臺灣博碩士論文加值系統

成癮行為是神經生物系統有關的心智疾患，包括藉由吸入尼古丁、酒精、古柯鹼等所造成的藥物成癮現象，以及社會文化環境所導致的賭博成癮、網路成癮、購物成癮等。這些成癮疾病的來源雖然歧異，但其成癮的外顯行為表現卻相當類似，包含無法抑制獲取成癮物的渴望，因此，精神疾病診斷與統計手冊(DSM-5)將藥物成癮與賭博成癮疾病共同歸類到成癮性疾病下，提供診斷、評估與治療成癮行為的臨床參考。然而，眾多成癮行為是否具有相似的成癮神經機制，仍然未知。本實驗運用了醫學影像的統合分析方法(meta-analysis)，分析生物醫學資料庫中運用功能性磁振造影(functional MRI)探討成癮行為的神經科學文獻，使用活化可能性估計法 (Activation Likelihood Estimation)計算文獻報告中與成癮行為高度相關的大腦活動區域，在1036篇與神經造影有關的論文中，先將不符合活化可能性估計法需求的文獻排除，最後將150篇文獻歸類成三類：藥物成癮、賭博成癮、網路與性愛成癮。統合分析的結果發現：(1) 當受試者觀看藥物相關的影片或圖片時，他們的尾狀核、前扣帶迴、腦島會有較高的活化現象；尾狀核的功能主要是負責評估事件價值，並決定是否將要執行，前扣帶迴目前已知的功能則是有錯誤偵測的能力與發現事件矛盾或衝突區域；(2) 當受試者觀看賭博相關的影片或圖片，大腦活化狀況與觀看藥物圖片的狀況類似，顯示大腦的生物回饋系統無論成癮來源為賭博或是藥物，均引發相同的神經迴路；(3)成癮患者的杏仁核有較正常人有高的活化狀態，可能顯示成癮患者的情緒調控能力較正常人為低；(4) 無論在任何具成癮的提示刺激之下，丘腦下核與黑質皆會有活化的現象，大腦神經核均涉及了神經回饋系統，顯示成癮疾病是與大腦回饋系統功能異常有高度相關。本篇論文的結果提供了精神疾病診斷與統計手冊在診斷、評估與治療成癮行為的證據，並支持精神疾病診斷與統計手冊在行為成癮疾病和藥物成癮疾病分類的神經生物基礎。

Addiction is a neurobiological disease characterized by compulsive engagement in rewarding stimuli despite negative bio-psychosocial consequences, and can be classified as the loss of voluntary control over mood-alerting addicting substances (e.g., alcohol) or behaviors (e.g., gambling). However, with the new edition of the Diagnostic and Statistical Manual for Mental Disorder (DSM-5), both Substance-Related Disorder and Gambling Disorder are re-conceptualized into the revised category of “Addiction and Related Disorder” which suggests a variety of commonalities in clinical expression and treatment between two types of addictions. Here, we investigate whether brain activities are affected the same way in behavioral addictions as they are by substance addiction which has been identified by chronic exposure to drugs that causes significant biochemistry changes in brain circuits. A meta-analysis approach using Activation Likelihood Estimation (ALE) was conducted to compute statistically significant concordance with published coordinates across independent task-related functional neuroimaging studies. One hundred and fifty studies were categorized into three visual stimuli that induce specific nature of addictive behaviors: substance cue, gambling cue, and Internet & sex cues. Meta-analytic neuroimaging results demonstrated that participants showed greater brain activation in caudate, anterior cingulate cortex (ACC), and insula when viewing substance cues. Caudate has been identified to be responsible for estimating values and commanding action, and ACC has been suggested to error monitoring and conflict resolution. Similarly, the patterns of brain activation were also observed when viewing gambling cues, suggesting a common reward system regardless of different types of stimulants. Moreover, participants with substance-related disorder showed greater activation in right amygdala compared to healthy controls, indicating a dysfunction of neural circuitry to regulate the affective responses. Finally, the common brain regions in subthalamic nucleus (STN) and substania nigra (SN) were found across a variety of visual stimulus presented, including substance-related cue and CNS stimulant cue. These results provide a quantitative meta-analytic evidence of neurobiological basis of addictive disorder, and provide empirical evidence of similarities in reward neural pathways of the addictive human brain between substance addictions and behavioral addictions. Finally, our results support the classification of DSM-5 that neural network of gambling disorder could be resemble to other substance-related and addictive disorders.

List of Figures--ii
List of Tables--iii
摘要--iv
Abstract--v
致謝--vii
Chapter 1: Introduction--1
Chapter 2: Method--8
2.1 Literature searching and classification--8
2.2 Study 1--9
2.3 Study 2--10
2.4 Study 3--11
2.5 Data analysis--11
Chapter 3: Results--18
3.1 Study 1--18
3.2 Study 2--21
3.3 Study 3--24
Chapter 4: Discussion--30
Chapter 5: Conclusion--34
Appendix A--36
References--49

Bach, P., Vollstädt-Klein, S., Frischknecht, U., Hoerst, M., Kiefer, F., Mann, K., . . . Hermann, D. (2012). Diminished brain functional magnetic resonance imaging activation in patients on opiate maintenance despite normal spatial working memory task performance. Clinical Neuropharmacology., 35(4), 105-160. doi: 10.1097/WNF.0b013e31825c38f5.
Baicy, K., & London, E. D. (2007). Corticolimbic dysregulation and chronic methamphetamine abuse. Addiction, 102, 5-15. doi: 10.1111/j.1360-0443.2006.01777.x
Castilla-Ortega, E., Serrano, A., Blanco, E., Araos, P., Suárez, J., Pavón, F. J., . . . Santín, L. J. (2016). A place for the hippocampus in the cocaine addiction circuit: Potential roles for adult hippocampal neurogenesis. Neuroscience & Biobehavioral Reviews, 66, 15-32. doi: http://dx.doi.org/10.1016/j.neubiorev.2016.03.030
Deborah S. Hasin, Charles P. O’Brien, Marc Auriacombe, Guilherme Borges, Kathleen Bucholz, Alan Budney, . . . Bridget F. Grant. (2013). DSM-5 Criteria for Substance Use Disorders: Recommendations and Rationale. American Journal of Psychiatry, 170(8), 834-851. doi: 10.1176/appi.ajp.2013.12060782
Engelmann, J. M., Versace, F., Robinson, J. D., Minnix, J. A., Lam, C. Y., Cui, Y., . . . Cinciripini, P. M. (2012). Neural substrates of smoking cue reactivity: A meta-analysis of fMRI studies. NeuroImage, 60(1), 252-262. doi: http://dx.doi.org/10.1016/j.neuroimage.2011.12.024
Goldstein, R. Z., Tomasi, D., Alia-Klein, N., Honorio Carrillo, J., Maloney, T., Woicik, P. A., . . . Volkow, N. D. (2009). Dopaminergic response to drug words in cocaine addiction. J Neurosci, 29(18), 6001-6006. doi: 10.1523/jneurosci.4247-08.2009
Grahn, J. A., Parkinson, J. A., & Owen, A. M. (2008). The cognitive functions of the caudate nucleus. Prog Neurobiol, 86(3), 141-155. doi: 10.1016/j.pneurobio.2008.09.004
Lee, E., Ku, J., Jung, Y.-C., Lee, H., An, S. K., Kim, K. R., . . . Namkoong, K. (2013). Neural Evidence for Emotional Involvement in Pathological Alcohol Craving. Alcohol and Alcoholism, 48(3), 288-294. doi: 10.1093/alcalc/ags130
Linnet, J., Mouridsen, K., Peterson, E., Moller, A., Doudet, D. J., & Gjedde, A. (2012). Striatal dopamine release codes uncertainty in pathological gambling. Psychiatry Res, 204(1), 55-60. doi: 10.1016/j.pscychresns.2012.04.012
London, E. D., Kohno, M., Morales, A. M., & Ballard, M. E. (2015). Chronic methamphetamine abuse and corticostriatal deficits revealed by neuroimaging. Brain Research, 1628, Part A, 174-185. doi: http://dx.doi.org/10.1016/j.brainres.2014.10.044
McClernon FJ, F. B., Rose JE, Kozink RV, Addicott MA, Sweitzer MM, Westman EC, Van Wert DM. (2016). The effects of nicotine and non-nicotine smoking factors on working memory and associated brain function. Addict Biology, 21(4), 954-961. doi: 10.1111/adb.12253.
Meng, Y.-j., Deng, W., Wang, H.-y., Guo, W.-j., Li, T., Lam, C., & Lin, X. (2014). Reward pathway dysfunction in gambling disorder: A meta-analysis of functional magnetic resonance imaging studies. Behavioural Brain Research, 275, 243-251. doi: http://dx.doi.org/10.1016/j.bbr.2014.08.057
Meng, Y., Deng, W., Wang, H., Guo, W., & Li, T. (2015). The prefrontal dysfunction in individuals with Internet gaming disorder: a meta-analysis of functional magnetic resonance imaging studies. Addict Biol, 20(4), 799-808. doi: 10.1111/adb.12154
Moeller, S. J., Tomasi, D., Honorio, J., Volkow, N. D., & Goldstein, R. Z. (2012). Dopaminergic involvement during mental fatigue in health and cocaine addiction. Transl Psychiatry, 2, e176. doi: 10.1038/tp.2012.110
Noori, H. R., Cosa Linan, A., & Spanagel, R. (2016). Largely overlapping neuronal substrates of reactivity to drug, gambling, food and sexual cues: A comprehensive meta-analysis. European Neuropsychopharmacology, 26(9), 1419-1430. doi: 10.1016/j.euroneuro.2016.06.013
Okita, K., Ghahremani, D. G., Payer, D. E., Robertson, C. L., Dean, A. C., Mandelkern, M. A., & London, E. D. (2016). Emotion dysregulation and amygdala dopamine D2-type receptor availability in methamphetamine users. Drug and Alcohol Dependence, 161, 163-170. doi: https://doi.org/10.1016/j.drugalcdep.2016.01.029
Probst, C. C., & van Eimeren, T. (2013). The Functional Anatomy of Impulse Control Disorders. Current Neurology and Neuroscience Reports, 13(10), 386. doi: 10.1007/s11910-013-0386-8
Quester, S., & Romanczuk-Seiferth, N. (2015). Brain Imaging in Gambling Disorder. Current Addiction Reports, 2(3), 220-229. doi: 10.1007/s40429-015-0063-x
Robinson, T. E., & Berridge, K. C. (1993). The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res Brain Res Rev, 18(3), 247-291.
Romanczuk-Seiferth, N., van den Brink, W., & Goudriaan, A. E. (2014). From Symptoms to Neurobiology: Pathological Gambling in the Light of the New Classification in DSM-5. Neuropsychobiology, 70(2), 95-102.
Schacht, J. P., Anton, R. F., & Myrick, H. (2013). Functional neuroimaging studies of alcohol cue reactivity: A quantitative meta-analysis and systematic review. Addict Biol, 18(1), 121-133. doi: 10.1111/j.1369-1600.2012.00464.x
Schmidt, C., Morris, L. S., Kvamme, T. L., Hall, P., Birchard, T., & Voon, V. (2017). Compulsive sexual behavior: Prefrontal and limbic volume and interactions. Hum Brain Mapp, 38(3), 1182-1190. doi: 10.1002/hbm.23447
Sescousse, G., Caldu, X., Segura, B., & Dreher, J. C. (2013). Processing of primary and secondary rewards: a quantitative meta-analysis and review of human functional neuroimaging studies. Neurosci Biobehav Rev, 37(4), 681-696. doi: 10.1016/j.neubiorev.2013.02.002
Sescousse, G., Janssen, L. K., Hashemi, M. M., Timmer, M. H., Geurts, D. E., Huurne, N. P. t., . . . Cools, R. (2016). Amplified striatal responses to near-miss outcomes in pathological gamblers. Neuropsychopharmacology, 41, 2614-2623. doi: 10.1038/npp.2016.43
Silveri, M. M., Dager, A. D., Cohen-Gilbert, J. E., & Sneider, J. T. (2016). Neurobiological signatures associated with alcohol and drug use in the human adolescent brain. Neurosci Biobehav Rev, 70, 244-259. doi: 10.1016/j.neubiorev.2016.06.042
Volkow, N. D., Wang, G. J., Fowler, J. S., & Tomasi, D. (2012). Addiction Circuitry in the Human Brain. Annu Rev Pharmacol Toxicol, 52, 321-336. doi: 10.1146/annurev-pharmtox-010611-134625
Vollstadt-Klein, S., Hermann, D., Rabinstein, J., Wichert, S., Klein, O., Ende, G., & Mann, K. (2010). Increased activation of the ACC during a spatial working memory task in alcohol-dependence versus heavy social drinking. Alcohol Clin Exp Res, 34(5), 771-776. doi: 10.1111/j.1530-0277.2010.01149.x
Wager, T. D., Lindquist, M., & Kaplan, L. (2007). Meta-analysis of functional neuroimaging data: current and future directions. Social Cognitive and Affective Neuroscience, 2(2), 150-158. doi: 10.1093/scan/nsm015
Weinstein, A., & Lejoyeux, M. (2015). New developments on the neurobiological and pharmaco-genetic mechanisms underlying internet and videogame addiction. Am J Addict, 24(2), 117-125. doi: 10.1111/ajad.12110
Zhao, H.-k., Chang, C.-w., Geng, N., Gao, L., Wang, J., Wang, X., . . . Gao, G.-d. (2012). Associations between personality changes and nucleus accumbens ablation in opioid addicts. Acta Pharmacologica Sinica, 33(5), 588-593. doi: 10.1038/aps.2012.10