大学生手机依赖症脑灰质密度改变的研究
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摘要
目的研究手机依赖者大脑灰质结构的变化,探讨手机依赖者大脑灰质结构改变的特征。方法 25名手机依赖症者与23名健康对照者参加本研究,采用西门子3.0 T Trio MRI扫描仪对全脑灰质(3D T1_mprage)进行数据采集,使用基于体素的形态学分析(VBM)方法观察手机依赖组与正常被试组之间的灰质结构的差异,采用双样本t检验分析两组差异,并进行Alpha Sim校正,取个数>115的体素集合,校正后P<0.01的像素被认为具有显著性。结果与正常组相比,手机依赖组多个脑区的灰质体积缩小,主要包括中央前回、旁中央小叶、额上回、眶额部皮层、背侧前扣带回、岛叶、基底节区的尾状核、壳核、苍白球、杏仁核和丘脑、伏隔核、中脑腹侧被盖区、海马等区域。结论手机依赖症者与正常对照组相比,在上述区域的灰质结构已发生变化。提示手机依赖症可能影响了与认知功能、冲动控制、情绪和精神行为、大脑奖赏等功能相关脑区的灰质结构。
Objective To study the changes and explore the characteristics of brain gray matter structure changes in mobile phone addiction. Methods 25 mobile phone addicts and 23 control subjects were recruited. The Siemens 3. 0 Ttrio MRI was used for( 3D T1_mprage) data acquisition,( Voxel-based morphometry,VBM) were used for the comparison of the differences of gray matter structures between addiction group and control group. Using two sample t test to analyse the differences between the two groups,And AlphaS im correction in order to take the number of the set of more than 40 voxel,there were significant differences when P < 0. 01 pixel after adjustment. Results Compared with the control group,mobile phone addiction group had multiple areas of the brain gray matter volume reduction,mainly including Precentral gyrus 、Postcentral gyrus、paracentral lobule、superior frontal gyrus、orbit frontal cortex、dorsal anterior cingulate cortex、posterior cingulate cortex、insula、Caudate nucleus、Putamen、Globus pallidus、amygdaloid nucleus、Thalamus、Nucleus accumbens、ventral tegmental area and Hippocampus. Conclusion Compared with the control group,the gray matter structure in certain areas of the brain in the mobile phone addiction group area showed some changes. Changes of brain gray matter density mainly involves cognitive function,impulse control,emotional and mental behavior as well as brain reward related areas.
Objective To study the changes and explore the characteristics of brain gray matter structure changes in mobile phone addiction. Methods 25 mobile phone addicts and 23 control subjects were recruited. The Siemens 3. 0 Ttrio MRI was used for( 3D T1_mprage) data acquisition,( Voxel-based morphometry,VBM) were used for the comparison of the differences of gray matter structures between addiction group and control group. Using two sample t test to analyse the differences between the two groups,And AlphaS im correction in order to take the number of the set of more than 40 voxel,there were significant differences when P < 0. 01 pixel after adjustment. Results Compared with the control group,mobile phone addiction group had multiple areas of the brain gray matter volume reduction,mainly including Precentral gyrus 、Postcentral gyrus、paracentral lobule、superior frontal gyrus、orbit frontal cortex、dorsal anterior cingulate cortex、posterior cingulate cortex、insula、Caudate nucleus、Putamen、Globus pallidus、amygdaloid nucleus、Thalamus、Nucleus accumbens、ventral tegmental area and Hippocampus. Conclusion Compared with the control group,the gray matter structure in certain areas of the brain in the mobile phone addiction group area showed some changes. Changes of brain gray matter density mainly involves cognitive function,impulse control,emotional and mental behavior as well as brain reward related areas.
引文
1 Park WK.Mobile phone addiction[J].Mob Commun,2005,31:253-272.
2 Park WK.The mobile phone addiction among Korean college students[J].Korean Soc J Commun,2003,47:250-281.
3中国互联网络信息中心(CNNIC).第35次中国互联网络发展状况统计报告[EB/OL].Hnp://www.cnnic net.en/hlwfzyj/hlwxzhg/hlwtjbg/201502/t20150203_51634.htm,2015.
4熊婕,周宗奎,陈武,等.大学生手机成瘾倾向量表的编制[J].中国心理卫生杂志,2012,26:222-225.
5 Mackey S,Stewart JL,Connolly CG,et al.A voxel-based morphometry study of young occasional users of amphetaminetype stimulants and cocaine[J].Drug and Alcohol Dependence,2014,135:104-111.
6 Jin Y,Shi Y,Zhan L,et al.Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics[J].Neuro Image,2014,100:75-90.
7 Aarts E,Roelofs A.Attentional conlrol in anterior cingulated cortex based on probabilistic cueing[J].Journal of Cognitive Neuroscience,2011,23:716-727.
8 Romero MJ,Asensio S,Palall C,et al.Cocaine addiction:Diffusion tensor imaging study of the inferior frontal and anterior cingulate white matter,Psychiatry Research[J].Neuroimaging,2010,181:57-63.
9 Dong G,Wang J,Yang X,et al.Risk personality traits of Internet addiction:A longitudinal study of Intemet-addicted Chinese university students[J].Asia Pac Psychiatry,2013,5:316-321.
10 Hoogendijk WJG,Veltman DJ.Cognitive Inflexibility in ObsessiveCompulsive Disorder and Major Depression Is Associated with Distinct Neural Correlates[J].PLo S One,2013,8:e59600
11 Cao E,Su L,Liu T,et al.The relationship between impulsivity and Internet addiction in a sample of Chinese adolescents[J].European Psychiatry,2007,22:466-471.
12 Dong G,De Vito EE,Du X,et al.Impaired inhibitory control in internet addiction disorder:A functional magnetic resonance imaging study.Psychiatry Research the relationship between impulsivity and Internet addiction in a sample of Chinese adolescents[J].Neuroimaging,2012,203:153-158.
13 Dong G,Lu Q,Zhou H,et al.Impulse inhibition in people with Internet addiction disorder:Electrophysiological evidence from a Go/NoGo study[J].Neuroscience Letters,2010,485:138-142.
14 Ko CH,Hsiao S,Liu GC,et al.The characteristics of decision making potential to take risks and personality of college students with Interact addiction[J].Psychiatry Research,2010,175:121-125.
15 Heil SH,Johnson MW,Higgius ST,et al.Delay discounting in currently using and currently abstinent cocaine-dependent outpatients and non-drug-using matched controls[J].Addictive Behaviors,2006,31:1290-1294.
16 Mitchell MR,Weiss VG,Beas BS,et al.Adolescent Risk Taking,Cocaine Self-Administration,and Striatal Dopamine Signaling[J].Neuropsychopharmacology,2014,39:955-962.
17 Goudriaan AE,Oosterlaan J,de Bears E,et al.Pathological gambling:a comprehensive review of biobehavioral findings[J].Neuroscience Biobehavioral Reviews,2004,28:123-141.
18 Goudriaan AE,Oosterlaan J,de Beurs E,et al.W:Psychophysiological determinants and concomitants of deficient decision making in pathological gamblers[J].Drug and Alcohol Dependence,2006,84:231-239.
19 Barrds Loscertales A,Bustamante JC,Ventura-Campos N,et al.Lower activation in the right frontoparietal network during a counting Stroop task in a cocaine dependent group[J].Psychiatry Research Neuroimaging,2011,194:111-118.
20 Kemotn S.Brain reward circuitry beyond the mesolimbic dopamine system:a neurobiologieal theory[J].Netrrosci Biobehav Rev,2010,35:129-150.
21 Dunn BD,Dalgleish T,Lawrence AD.The somatic marker hypothesis:a critical evaluation[J].Neuroscience and Biobehavioral Reviews,2006,30:239-271.
2 Park WK.The mobile phone addiction among Korean college students[J].Korean Soc J Commun,2003,47:250-281.
3中国互联网络信息中心(CNNIC).第35次中国互联网络发展状况统计报告[EB/OL].Hnp://www.cnnic net.en/hlwfzyj/hlwxzhg/hlwtjbg/201502/t20150203_51634.htm,2015.
4熊婕,周宗奎,陈武,等.大学生手机成瘾倾向量表的编制[J].中国心理卫生杂志,2012,26:222-225.
5 Mackey S,Stewart JL,Connolly CG,et al.A voxel-based morphometry study of young occasional users of amphetaminetype stimulants and cocaine[J].Drug and Alcohol Dependence,2014,135:104-111.
6 Jin Y,Shi Y,Zhan L,et al.Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics[J].Neuro Image,2014,100:75-90.
7 Aarts E,Roelofs A.Attentional conlrol in anterior cingulated cortex based on probabilistic cueing[J].Journal of Cognitive Neuroscience,2011,23:716-727.
8 Romero MJ,Asensio S,Palall C,et al.Cocaine addiction:Diffusion tensor imaging study of the inferior frontal and anterior cingulate white matter,Psychiatry Research[J].Neuroimaging,2010,181:57-63.
9 Dong G,Wang J,Yang X,et al.Risk personality traits of Internet addiction:A longitudinal study of Intemet-addicted Chinese university students[J].Asia Pac Psychiatry,2013,5:316-321.
10 Hoogendijk WJG,Veltman DJ.Cognitive Inflexibility in ObsessiveCompulsive Disorder and Major Depression Is Associated with Distinct Neural Correlates[J].PLo S One,2013,8:e59600
11 Cao E,Su L,Liu T,et al.The relationship between impulsivity and Internet addiction in a sample of Chinese adolescents[J].European Psychiatry,2007,22:466-471.
12 Dong G,De Vito EE,Du X,et al.Impaired inhibitory control in internet addiction disorder:A functional magnetic resonance imaging study.Psychiatry Research the relationship between impulsivity and Internet addiction in a sample of Chinese adolescents[J].Neuroimaging,2012,203:153-158.
13 Dong G,Lu Q,Zhou H,et al.Impulse inhibition in people with Internet addiction disorder:Electrophysiological evidence from a Go/NoGo study[J].Neuroscience Letters,2010,485:138-142.
14 Ko CH,Hsiao S,Liu GC,et al.The characteristics of decision making potential to take risks and personality of college students with Interact addiction[J].Psychiatry Research,2010,175:121-125.
15 Heil SH,Johnson MW,Higgius ST,et al.Delay discounting in currently using and currently abstinent cocaine-dependent outpatients and non-drug-using matched controls[J].Addictive Behaviors,2006,31:1290-1294.
16 Mitchell MR,Weiss VG,Beas BS,et al.Adolescent Risk Taking,Cocaine Self-Administration,and Striatal Dopamine Signaling[J].Neuropsychopharmacology,2014,39:955-962.
17 Goudriaan AE,Oosterlaan J,de Bears E,et al.Pathological gambling:a comprehensive review of biobehavioral findings[J].Neuroscience Biobehavioral Reviews,2004,28:123-141.
18 Goudriaan AE,Oosterlaan J,de Beurs E,et al.W:Psychophysiological determinants and concomitants of deficient decision making in pathological gamblers[J].Drug and Alcohol Dependence,2006,84:231-239.
19 Barrds Loscertales A,Bustamante JC,Ventura-Campos N,et al.Lower activation in the right frontoparietal network during a counting Stroop task in a cocaine dependent group[J].Psychiatry Research Neuroimaging,2011,194:111-118.
20 Kemotn S.Brain reward circuitry beyond the mesolimbic dopamine system:a neurobiologieal theory[J].Netrrosci Biobehav Rev,2010,35:129-150.
21 Dunn BD,Dalgleish T,Lawrence AD.The somatic marker hypothesis:a critical evaluation[J].Neuroscience and Biobehavioral Reviews,2006,30:239-271.