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大规模脑网络 (查看源代码)

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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>

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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}}</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>

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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~~|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>'''。

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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>'''。

==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" />]]

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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。

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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）===

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*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">

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*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>

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