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第29行： − + + − 因为大脑网络可以用不同的分辨率和不同的神经生物学特性来识别，所以没有适合所有情况的通用大脑网络图谱。在承认这个问题的同时，Uddin，Yeo，和 Spreng 在2019年提出，以下六个网络应该被定义为核心网络，基于来自多个研究的聚合证据，以促进研究人员之间的交流。+ 第42行：
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无编辑摘要
== Core networks==
== Core networks==
[[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]]
[[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>{{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>{{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>{{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.
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.
【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" />】
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. While acknowledging this problem, Uddin, Yeo, and Spreng proposed in 2019 that the following six networks should be defined as core networks based on converging evidences from multiple studies to facilitate communication between researchers.
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. While acknowledging this problem, Uddin, Yeo, and Spreng proposed in 2019 that the following six networks should be defined as core networks based on converging evidences from multiple studies to facilitate communication between researchers.
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" />在承认这个问题的同时，Uddin，Yeo，和Spreng在2019年提出<ref name="Uddin2019" />，综合考虑来自多个研究的证据<ref name=":8" /><ref name="Yeo" /><ref name=":9" />，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。
===Default Mode (Medial frontoparietal)===
===Default Mode (Medial frontoparietal)===
*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.
* 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.
*这个网络包括腹侧注意网络，主要包括右半球的颞顶联合区和腹侧额叶皮层。当行为相关的刺激意外发生时，这些区域会做出反应。腹侧注意网络在使用自上而下加工的集中注意过程中被抑制，例如在视觉搜索某物时。这种反应可以防止目标驱动的注意力被非相关的刺激分散。当找到目标或关于目标的相关信息时，它再次激活。
*这个网络包括腹侧注意网络，主要包括右半球的颞顶联合区和腹侧额叶皮层。当行为相关的刺激意外发生时，这些区域会做出反应。腹侧注意网络在使用自上而下加工的集中注意过程中被抑制，例如在视觉搜索某物时。这种反应可以防止目标驱动的注意力被非相关的刺激分散。当找到目标或关于目标的相关信息时，它再次激活。
===Attention (Dorsal frontoparietal) ===
===Attention (Dorsal frontoparietal)===
{{Main|Dorsal attention network}}
{{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>{{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" />
*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>{{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" />
*Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.<ref name="Uddin2019" />
*Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.<ref name="Uddin2019" />
* Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.
*Versions of this network have also been called the central executive (or executive control) network and the cognitive control network.
===Sensorimotor or Somatomotor (Pericentral)===
===Sensorimotor or Somatomotor (Pericentral)===
{{Main|Sensorimotor network}}
{{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.<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" />
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* 复杂网络
*复杂网络
*
*
*神经网络
*神经网络