Psychology Sport Exercise. 2019, 374-79. 1016/j.psychsport.2019.04.006
  3. Huang J, Hegele M, Billino J. Motivational Modulation of Age-RelatedEffectss on Reaching Adaptation. Front. Psychol. 2018, 9, 2285.https://doi.org/10.3389/fpsyg.2018.02285
  4. Milton J, Solodkin A, Hluštík P, Small SL. The mind of expert motor performance is cool and focused. Neuroimage, 2007, 35(2), 804-813.
  5. Kelly AM, Garavan H. Human functional neuroimaging of brain changes associated with practice. Cerebral Cortex, 2005, 15(8), 1089–02. https://doi.org/10.1093/cercor/bhi005.
  6. Egner T, Gruzelier JH. EEG Biofeedback of low beta band components: Frequency-specific effects on variables of attention and event-related brain potentials. Clinical Neurophysiology, 2004, 115(1), 131–9. 1016/S1388-2457(03)00353-5
  7. Zhou J. et al. Te complexity of standing postural control in older adults: A modifed detrended fuctuation analysis based upon the empirical mode decomposition algorithm. PLoS ONE 2013, 8, e62585. https://doi.org/10.1371/journal.pone.0062585
  8. Floyer-Lea A, Matthews PM. Distinguishable brain activation networks for short- and long-term motor skill learning. J. Neurophysiol. 2005, 94, 512–18. 1152/jn.00717.2004
  9. Dimyan MA, Cohen LG. Neuroplasticity in the context of motor rehabilitation after stroke. Nat Rev Neurol 2011; 7(2):76-85. https://doi.org/10.1038%2Fnrneurol.2010.200
  10. Picard N, Matsuzaka Y, Strick PL. Extended practice of a motor skill is associated with reduced metabolic activity in M1. Nature neuroscience, 2013, 16(9), 1340-1347. https://doi.org/10.1038%2Fnn.3477
  11. Wu Z, Guo Z, Gearing M, Chen G. Tonic inhibition in dentate gyrus impairs long-term potentiation and memory in an Alzheimer’s disease model. Nature communications, 2014, 5 (1), 1-13. https://doi.org/10.1038/ncomms5159
  12. Poldrack RA, Sabb FW, Foerde K, Tom SM, Asarnow RF, Book-heimer SY, Knowlton BJ. The neural correlates of motor skill automaticity. J. Neurosci. 2005, 25, 5356–5364. https://doi.org/10.1523/jneurosci.3880-04.2005
  13. Bazanova OM, Vernon D. Interpreting EEG alpha activity. Neuroscience & Biobehavioral Reviews, 2014, 44, 94-110. https://doi.org/10.1016/j.neubiorev.2013.05.007
  14. Moliadze V, Fritzsche G, Antal A. Comparing the efficacy of excitatory transcranial stimulation methods measuring motor evoked potentials. Neural Plast. 2014; 837141. https://doi.org/10.1155/2014/837141
  15. Alimardani A, Shahbazi M, Tahmasebi Boroujeni S, Arabameri E. The effect of play at home (proposed by UNICEF) and metacognitive strategies on the health of children aged 5 to 8 years in the Corona pandemic. Sports Psychology, 2023; 15(2): 125-136. In Persian https://doi.org/10.48308/mbsp.2022.226686.1107
  16. Lee G, Thangavel R, Sharma V M., Litersky, JM, Bhaskar K, Fang SM, Ksiezak-Reding H. Phosphorylation of tau by fyn: implications for Alzheimer's disease. Journal of Neuroscience, 2004, 24(9), 2304-2312. https://doi.org/10.1523/jneurosci.4162-03.2004
  17. Carmel D, Carrasco M. Perceptual learning and dynamic changes in primary visual cortex. Neuron, 2008 57(6), 799-801. https://doi.org/10.1016/j.neuron.2008.03.009
  18. Miniussi C, Harris JA, Ruzzoli M. Modelling non-invasive brain stimulation in cognitive neuroscience. Neurosci Biobehav Rev 2013, 37:1702–1712.

https://doi.org/10.1016/j.neubiorev.2013.06.014

  1. Francis JT, Gluckman BJ, Schiff SJ. Sensitivity of neurons to weak electric J Neurosci, 2003, 23:7255–7261.
  2. Bikson M, Radman T, Datta A. Rational modulation of neuronal processing with applied electric fields. Int Conf IEEE Eng Med Biol Soc, 2006:1616–1619. https://doi.org/10.1109/iembs.2006.259548
  3. Qavami, A, Mohammadzadeh H, Rahban Fard H. The effect of self-regulation and observation of a beginner's pattern in learning relative and absolute timing. Journal of sports management and movement behavior, 2018; 14 (27), 14-25. In persian
  4. Maurer LK, Sammer G, Bischoff M, Maurer H, Müller H. Timing accuracy in self-timed movements related to neural indicators of movement initiation. Human Movement Science. 2014; 37: 42-57. 1016/j.humov.2014.06.005.
  5. Zhang Z, Guo D, Huber ME, Park S-W, Sternad D. Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise. PLoS Computational Biology. 2018; 14(2):e1006013.

https://doi.org/10.1371/journal.pcbi.1006013