대한약침학회지 (Journal of Pharmacopuncture)

  • 제22권3호
  • /
  • Pages.166-170
  • /
  • 2019
  • /
  • 2093-6966(pISSN)
  • /
  • 2234-6856(eISSN)
대한약침학회 (KOREAN PHARMACOPUNCTURE INSTITUTE)
권호 표지
DOI QR코드

DOI QR Code

qEEG Measures of Attentional and Memory Network Functions in Medical Students: Novel Targets for Pharmacopuncture to Improve Cognition and Academic Performance

  • Gorantla, Vasavi R. (Department of Behavioural Sciences and Neuroscience, AUA College of Medicine) ;
  • Bond, Vernon Jr. (Department of Recreation, Human Performance & Leisure Studies and Exercise Science & Human Nutrition Laboratory, Howard University Cancer Centre) ;
  • Dorsey, James (Department of Recreation, Human Performance & Leisure Studies and Exercise Science & Human Nutrition Laboratory, Howard University Cancer Centre) ;
  • Tedesco, Sarah (AUA College of Medicine) ;
  • Kaur, Tanisha (AUA College of Medicine) ;
  • Simpson, Matthew (AUA College of Medicine) ;
  • Pemminati, Sudhakar (Department of Medical Pharmacology, AUA College of Medicine, Antigua and Barbuda 8 Department of Medical Physiology, AUA College of Medicine) ;
  • Millis, Richard M. (Department of Behavioural Sciences and Neuroscience, AUA College of Medicine)
  • 투고 : 2019.01.08
  • 심사 : 2019.09.03
  • 발행 : 2019.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Objectives: Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance. Methods: Ten healthy male volunteers were subjected to 5-10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in ${\mu}V$, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson's product-moment coefficients and linear regression analysis. Results: fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively). Conclusion: Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain's cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

키워드

참고문헌

  1. Jittiwat J, Wattanathorn, Ginger J. pharmacopuncture improves cognitive impairment and oxidative stress following cerebral ischemia. J Acupunct Meridian Stud. 2012;5(6):295-300. https://doi.org/10.1016/j.jams.2012.09.003
  2. Isbell E, Stevens C, Pakulak E, Hampton Wray A, Bell TA, Neville HJ. Neuroplasticity of selective attention: Research foundations and preliminary evidence for a gene by intervention interaction. Proc Natl Acad Sci U S A. 2017;114(35):9247-54. https://doi.org/10.1073/pnas.1707241114
  3. Dean AC, Morales AM, Hellemann G, London ED. Cognitive deficit in methamphetamine users relative to childhood academic performance: link to cortical thickness. Neuropsychopharmacology. 2018;43(8):1745-52. https://doi.org/10.1038/s41386-018-0065-1
  4. Jolivet, Coggan JS, Allaman I, Magistretti PJ. Multi-timescale modeling of activity- Dependent metabolic coupling in the neuron-glia-vasculature ensemble. PLoS Computational Biology. 2015;11:e1004036. https://doi.org/10.1371/journal.pcbi.1004036
  5. Duyn JH. EEG-fMRI methods for the study of brain networks during sleep. Frontiers in Neurology. 2012;3:100. doi:10.3389/fneur.2012.00100.
  6. Plichta M, Wolf I, Hohmann S, et al. Simultaneous EEG and fMRI reveals a causally connected subcortical-cortical network during reward anticipation. J Neurosci. 2013; 33(36):14526-33. https://doi.org/10.1523/JNEUROSCI.0631-13.2013
  7. FDA News Release July 15, 2013.https://wayback.archiveit.org/7993/20170112223021/http://www.fda.gov/NewsEvents/ Newsroom/PressAnnouncements/ucm360811.htm.
  8. Pavlov YG, Kotchoubey B. EEG correlates of working memory performance in females. BMC Neurosci. 2017;18(1):26. doi: 10.1186/s12868-017-0344-5.
  9. Donner T H, Siegel M. A framework for local cortical oscillation patterns. Trends Cogn Sci. 2011;15(5):191-9. https://doi.org/10.1016/j.tics.2011.03.007
  10. Putman P, Verkuil B, Arias-Garcia E, Pantazi I, van Schie C. EEG theta/beta ratio as a potential biomarker for attentional control and resilience against deleterious effects of stress on attention. Cogn Affect Behav Neurosci. 2014;14(2):782-91. https://doi.org/10.3758/s13415-013-0238-7
  11. Enriquez-Geppert S, Huster RJ, Figge C, Herrmann CS. Self-regulation of frontal-midline theta facilitates memory updating and mental set shifting. Front Behav Neurosci. 2014; 8:420. doi: 10.3389/fnbeh.2014.00420.
  12. Kirov R, Weiss C, Siebner HR, Born J, Marshall L. Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding. Proc Natl Acad Sci U S A 2009;106(36):15460-5. doi: 10.1073/pnas.0904438106.
  13. Gorantla VR, Parsons G, Sayed E, Fadel A, Olukoga C, Volkova YA, et al. Electroencephalographic correlates of brain adaptations to medical school academic challenges-a pilot study. J Clin Diagn Res. 2018;12(4):CC05-CC08.
  14. Loo SK, Makeig S. Clinical Utility of EEG in Attention-Deficit/Hyperactivity Disorder: A Research Update. Neurotherapeutics. 2012;9(3):569-87. https://doi.org/10.1007/s13311-012-0131-z
  15. Ogrim G, Kropotov J, Hestad K. The quantitative EEG theta/beta ratio in attention deficit/hyperactivity disorder and normal controls: Sensitivity, specificity, and behavioral correlates. Psychiatry Res. 2012;198(3):482-8. https://doi.org/10.1016/j.psychres.2011.12.041
  16. Angelidis A, van der Does W, Schakel L, Putman P. Frontal EEG theta/beta ratio as an electrophysiological marker for attentional control and its test-retest reliability. Biol Psychol. 2016;121(Pt A):49-52. https://doi.org/10.1016/j.biopsycho.2016.09.008
  17. White JN, Hutchens TA, Lubar JF. Quantitative EEG assessment during neuropsychological task performance in adults with attention deficit hyperactivity disorder. J Adult Dev. 2005;12(2):113-21. https://doi.org/10.1007/s10804-005-7027-7
  18. Sangal RB, Sangal JM. Use of EEG beta-1 power and theta/beta ratio over Broca's area to confirm diagnosis of attention deficit/hyperactivity disorder in children. Clin EEG Neurosci. 2015;46(3):177-82. https://doi.org/10.1177/1550059414527284
  19. Snyder SM, Rugino TA, Hornig M, Stein MA. Integration of an EEG biomarker with a clinician's ADHD evaluation. Brain Behav. 2015;5:e00330.doi:10.1002/brb3.330.
  20. Graczyk M, Pachalska M, Ziolkowski A, Manko G, Łukaszewska B, Kochanowicz K, et.al. Neurofeedback training for peak performance. Ann Agri En vironl Med. 2014;21(4):871-5. https://doi.org/10.5604/12321966.1129950
  21. Ros T, Moseley MJ, Bloom PA, Benjamin L, Parkinson LA, Gruzelier JH. Optimizing microsurgical skills with EEG neurofeedback. BMC Neurosci. 2009;10:87. doi: 10.1186/1471-2202-10-87.
  22. Aguirre-Perez DM, Otero-Ojeda GA, Pliego-Rivero FB, Ferreira-Martinez AA. Relationship of working memory and EEG to academic performance: A study among high school students. Int J Neurosci. 2007;117(6):869-82. https://doi.org/10.1080/00207450600910077
  23. Field T, Diego M, Hernandez-Reif M. Tai Chi/ Yoga Effects on Anxiety, Heartrate, EEG and Math Computations. Complement Ther Clinl Pract. 2010;16(4):235-38. https://doi.org/10.1016/j.ctcp.2010.05.014
  24. Trakroo M, Bhavanani AB, Pal GK, Udupa K, Krishnamurthy N. A comparative study of the effects of asan, pranayama and asan-pranayama training on neurological and neuromuscular functions of Pondicherry police trainees. Int J Yoga. 2013;6:96-103. https://doi.org/10.4103/0973-6131.113398
  25. Putman P, van Peer J, Maimari I, van der Werff S. EEG theta/beta ratio in relation to fear- modulated response-inhibition, attentional control, and affective traits. Biol Psychol. 2010 83(2):73-8. https://doi.org/10.1016/j.biopsycho.2009.10.008
  26. Putman P, Verkuil B, Arias-Garcia E, Pantazi I, Schie C. EEG theta/beta ratio as a potential biomarker for attentional control and resilience against deleterious effects of stress on attention. Cogn Affect Behav Neurosci. 2014;14(2), 782-91. https://doi.org/10.3758/s13415-013-0238-7
  27. Miller J, Watrous AJ, Tsitsiklis M, Lee SA, Sheth SA, Schevon CA, et al. Lateralized hippocampal oscillations underlie distinct aspects of human spatial memory and navigation. Nat Commun. 2018;9(1):2423. doi: 10.1038/s41467-018-04847-9.
  28. Hosseini S, Pritchard-Berman M, Sosa N, Ceja A, Kesler S. Task-based neurofeedback training: A novel approach toward training executive functions. Neuroimage. 2016;134:153- 9. https://doi.org/10.1016/j.neuroimage.2016.03.035
  29. Thompson M, Thompson L. Improving attention in adults and children: differing electroencephalography profiles and implications for training. Association for Applied Psychophysiology & Biofeedback. 2006;34(3):99-105.
  30. Vernon D, Egner T, Cooper N, Compton T, Neilands C, Sheri A, et al. The effect of training distinct neurofeedback protocols on aspects of cognitive performance. Int J Psychophysiol. 2003;47(1):75-85. https://doi.org/10.1016/S0167-8760(02)00091-0