电子竞技影响认知功能的作用机制

刘承宜, 唐璐, 孙莎莎, 白慕炜, 龚妍春, 蔺海旗

刘承宜, 唐璐, 孙莎莎, 白慕炜, 龚妍春, 蔺海旗. 电子竞技影响认知功能的作用机制[J]. 华南师范大学学报(自然科学版), 2020, 52(2): 1-8. DOI: 10.6054/j.jscnun.2020019
引用本文: 刘承宜, 唐璐, 孙莎莎, 白慕炜, 龚妍春, 蔺海旗. 电子竞技影响认知功能的作用机制[J]. 华南师范大学学报(自然科学版), 2020, 52(2): 1-8. DOI: 10.6054/j.jscnun.2020019
LIU Chengyi, TANG Lu, SUN Shasha, BAI Muwei, GONG Yanchun, LIN Haiqi. The Mechanism of Esport Influencing Cognitive Function[J]. Journal of South China Normal University (Natural Science Edition), 2020, 52(2): 1-8. DOI: 10.6054/j.jscnun.2020019
Citation: LIU Chengyi, TANG Lu, SUN Shasha, BAI Muwei, GONG Yanchun, LIN Haiqi. The Mechanism of Esport Influencing Cognitive Function[J]. Journal of South China Normal University (Natural Science Edition), 2020, 52(2): 1-8. DOI: 10.6054/j.jscnun.2020019

电子竞技影响认知功能的作用机制

基金项目: 

国家重点研发计划项目 2017YFB0403800

详细信息
    通讯作者:

    刘承宜, 教授, Email:liutcy@scnu.edu.cn

  • 中图分类号: G623.8

The Mechanism of Esport Influencing Cognitive Function

  • 摘要: 电子竞技作为新兴体育运动项目之一,受到了越来越多的关注.电子竞技对健康的影响是研究者感兴趣的一个主题.近些年来,习惯性电子竞技与认知能力之间的关系成为研究热点.通过对该领域研究进展的综述发现,习惯性电子竞技可以增强认知功能,主要通过注意功能、视觉空间功能和认知控制功能的提高、认知负荷的增大、技能习得的加快以及奖赏加工的增强等方面来实现.研究结果证实了脑的可塑性,同时表明习惯性电子竞技可以帮助人们更加有效地学习与工作.
    Abstract: As one of the emerging sports, Esport has attracted more and more attention. The impact of Esport on health is a topic of interest to researchers. In recent years, the relationship between habitual Esport and cognitive abilities had become a hot topic of research. Through a review of research progress in this field, it was found that habitual Esport could enhance cognitive function, mainly through the improvement of attention function, visual space function and cognitive control function, the increase of cognitive load, the acceleration of skill acquisition, and rewards processing enhancement. The results confirm the plasticity of the brain and show that habitual Esport can help people learn and work more effectively.
  • 复合脉冲是一组具有确定相位的脉冲序列,能够自动补偿操控误差,实现高效率高鲁棒性的量子态操控.复合脉冲是通用有效的量子态操控工具,主要被用于核磁共振[1]、量子信息[2-3]和量子光学[4-7]中两能级系统的量子操控.近年来的研究开始将复合脉冲技术用于三态和多态量子系统中[7-8].由于它在量子系统相干控制中的鲁棒性和精确性,复合脉冲序列已在原子物理[4, 6, 9]、固态量子传感器的磁力测量[10]、分子光谱[11]和原子干涉测量[12]中得到了应用.复合脉冲在多态量子系统中也有很多重要应用,例如,利用复合脉冲的鲁棒性,采用复合脉冲可构造对各种实验参数误差不敏感的高保真量子相位门[13]; 利用复合脉冲结合受激拉曼绝热通道技术,可以在冷原子系统中实现无中间激发态布居的基态到里德堡态的高效率粒子数转移[14]; 复合脉冲还可被应用于因补偿频率偏移、场的不均匀性等引起的系统性误差,提高量子操控的精确性,达到量子计算和量子模拟的要求[15-25].

    要实现精确的量子态操控,通常要求量子系统中的量子态和相互作用有明确的定义.但在实际多态量子系统中,由于偏振激光没有严格按照量子化轴设置、存在非共振耦合目标外的量子态、系统扰动易产生额外激发等因素,会在该量子系统中产生额外的量子转移通道,造成量子态操控的保真度下降.例如在超冷原子量子模拟实验中,装载于光阱或光晶格中的原子与圆偏振光相互作用时,形成光阱或光晶格的是聚焦的高斯光场,光场强度呈现不均匀性.这使得在束腰以外位置的原子感受到的相互作用与势阱中心的原子感受到的相互作用会有偏差.通过控制脉冲序列的相对相位,复合脉冲技术能够自动补偿脉冲面积、脉冲频率的偏差,有效抑制额外的量子转移通道,实现高效率的粒子数转移,保持高保真的量子态操控.

    本文为解决阶梯型三态量子系统的粒子定向转移问题,采用改进的复合脉冲操控方法,对影响粒子数转移效率和保真度的参数进行了研究.

    三能级阶梯型系统如图 1所示,利用耦合光操控粒子从初态|1〉转移到目标态|2〉上.由于耦合光偏振不纯等因素,在加入耦合光时,会产生干扰光将|2〉态和|3〉态耦合起来.粒子从初态|1〉转移到目标态|2〉的过程中,会因为耦合光的作用产生额外的干扰通道,使处于|2〉态的粒子跃迁到|3〉态上去,造成目标态转移效率降低.采用复合脉冲的方法,可以有效抑制干扰光产生的额外转移通道,保持初态|1〉到目标态|2〉的高转移效率.该过程用薛定谔方程itc(t)=H(t)c(t)描述,其中态矢量c(t)=[c1(t),c2(t),c3(t)]T.在旋波近似下,哈密顿量算符如下

    H=(/2)Δ(Π11Π22Π33)+(ˉh/2)[Ω12(t)eiφ12Π12+Ω23(t)eiφ23Π23+h.c.],
    (1)
    图  1  系统结构示意图
    注:图A为三能级阶梯型量子系统, 图B为利用Morris-Shore转换后的二能级和孤立态的系统.
    Figure  1.  The schematic diagram of system structure

    其中, Δ=Ω0-Ω是激光频率Ω相对原子跃迁频率Ω0的失谐量,Πjk=|jk|.拉比频率为Ωjk(t)=|djkE(t)|/,表征原子和光场的耦合强度,式中E(t)是激光的电场强度,djk是电偶极矩,2束激光的相位分别为ϕ12ϕ23.假设2束激光脉冲有相同的脉冲形状f(t),用总拉比频率Ω和混合角θ定义2束激光的拉比频率分别为Ω12(t)=Ωf(t)cos θΩ23(t)=Ωf(t)sin θ.

    对于阶梯型系统,在用复合脉冲将粒子数从|1〉态转移到|2〉态的过程中,可以通过控制脉冲序列的相对相位ϕ1j来抑制从|1〉态到|3〉态的转移路径.采用复合脉冲技术,即使在额外干扰光的耦合强度未知的情况下,仍可实现高效率的粒子数转移.

    利用Morris-Shore转换[6]将三能级阶梯型系统变换为由1个二能级系统和1个孤立态构成的系统:

    {|d=eiϕ12cosθ|3+eiϕ23sinθ|1|2=|2|c=eiϕ23sinθ|3+eiϕ12cosθ|1,
    (2)

    这里|2〉态和|c〉态构成一个二能级系统,|d〉态为一个孤立态.该系统的传播算子为

    U=(ab0ba0001),
    (3)

    其中,Cayley-Klein参数ab取决于脉冲面积

    A=tftiΩf(t)dt,a=cos(A/2),b=isin(A/2).

    由此可得原基失上的传播算子

    U(ϕ)=(acos2θ+ζsin2θA(aζ)BAaC(aζ)BCζcos2θ+asin2θ),
    (4)

    其中,

    A=beiϕ12cosθ,B=eiϕsinθcosθ,C=beiϕ23sinθ.

    当脉冲面积为π时,Cayley-Klein参数a=0和b=-i,代入式(4)可得

    Uπ(ϕ)=(ζsin2θieiϕ12cosθζeiϕsinθcosθieiϕ12cosθ0ieiϕ23sinθζeiϕsinθcosθieiϕ23sinθζcos2θ),
    (5)

    其中,

    ϕ=ϕ12ϕ23,ζ=exp[itftiΔ(t)dt/2].

    通过一个单脉冲,粒子可以从|1〉态转移到|2〉态,令参数设置为a=0, |b|=1,当θ=0时,为完全转移.但若θ≠0,|2〉态与|3〉态之间的耦合是非零的,部分粒子会从|2〉态转移到|3〉态或又回到|1〉态. θ对零点的偏差可以通过调节复合脉冲的相位进行补偿,n个复合脉冲的传播算子表示为

    U(n)=U(ϕn)U(ϕn1)U(ϕ2)U(ϕ1),
    (6)

    其中,ϕk=(ϕk12,ϕk23)是第k个脉冲的相位,当θ=0时,有P12=|U(n)21|2=1,通过泰勒展开θ的函数P1→2,选择合适的ϕk12ϕk23, 使θ高阶项的系数为0,由此确定脉冲序列的相位.

    复合脉冲中第k个脉冲作用时的薛定谔方程为

    [˙c1k(t)˙c2k(t)˙c3k(t)]=i2(0D0D2ΔE0E0)[c1k(t)c2k(t)c3k(t)],
    (7)

    其中,D=Ωcosθeiϕk12,D=Ωcosθeiϕk12,E=Ωsinθ×eiϕk23,E=Ωsinθeiϕk23.

    求解由n个脉冲组成的复合脉冲作用后量子态演化的结果,是将第k-1个脉冲作用后的末态作为第k个脉冲的初态,并依次求解第1, 2, 3, …, n个脉冲作用时的薛定谔方程,最后得到n个脉冲作用后的结果.假设初始1个粒子处在初态|1〉上,即c11(0)=1,n个脉冲作用后该粒子处在目标态|2〉上的概率P12=|c2n(t)|2.

    考虑共振情况,单光子失谐Δ=0,即ζ=1,矩形脉冲且脉冲面积A=π的情形.当单脉冲作用时,取相位ϕ12=0和 ϕ23=0,传播算子为

    U(1)(ϕ)=(sin2θicosθsinθcosθicosθ0isinθsinθcosθsinθcos2θ),
    (8)

    当复合脉冲为三脉冲序列时,每个脉冲的传播算子分别为U1(ϕ)、U2(ϕ)、U3(ϕ),三脉冲复合脉冲作用的总传播算子为U(3)=U3(ϕ) U2(ϕ) U1(ϕ).可得到3个脉冲的相位(ϕ12ϕ23)分别为(0,0)、(2π/3,-2π/3)和(π/6,π/6).同样,当复合脉冲为五脉冲序列时,总传播算子U(5)=U5(ϕ)U4(ϕ)U3(ϕ)U2(ϕ)U1(ϕ).每个脉冲的相位(ϕ12ϕ23)分别为(0,0)、(-4π/10,4π/10)、(-π/10,3π/10)、(7π/10,3π/10)和(-4π/10,0).矩形复合脉冲的相位和形状如图 2所示.

    图  2  复合脉冲的相位
    Figure  2.  The composite pulse phase

    将以上参数依次代入式(7),通过数值求解得到|1〉态到|2〉态的转移效率(P1→2)以及|1〉态到|3〉态的转移效率(P1→3)与混合角θ的关系如图 2所示.当θ=0,在无额外转移通道时,粒子数全部从|1〉态转移到|2〉态.当θ偏离零点并逐渐增大时,干扰光的作用逐渐增强,额外的转移通道会逐渐开启,当复合脉冲为多脉冲序列时能有效抑制额外的转移通道,使P1→2保持为1.由图 3可知,在单脉冲条件下,θ在开始偏离零点时,P1→2立即下降; 在三脉冲序列条件下,只有当θ>0.36时P1→2才开始下降; 在五脉冲序列条件下,只有当θ>0.59时P1→2才开始下降.因此,随着脉冲序列数的增加,复合脉冲对混合角θ的鲁棒性越好,抵抗额外转移通道干扰的能力越强.

    图  3  不同脉冲序列下转移概率P随混合角θ的变化
    注:图中1、3、5分别代表单脉冲、三脉冲以及五脉冲的情况,下同.
    Figure  3.  The variation of transition probability P with mixing angle θ under different pulse sequences

    进一步计算转移效率P1→2P1→3与拉比频率比值Ω23/Ω12的关系(图 4).在单脉冲条件下,只要干扰光的拉比频率大于0,P1→2即可快速降低.在三脉冲条件下,当干扰光的拉比频率大于耦合光拉比频率的40%时,P1→3才开始从1下降.而对于五脉冲,干扰光的拉比频率一直增加到耦合光拉比频率的60%时,P1→3才开始从1下降到0.999.这说明即使干扰光较强(相当于耦合光的光强),多脉冲的复合脉冲仍然能够很好地抑制额外的转移通道,保持高效率、高保真度的量子操控.在通常多态量子系统中,由于参数不完美或系统扰动产生的额外耦合强度一般远小于目标耦合的强度,即此时Ω23/Ω12 < 10%,采用多脉冲序列的复合脉冲能够完全抑制额外的转移通道,避免量子操控的保真度的降低.

    图  4  不同脉冲序列下转移概率随拉比频率比的变化
    Figure  4.  The change of transfer probability with the ratio of Rabi frequency under different pulse sequences

    其他参数不变,只改变脉冲面积,得到转移效率P1→2与混合角θ的关系(图 5).当脉冲面积偏离π时,单脉冲的P1→2即使在混合角θ为0(即没有额外耦合)时,都会明显降低.而采用三脉冲序列的复合脉冲时,当脉冲面积减为原来的一半(即π/2)、混合角θ < 0.1时,P1→2始终保持在90%以上.当脉冲面积为3π/4、混合角θ < 0.1时,P1→2能够保持在98%以上.所以多脉冲序列的复合脉冲对于脉冲面积的参数扰动,也具有很好的抗干扰能力.

    图  5  不同脉冲面积下转移概率随混合角的变化
    注:图中π/2、3π/4、π分别代表脉冲面积.
    Figure  5.  The change of transition probability with mixing angle under different pulse areas

    最后改变单光子失谐量,分别取失谐量Δ为0.1/T、0.2/T、0.5/T,这里T是脉冲宽度,计算转移效率P1→2与混合角θ的关系(图 6).在三脉冲条件下,当失谐量Δ=0.5/Tθ < 0.13时,转移效率可保持在90%以上.当失谐量较小、Δ=0.2/Tθ < 0.13时,转移效率可保持在0.98以上; 而当Δ=0.1/Tθ < 0.13时,转移效率可保持在0.99以上.由此可见,当单光子失谐量不为0、偏离共振点时,多脉冲序列的复合脉冲能够进行补偿并保持高效率的粒子数转移.

    图  6  不同失谐量下转移概率随混合角的变化
    注:黑线、红线、蓝线分别代表失谐量Δ=0.1/T、0.2/T、0.5/T的情况.
    Figure  6.  The change of transition probability with mixing angle under different detuning degrees

    复合脉冲操控量子态技术通常被用于二态量子系统,本文将该技术推广到阶梯型的三态量子系统.通过Morris-Shore变换,将三态量子系统等价转化为1个二态系统和1个孤立态,采用二态传播算子描述该量子系统的演化过程.求出n个脉冲序列复合脉冲的总传播算子U(n),当θ=0时,令P12=|U(n)21|2=1,通过泰勒展开θ的函数(P1→2),选择合适的第k个脉冲的相位(ϕk12ϕk23),使θ高阶项的系数为0,由此确定脉冲序列的相位.考虑共振时,面积为π的矩形脉冲序列与阶梯型三态量子系统的相互作用,求解含时薛定谔方程,结果表明:通过增加脉冲序列数并控制单个脉冲的相位,即可达到高效率、高鲁棒性的量子态操控和粒子数转移.即使存在额外的干扰光作用时,多脉冲序列的复合脉冲也可以很好地抑制额外的转移通道,实现高效率、高保真度的量子态操控和粒子数转移.

    进一步通过数值模拟额外通道和转移通道的拉比频率比、脉冲面积的变化、单光子失谐偏离零点等因素对转移效率的影响,结果表明:增加脉冲序列数可有效抵抗相关参数的扰动,保持高效率的粒子数转移.多脉冲序列复合脉冲的技术可被用于解决实际实验中偏振不纯、激光频率不纯、控制参数扰动等造成的量子态操控效率不高的问题.该方法对构造量子门、量子模拟等相关研究具有重要意义.

  • 图  1   习惯性玩家与非习惯性玩家在注意功能的比较[4]

    Figure  1.   The comparison of attention functions between habitual player and non-habitual player[4]

    图  2   电子竞技习惯回路的形成

    Figure  2.   The formation of Esport habit loop

    图  3   电子竞技与小脑活动的正则通路关系的可能机制[80]

    Figure  3.   The possible mechanism of the relationship between Esports and the cerebellum's NSP

  • [1] 杨越.新时代电子竞技和电子竞技产业研究[J].体育科学, 2018, 38(4):8-21. doi: 10.3969/j.issn.1004-3624.2018.04.002

    YANG Y. Research on Esports and Esports industry in the new era[J]. China Sport Science, 2018, 38(4):8-21. doi: 10.3969/j.issn.1004-3624.2018.04.002

    [2] 王东辉, 吴菲菲, 王圣明, 等.人类脑科学研究计划的进展[J].中国医学创新, 2019, 16(7):168-172. http://d.old.wanfangdata.com.cn/Periodical/zgyxcx201907044

    WU D H, WU F F, WANG S M, et al. Progress of human brain science research program[J]. Medical Innovation of China, 2019, 16(7):168-172. http://d.old.wanfangdata.com.cn/Periodical/zgyxcx201907044

    [3]

    ANGUERA J A, BOCCANFUSO J, RINTOUL J L, et al. Video game training enhances cognitive control in older adults[J]. Nature, 2013, 501:97-101. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=87e6cb2e8107399f21179ede69c39514

    [4]

    BAVELIER D, DAVIDSON R J. Games to do you good[J]. Nature, 2013, 494:425-426. doi: 10.1038/494425a

    [5]

    MAARTEN B J, JETSE G, ERIK H, et al. The effects of video games on laparoscopic simulator skills[J]. American Journal of Surgery, 2014, 208(1):151-156. doi: 10.1016/j.amjsurg.2013.11.006

    [6]

    LI L, CHEN R, CHEN J. Playing action video games improves visuomotor control[J]. Psychological Science, 2016, 27(8):1092-1098. doi: 10.1177/0956797616650300

    [7]

    GAMBACORTA C, NAHUM M, VEDAMURTHY I, et al. An action video game for the treatment of amblyopia in children:a feasibility study[J]. Vision Research, 2018, 148:1-14. doi: 10.1016/j.visres.2018.04.005

    [8]

    VOSSEL S, GENG J J, FINK G R. Dorsal and ventral attention systems:distinct neural circuits but collaborative roles[J]. Neuroscientist, 2014, 20(2):150-159. doi: 10.1177/1073858413494269

    [9]

    BAVELIER D, ACHTMAN R, MANI M, et al. Neural bases of selective attention in action video game players[J]. Vision Research, 2012, 61:132-143. doi: 10.1016/j.visres.2011.08.007

    [10]

    BAVELIER D, SHAWN G C, POUGET A, et al. Brain plasticity through the life span:learning to learn and action video games[J]. Annual Review of Neuroscience, 2012, 35:391-416. doi: 10.1146/annurev-neuro-060909-152832

    [11]

    PRAKASH R S, LEON A A D, MOURANY L, et al. Examining neural correlates of skill acquisition in a complex videogame training program[J]. Frontiers in Human Neuroscience, 2012, 6:115/1-11. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=Doaj000003593484

    [12]

    STRENZIOK M, PARASURAMAN R, CLARKE E, et al. Neurocognitive enhancement in older adults:comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity[J]. NeuroImage, 2014, 85:1027-1039. doi: 10.1016/j.neuroimage.2013.07.069

    [13]

    GONG D, HE H, MA W, et al. Functional integration between salience and central executive networks:a role for action video game experience[J]. Neural Plasticity, 2016, 2016:9803165/1-9. http://cn.bing.com/academic/profile?id=84e2ab9f218ce27a005123f7ae4ee7e5&encoded=0&v=paper_preview&mkt=zh-cn

    [14]

    GREEN C S, BAVELIER D. Action video game modifies visual selective attention[J]. Nature, 2003, 423:534-537. doi: 10.1038/nature01647

    [15]

    KAUFMAN L D, PRATT J, LEVINE B, et al. Executive deficits detected in mild Alzheimer's disease using the antisaccade task[J]. Brain and Behavior, 2012, 2(1):15-21. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3343295

    [16]

    PALAUS M, MARRON E M, VIEJO-SOBERA R, et al. Neural basis of video gaming:a Systematic review[J]. Frontiers in Human Neuroscience, 2017, 11:248/1-40. http://cn.bing.com/academic/profile?id=4016afbb86ad167ee74d2051ac029f5a&encoded=0&v=paper_preview&mkt=zh-cn

    [17]

    KRAVITZ D J, SALEEM K S, BAKER C I, et al. A new neural framework for visuospatial processing[J]. Nature Reviews Neuroscience, 2011, 12(4):217-230. doi: 10.1038/nrn3008

    [18]

    LEE A, YEUNG L, BARENSE M. The hippocampus and visual perception[J]. Frontiers in Human Neuroscience, 2012, 6:91/1-17. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3328126

    [19]

    KVHN S, GALLINAT J. Amount of lifetime video gaming is positively associated with entorhinal, hippocampal and occipital volume[J]. Molecular Psychiatry, 2014, 19(7):842-847. doi: 10.1038/mp.2013.100

    [20]

    SCHMIDT-HIEBER C, HÄUSSER M. Cellular mechanisms of spatial navigation in the medial entorhinal cortex[J]. Nature Neuroscience, 2013, 16(3):325-331. doi: 10.1038/nn.3340

    [21]

    MILLER J F, FRIED I, SUTHANA N, et al. Repeating spatial activations in human entorhinal cortex[J]. Current Biology, 2015, 25(8):1080-1085. doi: 10.1016/j.cub.2015.02.045

    [22]

    KVHN S, GLEICH T, LORENZ R C, et al. Playing super mario induces structural brain plasticity:gray matter changes resulting from training with a commercial video game[J]. Molecular Psychiatry, 2014, 19(2):265-271. doi: 10.1038/mp.2013.120

    [23]

    VOGAN V M, MORGAN B R, POWELL T L, et al. The neurodevelopmental differences of increasing verbal working memory demand in children and adults[J]. Developmental Cognitive Neuroscience, 2016, 17:19-27. doi: 10.1016/j.dcn.2015.10.008

    [24]

    BARROUILLET P, BERNARDIN S, PORTRAT S, et al. Time and cognitive load in working memory[J]. Journal of experimental psychology:learning, memory and cognition, 2007, 33(3):570-585. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3078384

    [25]

    BROOKINGS J, WILSON G, SWAIN C. Psychophysiological responses to changes in workload during simulated air traffic control[J]. Biological Psychology, 1996, 42(3):361-377. doi: 10.1016/0301-0511(95)05167-8

    [26]

    SHEIKHOLESLAMI C, YUAN H, HE E, et al. A high resolution EEG study of dynamic brain activity during video game play[C] //Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Piscataway: IEEE, 2007: 2489-2491.

    [27]

    IZZETOGLU K, BUNCE S, ONARAL B, et al. Functional optical brain imaging using near-infrared during cognitive tasks[J]. International Journal of Human-Computer Interaction, 2004, 17(2):211-227. doi: 10.1207/s15327590ijhc1702_6

    [28]

    MCMAHAN T, PARBERRY I, PARSONS T D. Modality specific assessment of video game player's experience using the Emotiv[J]. Entertainment Computing, 2015, 7:1-6. doi: 10.1016/j.entcom.2015.03.001

    [29]

    IACCARINO H F, SINGER A C, MARTORELL A J, et al. Gamma frequency entrainment attenuates amyloid load and modifies microglia[J]. Nature, 2016, 540:230-235. doi: 10.1038/nature20587

    [30]

    MANDREKAR S, JIANG Q, LEE C Y D, et al. Microglia mediate the clearance of soluble β through fluid phase macropinocytosis[J]. Journal of Neuroscience, 2009, 29(13):4252-4262. doi: 10.1523/JNEUROSCI.5572-08.2009

    [31]

    OBESO I, ROBLES N, MARRÓN E M, et al. Dissociating the role of the pre-SMA in response inhibition and swit-ching:a combined online and offline TMS approach[J]. Frontiers in Human Neuroscience, 2013, 7:150/1-9. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3629293

    [32]

    NACHEV P, KENNARD C, HUSAIN M. Functional role of the supplementary and pre-supplementary motor areas[J]. Nature Reviews Neuroscience, 2008, 9(11):856-869. doi: 10.1038/nrn2478

    [33]

    ALVAREZ J A, EMORY E. Executive function and the frontal lobes:a meta-analytic review[J]. Neuropsycho-logy Review, 2006, 16(1):17-42. doi: 10.1007-s11065-006-9002-x/

    [34]

    KVHN S, LORENZ R, BANASCHEWSKI T, et al. Positive association of video game playing with left frontal cortical thickness in adolescents[J]. PLoS One, 2014, 9(3):e91506/1-6. http://cn.bing.com/academic/profile?id=944febb9195e344c1450fb6fffcc4131&encoded=0&v=paper_preview&mkt=zh-cn

    [35]

    GLEICH T, LORENZ R C, GALLINAT J, et al. Functional changes in the reward circuit in response to gaming-related cues after training with a commercial video game[J]. Neuroimage, 2017, 152:467-475. doi: 10.1016/j.neuroimage.2017.03.032

    [36]

    WEST G, ZENDEL B, KONISHI K, et al. Playing Super Mario 64 increases hippocampal grey matter in older adults[J]. PLoS One, 2017, 12(12):e0187779/1-7. http://cn.bing.com/academic/profile?id=fcf79beaf8d8a4efa8af73d6cb67575b&encoded=0&v=paper_preview&mkt=zh-cn

    [37]

    SMITH E E, JONIDES J. Storage and executive processes in the frontal lobes[J]. Science, 1999, 283:1657-1661. http://cn.bing.com/academic/profile?id=ec42d80cd21f220b3578d4c1eb6711c1&encoded=0&v=paper_preview&mkt=zh-cn

    [38]

    KUMAR S, ZOMORRODI R, GHAZALA Z, et al. Extent of dorsolateral prefrontal cortex plasticity and its association with working memory in patients with Alzheimer disease[J]. JAMA Psychiatry, 2017, 74(12):1266-1274. doi: 10.1001/jamapsychiatry.2017.3292

    [39]

    BADDELEY A D, BRESSI S, SALA S D, et al. The decline of working memory in Alzheimer's disease[J]. Brain, 1991, 114(6):2521-2542. doi: 10.1093/brain/114.6.2521

    [40]

    HUNTLEY J D, HOWARD R J. Working memory in early Alzheimer's disease:a neuropsychological review[J]. International Journal of Geriatric Psychiatry, 2010, 25(2):121-132. doi: 10.1002/gps.2314

    [41]

    VOYTEK B, DAVIS M, YAGO E, et al. Dynamic neuroplasticity after human prefrontal Cortex damage[J]. Neuron, 2010, 68(3):401-408. doi: 10.1016/j.neuron.2010.09.018

    [42]

    SUSANNE J V V, SAWYER E K, CLOVER L, et al. Prefrontal cortex cytoarchitecture in normal aging and Alzheimer's disease:a relationship with IQ[J]. Brain Structure and Function, 2012, 217(4):797-808. doi: 10.1007/s00429-012-0381-x

    [43]

    BISWAL B B, ELDRETH D A, MOTES M A, et al. Task-dependent individual differences in prefrontal connectivity[J]. Cerebral Cortex, 2010, 20(9):2188-2197. doi: 10.1093/cercor/bhp284

    [44]

    MATSUDA G, HIRAKI K. Prefrontal Cortex deactivation during video game play[J]. Gaming, Simulations, and Society, 2005, 153:101-109. http://cn.bing.com/academic/profile?id=22cee32beead6cf0e404d3062c0433ae&encoded=0&v=paper_preview&mkt=zh-cn

    [45]

    NAGAMITSU S, NAGANO M, YAMASHITA Y, et al. Prefrontal cerebral blood volume patterns while playing video games:a near-infrared spectroscopy study[J]. Brain and Development, 2006, 28(5):315-321. doi: 10.1016/j.braindev.2005.11.008

    [46]

    QUIROGA R Q, REDDY L, KREIMAN G, et al. Invariant visual representation by single neurons in the human brain[J]. Nature, 2005, 435:1102-1107. doi: 10.1038/nature03687

    [47]

    GOBEL E W, PARRISH T B, REBER P J. Neural correlates of skill acquisition:decreased cortical activity during a serial interception sequence learning task[J]. NeuroImage, 2011, 58(4):1150-1157. doi: 10.1016/j.neuroimage.2011.06.090

    [48]

    ERICKSON K I, BOOT W R, BASAK C, et al. Striatal volume predicts level of video game skill acquisition[J]. Cerebral Cortex, 2010, 20(11):2522-2530. doi: 10.1093/cercor/bhp293

    [49]

    VO L, WALTHER D, KRAMER A, et al. Predicting individuals' learning success from patterns of pre-learning MRI activity[J]. PLoS One, 2011, 6(1):e16093/1-9. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3021541

    [50]

    KOEPP M J, GUNN R N, LAWRENCE A D, et al. Evidence for striatal dopamine release during a video game[J]. Nature, 1998, 393:266-268. doi: 10.1038/30498

    [51]

    ANDERSON J R, BOTHELL D, FINCHAM J M, et al. The sequential structure of brain activation predicts skill[J]. Neuropsychologia, 2016, 81:94-106. doi: 10.1016/j.neuropsychologia.2015.12.014

    [52]

    HABER S N. Neuroanatomy of reward:a view from the ventral striatum:Neurobiology of sensation and reward[M]. Bethesda MD:NCBI Bookshelf, 2011:1-27.

    [53]

    VOLKOW N D, WANG G J, FOWLER J S, et al. Addiction:decreased reward sensitivity and increased expectation sensitivity conspire to overwhelm the brain's control circuit[J]. BioEssays, 2010, 32(9):748-755. doi: 10.1002/bies.201000042

    [54]

    HEINZ A, BECK A, GRVSSER S M, et al. Identifying the neural circuitry of alcohol craving and relapse vulnerabi-lity[J]. Addiction Biology, 2009, 14(1):108-118. doi: 10.1111/j.1369-1600.2008.00136.x

    [55]

    FENG Q, CHEN X, SUN J, et al. Voxel-level comparison of arterial spin-labeled perfusion magnetic resonance imaging in adolescents with internet gaming addiction[J]. Behavioral and Brain Functions, 2013, 9:33/1-11. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_3751515

    [56]

    KO C, LIU G, YEN J, et al. Brain correlates of craving for online gaming under cue exposure in subjects with Internet gaming addiction and in remitted subjects[J]. Addiction Biology, 2013, 18(3):559-569. doi: 10.1111/j.1369-1600.2011.00405.x

    [57]

    JIN C, ZHANG T, CAI C, et al. Abnormal prefrontal cortex resting state functional connectivity and severity of internet gaming disorder[J]. Brain Imaging and Behavior, 2016, 10(3):719-729. doi: 10.1007/s11682-015-9439-8

    [58]

    WITTMANN B C, SCHOTT B H, GUDERIAN S, et al. Reward-related fMRI activation of dopaminergic midbrain is associated with enhanced hippocampus-dependent long-term memory formation[J]. Neuron, 2005, 45(3):459-467. doi: 10.1016/j.neuron.2005.01.010

    [59]

    ADCOCK R A, THANGAVEL A, WHITFIELD-GABRIELI S, et al. Reward-motivated learning:mesolimbic activation precedes memory formation[J]. Neuron, 2006, 50(3):507-517. doi: 10.1016/j.neuron.2006.03.036

    [60]

    FENG J, SPENCE I, PRATT J. Playing an action video game reduces gender differences in spatial cognition[J]. Psychological Science, 2007, 18(10):850-855. doi: 10.1111/j.1467-9280.2007.01990.x

    [61]

    DYE M, BAVELIER D. Differential development of visual attention skills in school-age children[J]. Vision Research, 2010, 50(4):452-459. doi: 10.1016/j.visres.2009.10.010

    [62]

    WANG P, LIU H, ZHU X, et al. Action video game training for healthy adults:a meta-analytic study[J]. Frontiers in Psychology, 2016, 7:907/1-17. http://cn.bing.com/academic/profile?id=1d37c1ba3ba0ab487f21e1787ff612e2&encoded=0&v=paper_preview&mkt=zh-cn

    [63]

    POWERS K L, BROOKS P J, ALDRICH N J, et al. Effects of video-game play on information processing:a meta-analytic investigation[J]. Psychonomic Bulletin and Review, 2013, 20(6):1055-1079. doi: 10.3758/s13423-013-0418-z

    [64] 田麦久, 麻雪田, 黄新河, 等.项群训练理论及其应用[J].体育科学, 1990(6):29-35. http://www.cnki.com.cn/Article/CJFD1990-TYKX199006008.htm

    TIAN M J, MA X T, HUANG XH, et al. The training theory of sports group and its application[J]. China Sport Science, 1990(6):29-35. http://www.cnki.com.cn/Article/CJFD1990-TYKX199006008.htm

    [65]

    JASSAL D S, MOFFAT D, KRAHN J, et al. Cardiac injury markers in non-elite marathon runners[J]. International Journal of Sports Medicine, 2009, 30(2):75-79. doi: 10.1055/s-0028-1104572

    [66]

    FREDERICSON M, MISRA A K. Epidemiology and aetiology of marathon running injuries[J]. Sports Medicine, 2007, 37(4/5):437-439. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=b2fdc13ea2413de730f1e83de1dad35b

    [67]

    HAMLIN M J, LIZAMORE C A, HOPKINS W G. The effect of natural or simulated altitude training on high-intensity intermittent running performance in team-sport athletes:a meta-analysis[J]. Sports Medicine, 2018, 42(2):431-446. http://cn.bing.com/academic/profile?id=d7745aa0aa3be6d30c2f7cab90c6dfba&encoded=0&v=paper_preview&mkt=zh-cn

    [68]

    STOCKDALE L, COYNE S M. Video game addiction in emerging adulthood:cross-sectional evidence of pathology in video game addicts as compared to matched healthy controls[J]. Journal of Affective Disorders, 2018, 255:265-272. http://cn.bing.com/academic/profile?id=baf4b4c63b16b84b33298f5c1427ab10&encoded=0&v=paper_preview&mkt=zh-cn

    [69]

    EVREN B, EVREN C, DALBUDAK E, et al. The impact of depression, anxiety, neuroticism, and severity of Internet addiction symptoms on the relationship between probable ADHD and severity of insomnia among young adults[J]. Psychiatry Research, 2019, 271:726-731. doi: 10.1016/j.psychres.2018.12.010

    [70]

    OWEN A M, HAMPSHIRE A, GRAHN J A, et al. Putting brain training to the test[J]. Nature, 2010, 465:775-778. doi: 10.1038/nature09042

    [71]

    RAICHLE M E, MACLEOD A M, SNYDER A Z, et al. A default mode of brain function[J]. Proceedings of the national academy of science of the United States of America, 2001, 98(2):676-682. doi: 10.1073/pnas.98.2.676

    [72]

    DENNIS E L, THOMPSON P M. Functional brain connectivity using fMRI in aging and Alzheimer's disease[J]. Neuropsychology Review, 2014, 24(1):49-62. doi: 10.1007/s11065-014-9249-6

    [73]

    HUSKEY R, CRAIGHEAD B, MILLER M B, et al. Does intrinsic reward motivate cognitive control? a naturalistic-fMRI study based on the synchronization theory of flow[J]. Cognitive, Affective & Behavioral Neuroscience, 2018, 18(5):902-924. http://cn.bing.com/academic/profile?id=ab92d7a8ea1df8a244eaea3f07a47b2d&encoded=0&v=paper_preview&mkt=zh-cn

    [74]

    ULRICH M, KELLER J, GRÖN G. Dorsal raphe nucleus down-regulates medial prefrontal Cortex during experience of flow[J]. Frontiers in Behavioral Neuroscience, 2016, 10:169/1-9. http://cn.bing.com/academic/profile?id=0c5297b103968b0f45992a6a1441add1&encoded=0&v=paper_preview&mkt=zh-cn

    [75]

    LIU T C Y, TANG X M, DUAN R, et al. The mitochondrial Na+/Ca2+ exchanger is necessary but not sufficient for Ca2+ homeostasis and viability[J]. Advances in Experimental Medicine and Biology, 2018, 1072:281-285. doi: 10.1007/978-3-319-91287-5_45

    [76]

    LILJEHOLM M, DUNNE S, O'DOHERTY J. Differentiating neural systems mediating the acquisition vs. expression of goal-directed and habitual behavioral control[J]. European Journal of Neuroscience, 2015, 41(10):1358-1371. doi: 10.1111/ejn.12897

    [77]

    HERCULANO-HOUZEL S. Coordinated scaling of cortical and cerebellar numbers of neurons[J]. Frontiers in Neuroanatomy, 2010, 4(12):1-8. http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_2839851

    [78]

    VANDERVERT L. The prominent role of the cerebellum in the learning, origin and advancement of culture[J]. Cerebellum & Ataxias, 2016, 3(1):1-13. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=WK_MED201912251464

    [79]

    WAGNER M J, KIM T H, SAVALL J, et al. Cerebellar granule cells encode the expectation of reward[J]. Nature, 2017, 544:96-100. doi: 10.1038/nature21726

    [80]

    LIU T, WU D, ZHU L, et al. Microenvironment dependent photobiomodulation on function-specific signal transduction pathways[J]. International Journal of Photoenergy, 2014, 2014:904304/1-8. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=eba8053edca39d839e50453c6e212071

    [81]

    LIU C, LIU G, HU S, et al. Quantitative biology of exercise-induced signal transduction pathways[J]. Advances in Experimental Medicine & Biology, 2017, 977:419-424. doi: 10.1007/978-3-319-55231-6_54

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