摘要(英) |
Methamphetamine (Methamphetamine, MA, called methamphetamine in Chinese) is currently the top three drug abusers in China. In the subsequent process of detoxification, there will be many withdrawal symptoms, such as listlessness, depression, restlessness, restlessness, etc. It is quite easy to relapse in the future process of detoxification. Studies have shown that drug abusers are prompted by VR neutral and drug-related environments, and the brain Gamma waves produce abnormalities in the medial prefrontal cortex/orbitofrontal cortex (MPFC / OFC) and dorsolateral prefrontal cortex (DLPFC) , And long-term use of drugs affect the central nervous system, and then cause abnormal brain function, such as psychosis, delusions and violent behavior, and observe abnormal brain wave frequency bands, but also cause arrhythmia and abnormalities of the autonomic nervous system. There are also several similar studies that explore whether the neutral VR environment and related drug environmental stimuli can actually cause stimulus responses, and propose that Gamma waves are related to the reward mechanism of the cerebral cortex. Under the stimulation of related drug environments, it is obviously induced Mood swings. Most of the research directions are the comparison of the neutral environment and the drug environment. Therefore, this research focuses on the analysis of the VR drug-related environment, observing the changes of stimulation of different intensities, and the electrophysiological signal between normal and drug addicts. Differences, and study the existence of their relevance, and the physiological significance that can be exhibited.
This study collected cases from Kaohsiung Chang Gung Memorial Hospital and Keelung Chang Gung Memorial Hospital in the Department of Psychiatry. There were 51 people in total, but currently only 26 people have undergone EEG experiments. There are 16 people in the experimental group (drug abusers) and 10 people in the control group (normal people). Use Virtual Reality (VR) to create a realistic KTV scene, divide four different stimulus intensities during the game, to stimulate the experimental group and the control group and collect FCZ, CZ, PZ, C3, C4 Channel brainwave data and ECG information for analysis and comparison. Research method We used Matlab R2019a SPM12 to process brain wave data, and applied signal processing methods (Wavelet and Hilbert-Huang Transform) to analyze the difference between the experimental group and the control group. ECG conducts HRV analysis to obtain some indicators for discussion, and analyzes the correlation between EEG and ECG. The results of the study showed that after watching the VR scenes individually in the patient group and the healthy group, under the four stages of different stimulation conditions, compared with the healthy group, the patient group found that the Alpha wave and Beta wave increased significantly under the fourth stage of stimulation. high. There is no significant difference between the two groups. The reason may be that there is only a single stimulus VR environment, and the content provided by the VR game content is only to cause a desire for drugs. To confirm the difference between the patient group and the healthy group , Must rely on the results of the post-test experiment. The analysis of HRV is in line with many previous related studies. The Poincaré diagram′s nonlinear analysis method is correlated with the frequency domain analysis method. In the discovery of LF and sympathetic nerves, we have found a set of test standards that may be treated later . Finally, the findings of EEG and ECG let us know that there is a correlation between them, and it also provides a major direction for follow-up research. However, because the number of people in this study is currently too small, it is expected that more data will be added in the future to improve the accuracy of the experiment, which can help more research on other substance addictions and provide help for the treatment of such brain diseases. |
參考文獻 |
[1] Northrop NA, Yamamoto BK. Methamphetamine effects on blood-brain barrier structure and function. Front Neurosci. 2015 Mar 4;9:69. doi: 10.3389/fnins.2015.00069. PMID: 25788874; PMCID: PMC4349189.
[2] Martins T, Baptista S, Gonçalves J, Leal E, Milhazes N, Borges F, Ribeiro CF, Quintela O, Lendoiro E, López-Rivadulla M, Ambrósio AF, Silva AP. Methamphetamine transiently increases the blood-brain barrier permeability in the hippocampus: role of tight junction proteins and matrix metalloproteinase-9. Brain Res. 2011 Sep 9;1411:28-40. doi: 10.1016/j.brainres.2011.07.013. Epub 2011 Jul 14. PMID: 21803344.
[3] Hart CL, Ward AS, Haney M, Foltin RW, Fischman MW. Methamphetamine self-administration by humans. Psychopharmacology (Berl). 2001 Aug;157(1):75-81. doi: 10.1007/s002130100738. PMID: 11512046.
[4] Potvin S, Pelletier J, Grot S, Hébert C, Barr AM, Lecomte T. Cognitive deficits in individuals with methamphetamine use disorder: A meta-analysis. Addict Behav. 2018 May;80:154-160. doi: 10.1016/j.addbeh.2018.01.021. Epub 2018 Jan 31. PMID: 29407687.
[5] Zahra Alam mehrjerdi et al., Methamphetamine-associated psychosis: a new
health challenge in Iran, Daru (2013) 21:30.
[6] McKetin R, Dawe S, Burns RA, Hides L, Kavanagh DJ, Teesson M, McD Young R, Voce A, Saunders JB. The profile of psychiatric symptoms exacerbated by methamphetamine use. Drug Alcohol Depend. 2016 Apr 1;161:104-9. doi: 10.1016/j.drugalcdep.2016.01.018. Epub 2016 Jan 30. PMID: 26874915.
[7] Khajehpour H, Mohagheghian F, Ekhtiari H, Makkiabadi B, Jafari AH, Eqlimi E, Harirchian MH. Computer-aided classifying and characterizing of methamphetamine use disorder using resting-state EEG. Cogn Neurodyn. 2019 Dec;13(6):519-530. doi: 10.1007/s11571-019-09550-z. Epub 2019 Aug 7. PMID: 31741689; PMCID: PMC6825232.
[8] Janetsian SS, Linsenbardt DN, Lapish CC. Memory impairment and alterations in prefrontal cortex gamma band activity following methamphetamine sensitization. Psychopharmacology (Berl). 2015 Jun;232(12):2083-95. doi: 10.1007/s00213-014-3840-7. Epub 2015 Jan 10. PMID: 25572530; PMCID: PMC4433565.
[9] Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England;
Hoboken, NJ: John Wiley & Sons. P.15-18
[10] Marzbani H, Marateb HR, Mansourian M. Neurofeedback: A Comprehensive Review on System Design, Methodology and Clinical Applications. Basic Clin Neurosci. 2016 Apr;7(2):143-58. doi: 10.15412/J.BCN.03070208. PMID: 27303609; PMCID: PMC4892319.
[11] Potenza MN, Balodis IM, Derevensky J, Grant JE, Petry NM, Verdejo-
Garcia A, Yip SW. Gambling disorder. Nat Rev Dis Primers. 2019 Jul
25;5(1):51. doi: 10.1038/s41572-019-0099-7. PMID: 31346179.
[12] Goldstein RZ, Volkow ND. Drug addiction and its underlying
neurobiological basis: neuroimaging evidence for the involvement of the
frontal cortex. Am J Psychiatry. 2002 Oct;159(10):1642-52. doi:
10.1176/appi.ajp.159.10.1642. PMID: 12359667; PMCID: PMC1201373.
[13] Dupre, A., Vincent, S., & Iaizzo, P. A. (n.d.). Basic ECG Theory, Recordings, and
Interpretation. Handbook of Cardiac Anatomy, Physiology, and Devices, 191–201.
[14] Politano L, Palladino A, Nigro G, Scutifero M, Cozza V. Usefulness of
heart rate variability as a predictor of sudden cardiac death in muscular
dystrophies. Acta Myol. 2008 Dec;27(3):114-22. PMID: 19472920; PMCID:
PMC2858940.
[15] Chen WL, Kuo CD. Characteristics of heart rate variability can predict
impending septic shock in emergency department patients with sepsis.
Acad Emerg Med. 2007 May;14(5):392-7. doi: 10.1197/j.aem.2006.12.015.
Epub 2007 Mar 26. PMID: 17389245.
[16] Ralevski E, Petrakis I, Altemus M. Heart rate variability in alcohol use: A
review. Pharmacol Biochem Behav. 2019 Jan;176:83-92. doi:
0.1016/j.pbb.2018.12.003. Epub 2018 Dec 6. PMID: 30529588.
[17] Tsai MC, Chung CR, Chen CC, Yeh SC, Chen JY, Lin CH, Chen YJ, Tsai MC, Wang
YL, Lin CJ, Wu H. An Intelligent Virtual-Reality System with Multi-Model Sensing
for Cue-Elicited Craving in Patients with Methamphetamine Use Disorder. IEEE
Trans Biomed Eng. 2021 Feb 11;PP. doi: 10.1109/TBME.2021.3058805. Epub ahead
of print. PMID: 33571085.
[18] Bordnick PS, Copp HL, Traylor A, Graap KM, Carter BL, Walton A, Ferrer
M. Reactivity to cannabis cues in virtual reality environments. J Psychoactive
Drugs. 2009 Jun;41(2):105-12. doi: 10.1080/02791072.2009.10399903. PMID:
19705672; PMCID: PMC4104948.
[19] Traylor AC, Bordnick PS, Carter BL. Using virtual reality to assess young
adult smokers′ attention to cues. Cyberpsychol Behav. 2009 Aug;12(4):373-8.
doi: 10.1089/cpb.2009.0070. PMID: 19630582; PMCID: PMC4104935.
[20] Ryan JJ, Kreiner DS, Chapman MD, Stark-Wroblewski K. Virtual reality
cues for binge drinking in college students. Cyberpsychol Behav Soc Netw.
2010 Apr;13(2):159-62. doi: 10.1089/cyber.2009.0211. PMID: 20528271.
[21] Segawa T, Baudry T, Bourla A, Blanc JV, Peretti CS, Mouchabac S, Ferreri
F. Virtual Reality (VR) in Assessment and Treatment of Addictive Disorders: A
Systematic Review. Front Neurosci. 2020 Jan 10;13:1409. doi:
10.3389/fnins.2019.01409. PMID: 31998066; PMCID: PMC6965009.
[22] Tan H, Chen T, Du J, Li R, Jiang H, Deng CL, Song W, Xu D, Zhao M. Drug-
related Virtual Reality Cue Reactivity is Associated with Gamma Activity in
Reward and Executive Control Circuit in Methamphetamine Use Disorders.
Arch Med Res. 2019 Nov;50(8):509-517. doi: 10.1016/j.arcmed.2019.09.003.
Epub 2020 Feb 3. PMID: 32028094.
[23] Ding X, Li Y, Li D, Li L, Liu X. Using machine-learning approach to
distinguish patients with methamphetamine dependence from healthy
subjects in a virtual reality environment. Brain Behav. 2020
Nov;10(11):e01814. doi: 10.1002/brb3.1814. Epub 2020 Aug 29. PMID:
32862513; PMCID: PMC7667292.
[24] Chen CC, Tsai MC, Wu H, Chung CR, LEE Y, Chiu PR, Tsai PY, Yeh SC. Using an intelligent virtual reality system to study the drug cue induced neuronal abnormalities in patients with methamphetamine use disorder.
[25] Subasi, A. and M. Gürsoy (2010). "EEG signal classification using PCA, ICA, LDA and support vector machines." Expert Systems with Applications 37: 8659-8666.
[26] 陳振雄,應用希爾伯特-黃轉換之訊號濾波研究,Journal of Science and
Engineering Technology, Vol. 6, No. 1, pp. 75-84 (2010)
[27] A.O. Boudraa, J.C. Cexus, and Z. Saidi, EMD-Based Signal Noise Reduction, World Academy of Science, Engineering and Technology International Journal of Electronics and Communication Engineering (2007) Vol:1, No:2
[28] Büssow, R. (2007). An algorithm for the continuous Morlet wavelet transform. Mechanical Systems and Signal Processing, 21(8), 2970–2979.
[29] Wadhwa RR, Marappa-Ganeshan R. T Test. 2020 Apr 16. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan–. PMID: 31971709.
[30] Tenny S, Abdelgawad I. Statistical Significance. 2020 Jul 10. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan–. PMID: 29083828.
[31] Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and
Norms. Front Public Health. 2017 Sep 28;5:258. doi:
10.3389/fpubh.2017.00258. PMID: 29034226; PMCID: PMC5624990.
[32] Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996 Mar 1;93(5):1043-65. PMID: 8598068.
[33] Kamen PW, Krum H, Tonkin AM. Poincaré plot of heart rate variability allows quantitative display of parasympathetic nervous activity in humans. Clin Sci (Lond). 1996 Aug;91(2):201-8. doi: 10.1042/cs0910201. PMID: 8795444.
[34] Hsu CH, Tsai MY, Huang GS, Lin TC, Chen KP, Ho ST, Shyu LY, Li CY. Poincaré plot indexes of heart rate variability detect dynamic autonomic modulation during general anesthesia induction. Acta Anaesthesiol Taiwan. 2012 Mar;50(1):12-8. doi: 10.1016/j.aat.2012.03.002. Epub 2012 Apr 3. PMID: 22500908.
[35] Ardissino M, Nicolaou N, Vizcaychipi M. Non-invasive real-time autonomic function characterization during surgery via continuous Poincaré quantification of heart rate variability. J Clin Monit Comput. 2019 Aug;33(4):627-635. doi: 10.1007/s10877-018-0206-4. Epub 2018 Oct 3. PMID: 30284098; PMCID: PMC6602980.
[36] Vanderlei LC, Pastre CM, Hoshi RA, Carvalho TD, Godoy MF. Basic notions of heart rate variability and its clinical applicability. Rev Bras Cir Cardiovasc. 2009 Apr-Jun;24(2):205-17. doi: 10.1590/s0102-76382009000200018. PMID: 19768301.
[37] Krummenauer F. I: Boxplots - die flexible Alternative zum "Antennenbildchen" [I: Box whisker plots--Flexible alternative to "MSE Plots"]. Klin Monbl Augenheilkd. 2002 Aug;219(8):613-5. German. doi: 10.1055/s-2002-34420. PMID: 12353181.
[38] Seow LSE, Ong WJ, Hombali A, AshaRani PV, Subramaniam M. A Scoping Review on Cue Reactivity in Methamphetamine Use Disorder. Int J Environ Res Public Health. 2020 Sep 7;17(18):6504. doi: 10.3390/ijerph17186504. PMID: 32906716; PMCID: PMC7558044.
[39] Forner-Phillips NA, Mills C, Ross RS. Tendency to ruminate and anxiety are associated with altered alpha and beta oscillatory power dynamics during memory for contextual details. Cogn Affect Behav Neurosci. 2020 Aug;20(4):698-716. doi: 10.3758/s13415-020-00797-2. PMID: 32430900.
[40] Başar E, Schürmann M, Başar-Eroglu C, Karakaş S. Alpha oscillations in brain functioning: an integrative theory. Int J Psychophysiol. 1997 Jun;26(1-3):5-29. doi: 10.1016/s0167-8760(97)00753-8. Erratum in: Int J Psychophysiol 1998 Jun;29(1):105. PMID: 9202992.
[41] Schürmann M, Başar-Eroglu C, Başar E. A possible role of evoked alpha in primary sensory processing: common properties of cat intracranial recordings and human EEG and MEG. Int J Psychophysiol. 1997 Jun;26(1-3):149-70. doi: 10.1016/s0167-8760(97)00762-9. PMID: 9203001.
[42] Sporn S, Hein T, Herrojo Ruiz M. Alterations in the amplitude and burst rate of beta oscillations impair reward-dependent motor learning in anxiety. Elife. 2020 May 19;9:e50654. doi: 10.7554/eLife.50654. PMID: 32423530; PMCID: PMC7237220.
[43] Chen T, Su H, Zhong N, Tan H, Li X, Meng Y, Duan C, Zhang C, Bao J, Xu D, Song W, Zou J, Liu T, Zhan Q, Jiang H, Zhao M. Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates. BMC Psychiatry. 2020 Jun 24;20(1):334. doi: 10.1186/s12888-020-02743-5. PMID: 32580716; PMCID: PMC7315471
[44] Wang YG, Shen ZH, Wu XC. Detection of patients with methamphetamine dependence with cue-elicited heart rate variability in a virtual social environment. Psychiatry Res. 2018 Dec;270:382-388. doi: 10.1016/j.psychres.2018.10.009. Epub 2018 Oct 2. PMID: 30300868.
[45] Knyazev GG. Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neurosci Biobehav Rev. 2007;31(3):377-95. doi: 10.1016/j.neubiorev.2006.10.004. Epub 2006 Dec 4. PMID: 17145079.
[46] Spencer KM, Nestor PG, Niznikiewicz MA, Salisbury DF, Shenton ME, McCarley RW. Abnormal neural synchrony in schizophrenia. J Neurosci. 2003 Aug 13;23(19):7407-11. doi: 10.1523/JNEUROSCI.23-19-07407.2003. PMID: 12917376; PMCID: PMC2848257.
[47] Ahmadlou M, Ahmadi K, Rezazade M, Azad-Marzabadi E. Global organization of functional brain connectivity in methamphetamine abusers. Clin Neurophysiol. 2013 Jun;124(6):1122-31. doi: 10.1016/j.clinph.2012.12.003. Epub 2013 Jan 16. PMID: 23332777.
[48] Brennan M, Palaniswami M, Kamen P. Do existing measures of Poincaré plot geometry reflect nonlinear features of heart rate variability? IEEE Trans Biomed Eng. 2001 Nov;48(11):1342-7. doi: 10.1109/10.959330. PMID: 11686633.
[49] Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991 Aug;84(2):482-92. doi: 10.1161/01.cir.84.2.482. PMID: 1860193.
[50] Karemaker JM. An introduction into autonomic nervous function. Physiol Meas. 2017 May;38(5):R89-R118. doi: 10.1088/1361-6579/aa6782. Epub 2017 Mar 17. PMID: 28304283.
[51] Edlinger G, Guger C. Correlation Changes of EEG and ECG After Fast Cable CAR Ascents. Conf Proc IEEE Eng Med Biol Soc. 2005;2005:5540-3. doi: 10.1109/IEMBS.2005.1615739. PMID: 17281509.
[52] Taylor JA, Carr DL, Myers CW, Eckberg DL. Mechanisms underlying very-low-frequency RR-interval oscillations in humans. Circulation. 1998 Aug 11;98(6):547-55. doi: 10.1161/01.cir.98.6.547. PMID: 9714112.
[53] Henry BL, Minassian A, Perry W. Effect of methamphetamine dependence on heart rate variability. Addict Biol. 2012 May;17(3):648-58. doi: 10.1111/j.1369-1600.2010.00270.x. Epub 2010 Dec 23. PMID: 21182570; PMCID: PMC3117088.
[54] Ito H, Yeo KK, Wijetunga M, Seto TB, Tay K, Schatz IJ. A comparison of echocardiographic findings in young adults with cardiomyopathy: with and without a history of methamphetamine abuse. Clin Cardiol. 2009 Jun;32(6):E18-22. doi: 10.1002/clc.20367. PMID: 19330818; PMCID: PMC3787838.
[55] Yun K, Park HK, Kwon DH, Kim YT, Cho SN, Cho HJ, Peterson BS, Jeong J. Decreased cortical complexity in methamphetamine abusers. Psychiatry Res. 2012 Mar 31;201(3):226-32. doi: 10.1016/j.pscychresns.2011.07.009. Epub 2012 Mar 24. PMID: 22445216. |