大规模脑网络 - 版本历史

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	==参考文献==		==参考文献==
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		+	== 编者推荐 ==
		+	===集智课程===
		+	====[https://campus.swarma.org/course/4370 神经动力学模型读书会]====
		+	人类大脑是一个由数以百亿计的神经元相互连接所构成的复杂系统。自神经科学这一学科建立以来，从解析神经元之间的相互作用机理、到刻画皮层柱之间的连接形式、再到探究脑区间不同认知功能的分离与整合模式，无数科学家试图从不同尺度研究大脑，以期揭示人脑这一最为复杂的神经系统的工作模式，进而理解语言、情绪、记忆和社会交往等高级认知活动的底层神经机制，并一定程度上启发通用人工智能机器人的设计。
		+
		+	近年来，脱胎于系统科学的动力学建模方法，逐渐被广泛地应用于神经科学研究中，其作为一种绝佳的数理工具，愈发地受到研究人员的重视，在类脑计算、脑认知原理解析和脑重大疾病致病机理探索等具体方面，发挥着不可替代的作用。
		+
		+	本着促进神经科学、系统科学以及计算机科学等不同领域的学术工作者的交流与合作，激发有志于加入脑科学与类脑研究这一领域的同学们的研究兴趣，来自国内外多所知名高校的专家学者（详见发起人介绍）共同发起了「神经动力学模型」读书会，聚焦于神经科学中的动力学建模这一前沿课题，讨论他们在研究一线中遇到的实际困惑，对相关文献进行深入梳理、激发跨学科的学术火花。
		+
		+
		+	====[https://campus.swarma.org/course/1925 廖旭红：从脑网络到认知]====
		+	脑是自然界最为复杂的系统之一。近年来，研究者逐渐意识到脑网络是人脑进行高效信息传输、实现各种认知功能的基础，开始全面而细致刻画人脑结构和功能连接模式。该报告将从基于磁共振成像技术和复杂网络理论的脑网络研究框架出发，探讨人脑结构和功能的组织原则以及认知行为的脑机制。
		+
		+
		+	====[https://campus.swarma.org/course/3541 脑网络——大脑功能的物理机制研究]====
		+	该讲座主要介绍大脑网络的基本概念、脑功能性质、脑结构网与功能网的构造及性质、网络集体行为的动力学建模等。然后，将详细地讲解部分同步化的机制如奇异态、遥同步与集团同步等；简要介绍大脑网络上的信号传播，特别是遥传播出现的条件。并讨论一些典型的应用如男女智商差别的微观机制与精神疾病与大脑结构变异的关系等。
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←上一版本		2022年4月10日 (日) 07:53的版本
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−	脑网络活动的中断与诸多神经精神疾病密切相关，如抑郁症、老年痴呆症、自闭症谱系障碍、精神分裂症、多动症<ref name=":5">{{cite journal \|last1=Griffiths \|first1=Kristi R. \|last2=Braund \|first2=Taylor A. \|last3=Kohn \|first3=Michael R. \|last4=Clarke \|first4=Simon \|last5=Williams \|first5=Leanne M. \|last6=Korgaonkar \|first6=Mayuresh S. \|title=Structural brain network topology underpinning ADHD and response to methylphenidate treatment \|journal=Translational Psychiatry \|date=2 March 2021 \|volume=11 \|issue=1 \|pages=1–9 \|doi=10.1038/s41398-021-01278-x \| pmc=7925571 ~~\|pmid=33654073~~ \|url=https://www.nature.com/articles/s41398-021-01278-x#citeas \|access-date=16 November 2021}}</ref>'''和'''躁郁症Bipolar disorder<ref name=":6">{{Cite journal\|url=https://www.researchgate.net/publication/51639686\|title=Large-scale brain networks and psychopathology: A unifying triple network model\|last=Menon\|first=Vinod\|journal=Trends in Cognitive Sciences\|date=2011-09-09\|volume=15\|issue=10\|pages=483–506\|doi=10.1016/j.tics.2011.08.003\|pmid=21908230}}</ref>'''。	+	脑网络活动的中断与诸多神经精神疾病密切相关，如抑郁症、老年痴呆症、自闭症谱系障碍、精神分裂症、多动症<ref name=":5">{{cite journal \|last1=Griffiths \|first1=Kristi R. \|last2=Braund \|first2=Taylor A. \|last3=Kohn \|first3=Michael R. \|last4=Clarke \|first4=Simon \|last5=Williams \|first5=Leanne M. \|last6=Korgaonkar \|first6=Mayuresh S. \|title=Structural brain network topology underpinning ADHD and response to methylphenidate treatment \|journal=Translational Psychiatry \|date=2 March 2021 \|volume=11 \|issue=1 \|pages=1–9 \|doi=10.1038/s41398-021-01278-x \| pmc=7925571\|url=https://www.nature.com/articles/s41398-021-01278-x#citeas \|access-date=16 November 2021}}</ref>'''和'''躁郁症Bipolar disorder<ref name=":6">{{Cite journal\|url=https://www.researchgate.net/publication/51639686\|title=Large-scale brain networks and psychopathology: A unifying triple network model\|last=Menon\|first=Vinod\|journal=Trends in Cognitive Sciences\|date=2011-09-09\|volume=15\|issue=10\|pages=483–506\|doi=10.1016/j.tics.2011.08.003\|pmid=21908230}}</ref>'''。

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 }}
-'''大规模脑网络 Large-scale brain networks'''(也称为'''内在大脑网络 Intrinsic brain networks''')是在对基于'''血氧水平依赖效应BOLD'''的功能性磁共振成像 Functional magnetic resonance imaging(fMRI)信号<ref name=Riedl>{{cite journal|last1=Riedl|first1=Valentin|last2=Utz|first2=Lukas|last3=Castrillón|first3=Gabriel|last4=Grimmer|first4=Timo|last5=Rauschecker|first5=Josef P.|last6=Ploner|first6=Markus|last7=Friston|first7=Karl J.|last8=Drzezga|first8=Alexander|last9=Sorg|first9=Christian|title=Metabolic connectivity mapping reveals effective connectivity in the resting human brain|journal=PNAS|date=January 12, 2016|volume=113|issue=2|pages=428–433|doi=10.1073/pnas.1513752113|pmid=26712010|pmc=4720331|bibcode=2016PNAS..113..428R|doi-access=free}}</ref>的统计分析或其他记录方法(如'''脑电图 Electroencephalography(EEG)<ref name=":1">{{Cite journal|last1=Foster|first1=Brett L.|last2=Parvizi|first2=Josef|date=2012-03-01|title=Resting oscillations and cross-frequency coupling in the human posteromedial cortex|journal=NeuroImage|volume=60|issue=1|pages=384–391|doi=10.1016/j.neuroimage.2011.12.019|pmid=22227048|issn=1053-8119|pmc=3596417}}</ref>'''、'''正电子发射断层扫描技术 Positron emission tomography(PET)<ref name=":2">{{Cite journal|last1=Buckner|first1=Randy L.|last2=Andrews‐Hanna|first2=Jessica R.|last3=Schacter|first3=Daniel L.|date=2008|title=The Brain's Default Network|journal=Annals of the New York Academy of Sciences|language=en|volume=1124|issue=1|pages=1–38|doi=10.1196/annals.1440.011|pmid=18400922|issn=1749-6632|bibcode=2008NYASA1124....1B|s2cid=3167595}}</ref>'''和'''脑磁图 Magnetoencephalography(MEG)<ref name=":3">{{Cite journal|last1=Morris|first1=Peter G.|last2=Smith|first2=Stephen M.|last3=Barnes|first3=Gareth R.|last4=Stephenson|first4=Mary C.|last5=Hale|first5=Joanne R.|last6=Price|first6=Darren|last7=Luckhoo|first7=Henry|last8=Woolrich|first8=Mark|last9=Brookes|first9=Matthew J.|date=2011-10-04|title=Investigating the electrophysiological basis of resting state networks using magnetoencephalography|journal=Proceedings of the National Academy of Sciences|language=en|volume=108|issue=40|pages=16783–16788|doi=10.1073/pnas.1112685108|issn=0027-8424|pmid=21930901|pmc=3189080|bibcode=2011PNAS..10816783B|doi-access=free}}</ref>''')中，表现出'''功能连接 Functional connectivity'''的'''脑区 Brain regions'''的集合。根据神经科学中一个新出现的范式，认知任务不是由单个脑区独立执行的，而是由几个互不相连的脑区“功能连接”组成的网络执行的。功能连接网络可以通过'''数据聚类Cluster analysis'''、空间'''独立元素分析ICA'''、种子点方法等算法来发现。<ref name="Petersen">{{cite journal|last1=Petersen|first1=Steven|last2=Sporns|first2=Olaf|title=Brain Networks and Cognitive Architectures|journal=Neuron|date=October 2015|volume=88|issue=1|pages=207–219|doi=10.1016/j.neuron.2015.09.027|pmid=26447582|pmc=4598639 }}</ref>同步的脑区也可以用脑电图、脑磁图或其他动态脑信号的远程同步来识别。.<ref name=Bressler>{{cite journal|last1=Bressler|first1=Steven L.|last2=Menon|first2=Vinod|s2cid=5967761|title=Large scale brain networks in cognition: emerging methods and principles|journal=Trends in Cognitive Sciences|date=June 2010|volume=14|issue=6|pages=233–290|doi=10.1016/j.tics.2010.04.004|url=http://www.cell.com/trends/cognitive-sciences/issue?pii=S1364-6613(10)X0005-5|accessdate=24 January 2016|pmid=20493761}}</ref>
+'''大规模脑网络 Large-scale brain networks'''(也称为'''内在大脑网络 Intrinsic brain networks''')是在对基于'''血氧水平依赖效应BOLD'''的功能性磁共振成像 Functional magnetic resonance imaging(fMRI)信号<ref name=Riedl>{{cite journal|last1=Riedl|first1=Valentin|last2=Utz|first2=Lukas|last3=Castrillón|first3=Gabriel|last4=Grimmer|first4=Timo|last5=Rauschecker|first5=Josef P.|last6=Ploner|first6=Markus|last7=Friston|first7=Karl J.|last8=Drzezga|first8=Alexander|last9=Sorg|first9=Christian|title=Metabolic connectivity mapping reveals effective connectivity in the resting human brain|journal=PNAS|date=January 12, 2016|volume=113|issue=2|pages=428–433|doi=10.1073/pnas.1513752113|pmid=26712010|pmc=4720331|bibcode=2016PNAS..113..428R|doi-access=free}}</ref>的统计分析或其他记录方法(如'''脑电图 Electroencephalography(EEG)<ref name=":1">{{Cite journal|last1=Foster|first1=Brett L.|last2=Parvizi|first2=Josef|date=2012-03-01|title=Resting oscillations and cross-frequency coupling in the human posteromedial cortex|journal=NeuroImage|volume=60|issue=1|pages=384–391|doi=10.1016/j.neuroimage.2011.12.019|pmid=22227048|issn=1053-8119|pmc=3596417}}</ref>'''、'''正电子发射断层扫描技术 Positron emission tomography(PET)<ref name=":2">{{Cite journal|last1=Buckner|first1=Randy L.|last2=Andrews‐Hanna|first2=Jessica R.|last3=Schacter|first3=Daniel L.|date=2008|title=The Brain's Default Network|journal=Annals of the New York Academy of Sciences|language=en|volume=1124|issue=1|pages=1–38|doi=10.1196/annals.1440.011|pmid=18400922|issn=1749-6632|bibcode=2008NYASA1124....1B}}</ref>'''和'''脑磁图 Magnetoencephalography(MEG)<ref name=":3">{{Cite journal|last1=Morris|first1=Peter G.|last2=Smith|first2=Stephen M.|last3=Barnes|first3=Gareth R.|last4=Stephenson|first4=Mary C.|last5=Hale|first5=Joanne R.|last6=Price|first6=Darren|last7=Luckhoo|first7=Henry|last8=Woolrich|first8=Mark|last9=Brookes|first9=Matthew J.|date=2011-10-04|title=Investigating the electrophysiological basis of resting state networks using magnetoencephalography|journal=Proceedings of the National Academy of Sciences|language=en|volume=108|issue=40|pages=16783–16788|doi=10.1073/pnas.1112685108|issn=0027-8424|pmid=21930901|pmc=3189080|bibcode=2011PNAS..10816783B|doi-access=free}}</ref>''')中，表现出'''功能连接 Functional connectivity'''的'''脑区 Brain regions'''的集合。根据神经科学中一个新出现的范式，认知任务不是由单个脑区独立执行的，而是由几个互不相连的脑区“功能连接”组成的网络执行的。功能连接网络可以通过'''数据聚类Cluster analysis'''、空间'''独立元素分析ICA'''、种子点方法等算法来发现。<ref name="Petersen">{{cite journal|last1=Petersen|first1=Steven|last2=Sporns|first2=Olaf|title=Brain Networks and Cognitive Architectures|journal=Neuron|date=October 2015|volume=88|issue=1|pages=207–219|doi=10.1016/j.neuron.2015.09.027|pmid=26447582|pmc=4598639 }}</ref>同步的脑区也可以用脑电图、脑磁图或其他动态脑信号的远程同步来识别。.<ref name=Bressler>{{cite journal|last1=Bressler|first1=Steven L.|last2=Menon|first2=Vinod|title=Large scale brain networks in cognition: emerging methods and principles|journal=Trends in Cognitive Sciences|date=June 2010|volume=14|issue=6|pages=233–290|doi=10.1016/j.tics.2010.04.004|url=http://www.cell.com/trends/cognitive-sciences/issue?pii=S1364-6613(10)X0005-5|accessdate=24 January 2016|pmid=20493761}}</ref>
@@ 第13行： / 第13行： @@
-脑网络活动的中断与诸多神经精神疾病密切相关，如抑郁症、老年痴呆症、自闭症谱系障碍、精神分裂症、多动症<ref name=":5">{{cite journal |last1=Griffiths |first1=Kristi R. |last2=Braund |first2=Taylor A. |last3=Kohn |first3=Michael R. |last4=Clarke |first4=Simon |last5=Williams |first5=Leanne M. |last6=Korgaonkar |first6=Mayuresh S. |title=Structural brain network topology underpinning ADHD and response to methylphenidate treatment |journal=Translational Psychiatry |date=2 March 2021 |volume=11 |issue=1 |pages=1–9 |doi=10.1038/s41398-021-01278-x | pmc=7925571 |pmid=33654073 |url=https://www.nature.com/articles/s41398-021-01278-x#citeas |access-date=16 November 2021}}</ref>'''和'''躁郁症Bipolar disorder<ref name=":6">{{Cite journal|url=https://www.researchgate.net/publication/51639686|title=Large-scale brain networks and psychopathology: A unifying triple network model|last=Menon|first=Vinod|s2cid=26653572|journal=Trends in Cognitive Sciences|date=2011-09-09|volume=15|issue=10|pages=483–506|doi=10.1016/j.tics.2011.08.003|pmid=21908230}}</ref>'''。
+脑网络活动的中断与诸多神经精神疾病密切相关，如抑郁症、老年痴呆症、自闭症谱系障碍、精神分裂症、多动症<ref name=":5">{{cite journal |last1=Griffiths |first1=Kristi R. |last2=Braund |first2=Taylor A. |last3=Kohn |first3=Michael R. |last4=Clarke |first4=Simon |last5=Williams |first5=Leanne M. |last6=Korgaonkar |first6=Mayuresh S. |title=Structural brain network topology underpinning ADHD and response to methylphenidate treatment |journal=Translational Psychiatry |date=2 March 2021 |volume=11 |issue=1 |pages=1–9 |doi=10.1038/s41398-021-01278-x | pmc=7925571 |pmid=33654073 |url=https://www.nature.com/articles/s41398-021-01278-x#citeas |access-date=16 November 2021}}</ref>'''和'''躁郁症Bipolar disorder<ref name=":6">{{Cite journal|url=https://www.researchgate.net/publication/51639686|title=Large-scale brain networks and psychopathology: A unifying triple network model|last=Menon|first=Vinod|journal=Trends in Cognitive Sciences|date=2011-09-09|volume=15|issue=10|pages=483–506|doi=10.1016/j.tics.2011.08.003|pmid=21908230}}</ref>'''。
 ==核心网络==
 [[File:Heine2012x3010.png|thumb|这是一个通过独立元素分析方法从静息状态脑功能性磁共振成像信号中分辨出10个大规模脑网络的例子。<ref name="Heine" />]]
-因为脑网络可以在不同分辨率条件下、使用不同的神经生物学特性来识别，所以没有能够适用于所有情况的通用脑网络图谱。<ref name=":7">{{cite journal|last1=Eickhoff|first1=SB|last2=Yeo|first2=BTT|last3=Genon|first3=S|title=Imaging-based parcellations of the human brain.|journal=Nature Reviews. Neuroscience|date=November 2018|volume=19|issue=11|pages=672–686|doi=10.1038/s41583-018-0071-7|pmid=30305712|s2cid=52954265|url=http://juser.fz-juelich.de/record/856633/files/Eickhoff_Yeo_Genon_NRN_MainManuscriptInclFigures.pdf}}</ref>在承认这个问题的同时，Uddin，Yeo，和Spreng在2019年提出<ref name="Uddin2019">{{cite journal|last1=Uddin|first1=LQ|last2=Yeo|first2=BTT|last3=Spreng|first3=RN|title=Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks.|journal=Brain Topography|date=November 2019|volume=32|issue=6|pages=926–942|doi=10.1007/s10548-019-00744-6|pmid=31707621|pmc=7325607}}</ref>，综合考虑来自多个研究的证据<ref name=":8">{{cite journal|last1=Doucet|first1=GE|last2=Lee|first2=WH|last3=Frangou|first3=S|title=Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases.|journal=Human Brain Mapping|date=2019-10-15|volume=40|issue=15|pages=4577–4587|doi=10.1002/hbm.24722|pmid=31322303|pmc=6771873}}</ref><ref name="Yeo" /><ref name=":9">{{cite journal|last1=Smith|first1=SM|last2=Fox|first2=PT|last3=Miller|first3=KL|last4=Glahn|first4=DC|last5=Fox|first5=PM|last6=Mackay|first6=CE|last7=Filippini|first7=N|last8=Watkins|first8=KE|last9=Toro|first9=R|last10=Laird|first10=AR|last11=Beckmann|first11=CF|title=Correspondence of the brain's functional architecture during activation and rest.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=2009-08-04|volume=106|issue=31|pages=13040–5|doi=10.1073/pnas.0905267106|pmid=19620724|pmc=2722273|bibcode=2009PNAS..10613040S|doi-access=free}}</ref>，以下六个网络应该被定义为核心网络，以促进研究人员之间的交流。
+因为脑网络可以在不同分辨率条件下、使用不同的神经生物学特性来识别，所以没有能够适用于所有情况的通用脑网络图谱。<ref name=":7">{{cite journal|last1=Eickhoff|first1=SB|last2=Yeo|first2=BTT|last3=Genon|first3=S|title=Imaging-based parcellations of the human brain.|journal=Nature Reviews. Neuroscience|date=November 2018|volume=19|issue=11|pages=672–686|doi=10.1038/s41583-018-0071-7|pmid=30305712|url=http://juser.fz-juelich.de/record/856633/files/Eickhoff_Yeo_Genon_NRN_MainManuscriptInclFigures.pdf}}</ref>在承认这个问题的同时，Uddin，Yeo，和Spreng在2019年提出<ref name="Uddin2019">{{cite journal|last1=Uddin|first1=LQ|last2=Yeo|first2=BTT|last3=Spreng|first3=RN|title=Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks.|journal=Brain Topography|date=November 2019|volume=32|issue=6|pages=926–942|doi=10.1007/s10548-019-00744-6|pmid=31707621|pmc=7325607}}</ref>，综合考虑来自多个研究的证据<ref name=":8">{{cite journal|last1=Doucet|first1=GE|last2=Lee|first2=WH|last3=Frangou|first3=S|title=Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases.|journal=Human Brain Mapping|date=2019-10-15|volume=40|issue=15|pages=4577–4587|doi=10.1002/hbm.24722|pmid=31322303|pmc=6771873}}</ref><ref name="Yeo" /><ref name=":9">{{cite journal|last1=Smith|first1=SM|last2=Fox|first2=PT|last3=Miller|first3=KL|last4=Glahn|first4=DC|last5=Fox|first5=PM|last6=Mackay|first6=CE|last7=Filippini|first7=N|last8=Watkins|first8=KE|last9=Toro|first9=R|last10=Laird|first10=AR|last11=Beckmann|first11=CF|title=Correspondence of the brain's functional architecture during activation and rest.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=2009-08-04|volume=106|issue=31|pages=13040–5|doi=10.1073/pnas.0905267106|pmid=19620724|pmc=2722273|bibcode=2009PNAS..10613040S|doi-access=free}}</ref>，以下六个网络应该被定义为核心网络，以促进研究人员之间的交流。
 ===默认模式网络（内侧额顶骨）===
-*默认模式网络在个体清醒和休息时都处于活跃状态。当个体专注于内部导向任务，比如做白日梦、展望未来、提取回忆和'''心智理论Theory of mind'''任务时，默认模式网络会被优先激活。它与专注于外部视觉信号的大脑系统成负相关。对默认模式网络的研究目前是所谓网络之中最为广泛的。<ref name="Bressler" /><ref name="Bassett" /><ref name=":10">{{Cite journal|date=2012-08-15|title=The serendipitous discovery of the brain's default network|journal=NeuroImage|language=en|volume=62|issue=2|pages=1137–1145|doi=10.1016/j.neuroimage.2011.10.035|pmid=22037421|issn=1053-8119|last1=Buckner|first1=Randy L.|s2cid=9880586}}</ref><ref name="Riedl" /><ref name="Yuan">
+*默认模式网络在个体清醒和休息时都处于活跃状态。当个体专注于内部导向任务，比如做白日梦、展望未来、提取回忆和'''心智理论Theory of mind'''任务时，默认模式网络会被优先激活。它与专注于外部视觉信号的大脑系统成负相关。对默认模式网络的研究目前是所谓网络之中最为广泛的。<ref name="Bressler" /><ref name="Bassett" /><ref name=":10">{{Cite journal|date=2012-08-15|title=The serendipitous discovery of the brain's default network|journal=NeuroImage|language=en|volume=62|issue=2|pages=1137–1145|doi=10.1016/j.neuroimage.2011.10.035|pmid=22037421|issn=1053-8119|last1=Buckner|first1=Randy L.}}</ref><ref name="Riedl" /><ref name="Yuan">
 {{cite journal|last1=Yuan|first1=Rui|last2=Di|first2=Xin|last3=Taylor|first3=Paul A.|last4=Gohel|first4=Suril|last5=Tsai|first5=Yuan-Hsiung|last6=Biswal|first6=Bharat B.|title=Functional topography of the thalamocortical system in human|journal=Brain Structure and Function|date=30 April 2015|doi=10.1007/s00429-015-1018-7|pmid=25924563|pmc=6363530|volume=221|issue=4|pages=1971–1984}}</ref><ref name="Bell">{{cite journal|last1=Bell|first1=Peter T.|last2=Shine|first2=James M.|title=Estimating Large-Scale Network Convergence in the Human Functional Connectome|journal=Brain Connectivity|date=2015-11-09|volume=5|issue=9|doi=10.1089/brain.2015.0348|pmid=26005099|pages=565–74}}</ref><ref name="Heine">{{cite journal|last1=Heine|first1=Lizette|last2=Soddu|first2=Andrea|last3=Gomez|first3=Francisco|last4=Vanhaudenhuyse|first4=Audrey|last5=Tshibanda|first5=Luaba|last6=Thonnard|first6=Marie|last7=Charland-Verville|first7=Vanessa|last8=Kirsch|first8=Murielle|last9=Laureys|first9=Steven|last10=Demertzi|first10=Athena|title=Resting state networks and consciousness. Alterations of multiple resting state network connectivity in physiological, pharmacological and pathological consciousness states.|journal=Frontiers in Psychology|date=2012|volume=3|pages=295|doi=10.3389/fpsyg.2012.00295|pmid=22969735|pmc=3427917|doi-access=free}}</ref><ref name="Yeo">{{cite journal|last1=Yeo|first1=B. T. Thomas|last2=Krienen|first2=Fenna M.|last3=Sepulcre|first3=Jorge|last4=Sabuncu|first4=Mert R.|last5=Lashkari|first5=Danial|last6=Hollinshead|first6=Marisa|last7=Roffman|first7=Joshua L.|last8=Smoller|first8=Jordan W.|last9=Zöllei|first9=Lilla|last10=Polimeni|first10=Jonathan R.|last11=Fischl|first11=Bruce|last12=Liu|first12=Hesheng|last13=Buckner|first13=Randy L.|title=The organization of the human cerebral cortex estimated by intrinsic functional connectivity|journal=Journal of Neurophysiology|date=2011-09-01|volume=106|issue=3|pages=1125–1165|doi=10.1152/jn.00338.2011|pmid=21653723|pmc=3174820|bibcode=2011NatSD...2E0031H }}</ref><ref name="Shafiei">{{cite journal|last1=Shafiei|first1=Golia|last2=Zeighami|first2=Yashar|last3=Clark|first3=Crystal A.|last4=Coull|first4=Jennifer T.|last5=Nagano-Saito|first5=Atsuko|last6=Leyton|first6=Marco|last7=Dagher|first7=Alain|last8=Mišić|first8=Bratislav|title=Dopamine Signaling Modulates the Stability and Integration of Intrinsic Brain Networks|journal=Cerebral Cortex|date=2018-10-01|volume=29|issue=1|pages=397–409|doi=10.1093/cercor/bhy264|pmid=30357316|pmc=6294404 }}</ref><ref name="Bailey">{{cite journal|last1=Bailey|first1=Stephen K.|last2=Aboud|first2=Katherine S.|last3=Nguyen|first3=Tin Q.|last4=Cutting|first4=Laurie E.|title=Applying a network framework to the neurobiology of reading and dyslexia|journal=Journal of Neurodevelopmental Disorders|date=13 December 2018|volume=10|issue=1|page=37|doi=10.1186/s11689-018-9251-z|pmid=30541433|pmc=6291929 }}</ref>

@@ 第24行： / 第24行： @@
 [[File:Heine2012x3010.png|thumb|An example that identified 10 large-scale brain networks from [[resting state fMRI]] activity through [[independent component analysis]].<ref name="Heine" />|链接=Special:FilePath/Heine2012x3010.png]]
 Because brain networks can be identified at various different resolutions and with various different neurobiological properties, there is no such thing as a universal atlas of brain networks that fits all circumstances.<ref name=":7">{{cite journal|last1=Eickhoff|first1=SB|last2=Yeo|first2=BTT|last3=Genon|first3=S|title=Imaging-based parcellations of the human brain.|journal=Nature Reviews. Neuroscience|date=November 2018|volume=19|issue=11|pages=672–686|doi=10.1038/s41583-018-0071-7|pmid=30305712|s2cid=52954265|url=http://juser.fz-juelich.de/record/856633/files/Eickhoff_Yeo_Genon_NRN_MainManuscriptInclFigures.pdf}}</ref> While acknowledging this problem, Uddin, Yeo, and Spreng proposed in 2019<ref name="Uddin2019">{{cite journal|last1=Uddin|first1=LQ|last2=Yeo|first2=BTT|last3=Spreng|first3=RN|title=Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks.|journal=Brain Topography|date=November 2019|volume=32|issue=6|pages=926–942|doi=10.1007/s10548-019-00744-6|pmid=31707621|pmc=7325607}}</ref> that the following six networks should be defined as core networks based on converging evidences from multiple studies<ref name=":8">{{cite journal|last1=Doucet|first1=GE|last2=Lee|first2=WH|last3=Frangou|first3=S|title=Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases.|journal=Human Brain Mapping|date=2019-10-15|volume=40|issue=15|pages=4577–4587|doi=10.1002/hbm.24722|pmid=31322303|pmc=6771873}}</ref><ref name="Yeo" /><ref name=":9">{{cite journal|last1=Smith|first1=SM|last2=Fox|first2=PT|last3=Miller|first3=KL|last4=Glahn|first4=DC|last5=Fox|first5=PM|last6=Mackay|first6=CE|last7=Filippini|first7=N|last8=Watkins|first8=KE|last9=Toro|first9=R|last10=Laird|first10=AR|last11=Beckmann|first11=CF|title=Correspondence of the brain's functional architecture during activation and rest.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=2009-08-04|volume=106|issue=31|pages=13040–5|doi=10.1073/pnas.0905267106|pmid=19620724|pmc=2722273|bibcode=2009PNAS..10613040S|doi-access=free}}</ref> to facilitate communication between researchers.
 ==核心网络==
@@ 第36行： / 第35行： @@
 *The default mode network is active when an individual is awake and at rest. It preferentially activates when individuals focus on internally-oriented tasks such as daydreaming, envisioning the future, retrieving memories, and [[theory of mind]]. It is negatively correlated with brain systems that focus on external visual signals. It is the most widely researched network.<ref name="Bressler" /><ref name="Bassett" /><ref name=":10">{{Cite journal|date=2012-08-15|title=The serendipitous discovery of the brain's default network|journal=NeuroImage|language=en|volume=62|issue=2|pages=1137–1145|doi=10.1016/j.neuroimage.2011.10.035|pmid=22037421|issn=1053-8119|last1=Buckner|first1=Randy L.|s2cid=9880586}}</ref><ref name="Riedl" /><ref name="Yuan">
 {{cite journal|last1=Yuan|first1=Rui|last2=Di|first2=Xin|last3=Taylor|first3=Paul A.|last4=Gohel|first4=Suril|last5=Tsai|first5=Yuan-Hsiung|last6=Biswal|first6=Bharat B.|title=Functional topography of the thalamocortical system in human|journal=Brain Structure and Function|date=30 April 2015|doi=10.1007/s00429-015-1018-7|pmid=25924563|pmc=6363530|volume=221|issue=4|pages=1971–1984}}</ref><ref name="Bell">{{cite journal|last1=Bell|first1=Peter T.|last2=Shine|first2=James M.|title=Estimating Large-Scale Network Convergence in the Human Functional Connectome|journal=Brain Connectivity|date=2015-11-09|volume=5|issue=9|doi=10.1089/brain.2015.0348|pmid=26005099|pages=565–74}}</ref><ref name="Heine">{{cite journal|last1=Heine|first1=Lizette|last2=Soddu|first2=Andrea|last3=Gomez|first3=Francisco|last4=Vanhaudenhuyse|first4=Audrey|last5=Tshibanda|first5=Luaba|last6=Thonnard|first6=Marie|last7=Charland-Verville|first7=Vanessa|last8=Kirsch|first8=Murielle|last9=Laureys|first9=Steven|last10=Demertzi|first10=Athena|title=Resting state networks and consciousness. Alterations of multiple resting state network connectivity in physiological, pharmacological and pathological consciousness states.|journal=Frontiers in Psychology|date=2012|volume=3|pages=295|doi=10.3389/fpsyg.2012.00295|pmid=22969735|pmc=3427917|doi-access=free}}</ref><ref name="Yeo">{{cite journal|last1=Yeo|first1=B. T. Thomas|last2=Krienen|first2=Fenna M.|last3=Sepulcre|first3=Jorge|last4=Sabuncu|first4=Mert R.|last5=Lashkari|first5=Danial|last6=Hollinshead|first6=Marisa|last7=Roffman|first7=Joshua L.|last8=Smoller|first8=Jordan W.|last9=Zöllei|first9=Lilla|last10=Polimeni|first10=Jonathan R.|last11=Fischl|first11=Bruce|last12=Liu|first12=Hesheng|last13=Buckner|first13=Randy L.|title=The organization of the human cerebral cortex estimated by intrinsic functional connectivity|journal=Journal of Neurophysiology|date=2011-09-01|volume=106|issue=3|pages=1125–1165|doi=10.1152/jn.00338.2011|pmid=21653723|pmc=3174820|bibcode=2011NatSD...2E0031H }}</ref><ref name="Shafiei">{{cite journal|last1=Shafiei|first1=Golia|last2=Zeighami|first2=Yashar|last3=Clark|first3=Crystal A.|last4=Coull|first4=Jennifer T.|last5=Nagano-Saito|first5=Atsuko|last6=Leyton|first6=Marco|last7=Dagher|first7=Alain|last8=Mišić|first8=Bratislav|title=Dopamine Signaling Modulates the Stability and Integration of Intrinsic Brain Networks|journal=Cerebral Cortex|date=2018-10-01|volume=29|issue=1|pages=397–409|doi=10.1093/cercor/bhy264|pmid=30357316|pmc=6294404 }}</ref><ref name="Bailey">{{cite journal|last1=Bailey|first1=Stephen K.|last2=Aboud|first2=Katherine S.|last3=Nguyen|first3=Tin Q.|last4=Cutting|first4=Laurie E.|title=Applying a network framework to the neurobiology of reading and dyslexia|journal=Journal of Neurodevelopmental Disorders|date=13 December 2018|volume=10|issue=1|page=37|doi=10.1186/s11689-018-9251-z|pmid=30541433|pmc=6291929 }}</ref>
 ===默认模式网络（内侧额顶骨）===
@@ 第54行： / 第52行： @@
 {{Main|Dorsal attention network}}
 *This network is involved in the voluntary, top-down deployment of attention.<ref name="Riedl" /><ref name="Yuan" /><ref name="Bell" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Vossel">{{cite journal|last1=Vossel|first1=Simone|last2=Geng|first2=Joy J.|last3=Fink|first3=Gereon R.|title=Dorsal and Ventral Attention Systems: Distinct Neural Circuits but Collaborative Roles|journal=The Neuroscientist|date=2014|volume=20|issue=2|pages=150–159|doi=10.1177/1073858413494269|pmid=23835449|pmc=4107817}}</ref><ref name="Hutton">{{cite journal|last1=Hutton|first1=John S.|last2=Dudley|first2=Jonathan|last3=Horowitz-Kraus|first3=Tzipi|last4=DeWitt|first4=Tom|last5=Holland|first5=Scott K.|title=Functional Connectivity of Attention, Visual, and Language Networks During Audio, Illustrated, and Animated Stories in Preschool-Age Children|journal=Brain Connectivity|date=1 September 2019|volume=9|issue=7|pages=580–592|doi=10.1089/brain.2019.0679|pmid=31144523|pmc=6775495|ref=Hutton}}</ref> Within the dorsal attention network, the intraparietal sulcus and frontal eye fields influence the visual areas of the brain. These influencing factors allow for the orientation of attention.<ref name=":13">{{Cite journal|last1=Fox|first1=Michael D.|last2=Corbetta|first2=Maurizio|last3=Snyder|first3=Abraham Z.|last4=Vincent|first4=Justin L.|last5=Raichle|first5=Marcus E.|date=2006-06-27|title=Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems|journal=Proceedings of the National Academy of Sciences|language=en|volume=103|issue=26|pages=10046–10051|doi=10.1073/pnas.0604187103|issn=0027-8424|pmid=16788060|pmc=1480402|bibcode=2006PNAS..10310046F|doi-access=free}}</ref><ref name="Vossel" /><ref name="Bailey" />
 ===注意网络（背侧额顶骨）===
@@ 第64行： / 第61行： @@
 *Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.<ref name="Uddin2019" />
 ===控制网络（侧额顶骨）===
@@ 第106行： / 第102行： @@
 *外侧视觉网络<ref name="Yuan" /><ref name="Bell" /><ref name="Heine" />
 *颞骨网络<ref name="Yeo" /><ref name="Shafiei" />
-*颞视知觉/图像网络<ref name="Hutton" />
+*视知觉/图像网络<ref name="Hutton" />
 ==See also==

@@ 第28行： / 第28行： @@
 =<nowiki>= = 核心网络 = =</nowiki>=
 【图1：An example that identified 10 large-scale brain networks from resting state fMRI activity through independent component analysis.<ref name="Heine" />这是一个通过独立元素分析方法从静息状态脑功能性磁共振成像信号中分辨出10个大规模脑网络的例子。<ref name="Heine" />】
@@ 第40行： / 第41行： @@
 =<nowiki>= = 默认模式网络（内侧额顶叶） = =</nowiki>=
 *默认模式网络在个体清醒和休息时都处于活跃状态。当个体专注于内部导向任务，比如做白日梦、展望未来、提取回忆和'''<font color="#ff8000">心智理论Theory of mind</font>'''任务时，默认模式网络会被优先激活。它与专注于外部视觉信号的大脑系统成负相关。对默认模式网络的研究目前是所谓网络之中最为广泛的。<ref name="Bressler" /><ref name="Bassett" /><ref name=":10" /><ref name="Riedl" /><ref name="Yuan" /><ref name="Bell" /><ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Bailey" />
-===Salience (Midcingulo-Insular)===
+=== Salience (Midcingulo-Insular)===
 {{Main|Salience network}}
 *The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region.<ref name=":11">{{Cite journal|last1=Steimke|first1=Rosa|last2=Nomi|first2=Jason S.|last3=Calhoun|first3=Vince D.|last4=Stelzel|first4=Christine|last5=Paschke|first5=Lena M.|last6=Gaschler|first6=Robert|last7=Goschke|first7=Thomas|last8=Walter|first8=Henrik|last9=Uddin|first9=Lucina Q.|date=2017-12-01|title=Salience network dynamics underlying successful resistance of temptation|journal=Social Cognitive and Affective Neuroscience|language=en|volume=12|issue=12|pages=1928–1939|doi=10.1093/scan/nsx123|pmid=29048582|pmc=5716209|issn=1749-5016|doi-access=free}}</ref><ref name=":0">{{Citation|last=Menon|first=V.|title=Brain Mapping|chapter=Salience Network|date=2015-01-01|chapter-url=http://www.sciencedirect.com/science/article/pii/B978012397025100052X|pages=597–611|editor-last=Toga|editor-first=Arthur W.|publisher=Academic Press|isbn=978-0-12-397316-0|access-date=2019-12-08|doi=10.1016/B978-0-12-397025-1.00052-X}}</ref> It plays the key role of monitoring the [[Salience (neuroscience)|salience]] of external inputs and internal brain events.<ref name="Riedl" /><ref name="Bressler" /><ref name="Bassett" /><ref name="Yuan" /><ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /> Specifically, it aids in directing attention by identifying important biological and cognitive events.<ref name=":0" /><ref name="Bailey" />
@@ 第49行： / 第51行： @@
 =<nowiki>= = 突显网络（扣带回-岛叶）= =</nowiki>=
 *突显网络由'''<font color="#32CD32"> 前(双)岛、前扣带回皮层和三个皮层下结构（腹侧纹状体、黑质/腹侧被盖区）</font>'''组成，<ref name=":11" /><ref name=":0" />它在监测外部输入和内部脑活动的'''<font color="#ff8000">凸显程度Salience</font>'''中发挥着关键作用。<ref name="Riedl" /><ref name="Bressler" /><ref name="Bassett" /><ref name="Yuan" /><ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" />具体来说，突显网络通过识别重要的生理、认知活动来帮助引导注意力。<ref name=":0" /><ref name="Bailey" />
@@ 第58行： / 第61行： @@
 =<nowiki>= = 注意网络(背侧额顶骨) = =</nowiki>=
 *这个网络参与了自发的、自上而下的注意力分配。<ref name="Riedl" /><ref name="Yuan" /><ref name="Bell" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Vossel" /><ref name="Hutton" />在背侧注意网络中，顶内沟和额眼影响着大脑的视觉区域。这些影响因素决定了注意力的方向。<ref name=":13" /><ref name="Vossel" /><ref name="Bailey" />
@@ 第68行： / 第72行： @@
 =<nowiki>= = 控制网络(侧额顶骨) = =</nowiki>=
 *这个网络参与了认知控制的启动与调节，它包括了大脑的18个亚区。<ref name=":14" />额顶网络与其他网络的参与程度和流体智力之间存在着有很强的相关性。<ref name=":15" />
@@ 第76行： / 第81行： @@
 *This network processes somatosensory information and coordinates motion.<ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Bassett" /><ref name="Yuan" /> The [[auditory cortex]] may be included.<ref name="Uddin2019" /><ref name="Yeo" />
 =<nowiki>= = 感觉运动网络(中央区域) = =</nowiki>=
 *这个网络参与了躯体感觉信息的加工和运动的协调。<ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Bassett" /><ref name="Yuan" />'''<font color="#ff8000">听觉皮层Auditory cortex</font>'''可能也包括在内。<ref name="Uddin2019" /><ref name="Yeo" />
@@ 第83行： / 第89行： @@
 *This network handles visual information processing.<ref name="Yang">{{cite journal|last1=Yang|first1=Yan-li|last2=Deng|first2=Hong-xia|last3=Xing|first3=Gui-yang|last4=Xia|first4=Xiao-luan|last5=Li|first5=Hai-fang|title=Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state|journal=Neural Regeneration Research|date=2015|volume=10|issue=2|pages=298–307|doi=10.4103/1673-5374.152386|pmid=25883631|pmc=4392680 }}</ref>
 =<nowiki>= = 视觉网络(枕部) = =</nowiki>=
 *这个网络处理视觉信息。<ref name="Yang" />
@@ 第88行： / 第95行： @@
 ==Other networks==
 Different methods and data have identified several other brain networks, many of which greatly overlap or are subsets of more well-characterized core networks.<ref name="Uddin2019" />
-* Limbic<ref name="Bassett" /><ref name="Yeo" /><ref name="Bailey" />
+*Limbic<ref name="Bassett" /><ref name="Yeo" /><ref name="Bailey" />
 *Auditory<ref name="Yuan" /><ref name="Heine" />
 *Right/left executive<ref name="Yuan" /><ref name="Heine" />
@@ 第98行： / 第105行： @@
 *Visual perception/imagery<ref name="Hutton" />
 =<nowiki>= = 其他网络 = =</nowiki>=
 不同的方法和数据已经能够确定上述核心网络以外的几个大脑网络，其中许多网络之间存在极大的重叠，部分网络实际上是核心网络更具特点的子集。<ref name="Uddin2019" />
@@ 第103行： / 第111行： @@
 *听觉网络<ref name="Yuan" /><ref name="Heine" />
 *右/左执行网络<ref name="Yuan" /><ref name="Heine" />
-* 小脑网络<ref name="Bell" /><ref name="Heine" />
+*小脑网络<ref name="Bell" /><ref name="Heine" />
 *空间注意网络<ref name="Riedl" /><ref name="Bressler" />
 *语言网络<ref name="Bressler" /><ref name="Hutton" />
@@ 第114行： / 第122行： @@
 *[[Neural network]]
 =<nowiki>= = 相关词条 = =</nowiki>=
 *[[复杂网络]]

@@ 第46行： / 第46行： @@
-=<nowiki>= = 默认模式网络（'''<font color="#32CD32"> 内侧额顶叶</font>''' ） = =</nowiki>=
+=<nowiki>= = 默认模式网络（内侧额顶叶） = =</nowiki>=
 *默认模式网络在个体清醒和休息时都处于活跃状态。当个体专注于内部导向任务，比如做白日梦、展望未来、提取回忆和'''<font color="#ff8000">心智理论Theory of mind</font>'''任务时，默认模式网络会被优先激活。它与专注于外部视觉信号的大脑系统成负相关。对默认模式网络的研究目前是所谓网络之中最为广泛的。
-=== Salience (Midcingulo-Insular)===
+===Salience (Midcingulo-Insular)===
 {{Main|Salience network}}
-* The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region.<ref>{{Cite journal|last1=Steimke|first1=Rosa|last2=Nomi|first2=Jason S.|last3=Calhoun|first3=Vince D.|last4=Stelzel|first4=Christine|last5=Paschke|first5=Lena M.|last6=Gaschler|first6=Robert|last7=Goschke|first7=Thomas|last8=Walter|first8=Henrik|last9=Uddin|first9=Lucina Q.|date=2017-12-01|title=Salience network dynamics underlying successful resistance of temptation|journal=Social Cognitive and Affective Neuroscience|language=en|volume=12|issue=12|pages=1928–1939|doi=10.1093/scan/nsx123|pmid=29048582|pmc=5716209|issn=1749-5016|doi-access=free}}</ref><ref name=":0">{{Citation|last=Menon|first=V.|title=Brain Mapping|chapter=Salience Network|date=2015-01-01|chapter-url=http://www.sciencedirect.com/science/article/pii/B978012397025100052X|pages=597–611|editor-last=Toga|editor-first=Arthur W.|publisher=Academic Press|isbn=978-0-12-397316-0|access-date=2019-12-08|doi=10.1016/B978-0-12-397025-1.00052-X}}</ref> It plays the key role of monitoring the [[Salience (neuroscience)|salience]] of external inputs and internal brain events.<ref name="Riedl" /><ref name="Bressler" /><ref name="Bassett" /><ref name="Yuan" /><ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /> Specifically, it aids in directing attention by identifying important biological and cognitive events.<ref name=":0" /><ref name="Bailey" />
+*The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region.<ref>{{Cite journal|last1=Steimke|first1=Rosa|last2=Nomi|first2=Jason S.|last3=Calhoun|first3=Vince D.|last4=Stelzel|first4=Christine|last5=Paschke|first5=Lena M.|last6=Gaschler|first6=Robert|last7=Goschke|first7=Thomas|last8=Walter|first8=Henrik|last9=Uddin|first9=Lucina Q.|date=2017-12-01|title=Salience network dynamics underlying successful resistance of temptation|journal=Social Cognitive and Affective Neuroscience|language=en|volume=12|issue=12|pages=1928–1939|doi=10.1093/scan/nsx123|pmid=29048582|pmc=5716209|issn=1749-5016|doi-access=free}}</ref><ref name=":0">{{Citation|last=Menon|first=V.|title=Brain Mapping|chapter=Salience Network|date=2015-01-01|chapter-url=http://www.sciencedirect.com/science/article/pii/B978012397025100052X|pages=597–611|editor-last=Toga|editor-first=Arthur W.|publisher=Academic Press|isbn=978-0-12-397316-0|access-date=2019-12-08|doi=10.1016/B978-0-12-397025-1.00052-X}}</ref> It plays the key role of monitoring the [[Salience (neuroscience)|salience]] of external inputs and internal brain events.<ref name="Riedl" /><ref name="Bressler" /><ref name="Bassett" /><ref name="Yuan" /><ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /> Specifically, it aids in directing attention by identifying important biological and cognitive events.<ref name=":0" /><ref name="Bailey" />
 *This network includes the ventral attention network, which primarily includes the [[temporoparietal junction]] and the ventral [[frontal cortex]] of the right hemisphere.<ref name="Uddin2019" /><ref name="Vossel" /> These areas respond when behaviorally relevant stimuli occur unexpectedly.<ref name="Vossel" /> The ventral attention network is inhibited during focused attention in which top-down processing is being used, such as when visually searching for something. This response may prevent goal-driven attention from being distracted by non-relevant stimuli. It becomes active again when the target or relevant information about the target is found.<ref name="Vossel" /><ref>{{Cite journal|last1=Shulman|first1=Gordon L.|last2=McAvoy|first2=Mark P.|last3=Cowan|first3=Melanie C.|last4=Astafiev|first4=Serguei V.|last5=Tansy|first5=Aaron P.|last6=d'Avossa|first6=Giovanni|last7=Corbetta|first7=Maurizio|date=2003-11-01|title=Quantitative Analysis of Attention and Detection Signals During Visual Search|journal=Journal of Neurophysiology|volume=90|issue=5|pages=3384–3397|doi=10.1152/jn.00343.2003|pmid=12917383|issn=0022-3077}}</ref>
-* The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region. It plays the key role of monitoring the salience of external inputs and internal brain events. Specifically, it aids in directing attention by identifying important biological and cognitive events.
+*The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region. It plays the key role of monitoring the salience of external inputs and internal brain events. Specifically, it aids in directing attention by identifying important biological and cognitive events.
-* This network includes the ventral attention network, which primarily includes the temporoparietal junction and the ventral frontal cortex of the right hemisphere. These areas respond when behaviorally relevant stimuli occur unexpectedly. The ventral attention network is inhibited during focused attention in which top-down processing is being used, such as when visually searching for something. This response may prevent goal-driven attention from being distracted by non-relevant stimuli. It becomes active again when the target or relevant information about the target is found.
+*This network includes the ventral attention network, which primarily includes the temporoparietal junction and the ventral frontal cortex of the right hemisphere. These areas respond when behaviorally relevant stimuli occur unexpectedly. The ventral attention network is inhibited during focused attention in which top-down processing is being used, such as when visually searching for something. This response may prevent goal-driven attention from being distracted by non-relevant stimuli. It becomes active again when the target or relevant information about the target is found.
-=<nowiki>= = 突显网络（'''<font color="#32CD32"> 扣带回-岛叶</font>'''）= =</nowiki>=
+=<nowiki>= = 突显网络（扣带回-岛叶）= =</nowiki>=
 *突显网络由'''<font color="#32CD32"> 前(双)岛、前扣带回皮层和三个皮层下结构（腹侧纹状体、黑质/腹侧被盖区）</font>'''组成，它在监测外部输入和内部脑活动的'''<font color="#ff8000">凸显程度Salience</font>'''中发挥着关键作用。具体来说，突显网络通过识别重要的生理、认知活动来帮助引导注意力。
 *突显网络包括主要由右半球的'''<font color="#ff8000">颞顶联合区Temporoparietal junction</font>'''和腹侧'''<font color="#ff8000">额叶Frontal cortex</font>'''皮层组成的腹侧注意网络。当行为相关的刺激意外发生时，这些区域会对此做出反应。在自上而下加工注意焦点的过程中（例如使用视觉搜索某件物品时），腹侧注意网络会受到抑制。这种抑制反应可以防止目标驱动的注意力被不相关的刺激分散。当找到目标或相关信息时，突显网络会被再次激活。
@@ 第74行： / 第74行： @@
 ===Control (Lateral frontoparietal)===
 {{Main|Frontoparietal network}}
-* This network initiates and modulates cognitive control and comprises 18 sub-regions of the brain.<ref>{{Cite journal|last1=Scolari|first1=Miranda|last2=Seidl-Rathkopf|first2=Katharina N|last3=Kastner|first3=Sabine|date=2015-02-01|title=Functions of the human frontoparietal attention network: Evidence from neuroimaging|journal=Current Opinion in Behavioral Sciences|series=Cognitive control|volume=1|pages=32–39|doi=10.1016/j.cobeha.2014.08.003|issn=2352-1546|pmid=27398396|pmc=4936532}}</ref> There is a strong correlation between fluid intelligence and the involvement of the fronto-parietal network with other networks.<ref>{{Cite journal|last1=Marek|first1=Scott|last2=Dosenbach|first2=Nico U. F.|date=June 2018|title=The frontoparietal network: function, electrophysiology, and importance of individual precision mapping|journal=Dialogues in Clinical Neuroscience|volume=20|issue=2|pages=133–140|doi=10.31887/DCNS.2018.20.2/smarek|issn=1294-8322|pmc=6136121|pmid=30250390}}</ref>
+*This network initiates and modulates cognitive control and comprises 18 sub-regions of the brain.<ref>{{Cite journal|last1=Scolari|first1=Miranda|last2=Seidl-Rathkopf|first2=Katharina N|last3=Kastner|first3=Sabine|date=2015-02-01|title=Functions of the human frontoparietal attention network: Evidence from neuroimaging|journal=Current Opinion in Behavioral Sciences|series=Cognitive control|volume=1|pages=32–39|doi=10.1016/j.cobeha.2014.08.003|issn=2352-1546|pmid=27398396|pmc=4936532}}</ref> There is a strong correlation between fluid intelligence and the involvement of the fronto-parietal network with other networks.<ref>{{Cite journal|last1=Marek|first1=Scott|last2=Dosenbach|first2=Nico U. F.|date=June 2018|title=The frontoparietal network: function, electrophysiology, and importance of individual precision mapping|journal=Dialogues in Clinical Neuroscience|volume=20|issue=2|pages=133–140|doi=10.31887/DCNS.2018.20.2/smarek|issn=1294-8322|pmc=6136121|pmid=30250390}}</ref>
@@ 第82行： / 第84行： @@
 *这个网络参与了认知控制的启动与调节，它包括了大脑的18个亚区。额顶网络与其他网络的参与程度和流体智力之间存在着有很强的相关性。
 *Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.
 *在其它版本中，这种网络也被称为中央执行(或执行控制)网络和认知控制网络。
@@ 第92行： / 第92行： @@
 {{Main|Sensorimotor network}}
 *This network processes somatosensory information and coordinates motion.<ref name="Heine" /><ref name="Yeo" /><ref name="Shafiei" /><ref name="Bassett" /><ref name="Yuan" /> The [[auditory cortex]] may be included.<ref name="Uddin2019" /><ref name="Yeo" />
 *This network processes somatosensory information and coordinates motion. The auditory cortex may be included.
-===Sensorimotor or Somatomotor (Pericentral)===
+=<nowiki>= = 感觉运动网络(中央区域) = =</nowiki>=
+* 这个网络参与了躯体感觉信息的加工和运动的协调。听觉皮层可能也包括在内。
-===Visual (Occipital)===
+===Visual (Occipital) ===
 {{See|Visual cortex}}
-* This network handles visual information processing.<ref name="Yang">{{cite journal|last1=Yang|first1=Yan-li|last2=Deng|first2=Hong-xia|last3=Xing|first3=Gui-yang|last4=Xia|first4=Xiao-luan|last5=Li|first5=Hai-fang|title=Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state|journal=Neural Regeneration Research|date=2015|volume=10|issue=2|pages=298–307|doi=10.4103/1673-5374.152386|pmid=25883631|pmc=4392680 }}</ref>
+*This network handles visual information processing.<ref name="Yang">{{cite journal|last1=Yang|first1=Yan-li|last2=Deng|first2=Hong-xia|last3=Xing|first3=Gui-yang|last4=Xia|first4=Xiao-luan|last5=Li|first5=Hai-fang|title=Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state|journal=Neural Regeneration Research|date=2015|volume=10|issue=2|pages=298–307|doi=10.4103/1673-5374.152386|pmid=25883631|pmc=4392680 }}</ref>
-* This network handles visual information processing.
+*This network handles visual information processing.
-= = = = = = = = = = = = = 这个网络处理视觉信息。
+=<nowiki>= = 视觉网络(枕部) = =</nowiki>=
 == Other networks==
@@ 第118行： / 第116行： @@
 *Spatial attention<ref name="Riedl" /><ref name="Bressler" />
 *Language<ref name="Bressler" /><ref name="Hutton" />
-*Lateral visual<ref name="Yuan" /><ref name="Bell" /><ref name="Heine" />
+* Lateral visual<ref name="Yuan" /><ref name="Bell" /><ref name="Heine" />
 *Temporal<ref name="Yeo" /><ref name="Shafiei" />
 *Visual perception/imagery<ref name="Hutton" />