Home > Workflow collections > Publication Charges > A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas > print

001     851363
005     20240313103127.0
024 7 _ |a 10.1371/journal.pcbi.1006359
|2 doi
024 7 _ |a 1553-734X
|2 ISSN
024 7 _ |a 1553-7358
|2 ISSN
024 7 _ |a 2128/20109
|2 Handle
024 7 _ |a pmid:30335761
|2 pmid
024 7 _ |a WOS:000450712400004
|2 WOS
024 7 _ |a altmetric:4825248
|2 altmetric
037 _ _ |a FZJ-2018-05048
082 _ _ |a 570
100 1 _ |a Schmidt, Maximilian
|0 P:(DE-Juel1)145897
|b 0
245 _ _ |a A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas
260 _ _ |a San Francisco, Calif.
|c 2018
|b Public Library of Science
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1542788979_6274
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe the first full-density multi-area spiking network model of cortex, using macaque visual cortex as a test system. The model represents each area by a microcircuit with area-specific architecture and features layer- and population-resolved connectivity between areas. Simulations reveal a structured asynchronous irregular ground state. In a metastable regime, the network reproduces spiking statistics from electrophysiological recordings and cortico-cortical interaction patterns in fMRI functional connectivity under resting-state conditions. Stable inter-area propagation is supported by cortico-cortical synapses that are moderately strong onto excitatory neurons and stronger onto inhibitory neurons. Causal interactions depend on both cortical structure and the dynamical state of populations. Activity propagates mainly in the feedback direction, similar to experimental results associated with visual imagery and sleep. The model unifies local and large-scale accounts of cortex, and clarifies how the detailed connectivity of cortex shapes its dynamics on multiple scales. Based on our simulations, we hypothesize that in the spontaneous condition the brain operates in a metastable regime where cortico-cortical projections target excitatory and inhibitory populations in a balanced manner that produces substantial inter-area interactions while maintaining global stability.
536 _ _ |a 571 - Connectivity and Activity (POF3-571)
|0 G:(DE-HGF)POF3-571
|c POF3-571
|x 0
|f POF III
536 _ _ |a 574 - Theory, modelling and simulation (POF3-574)
|0 G:(DE-HGF)POF3-574
|c POF3-574
|x 1
|f POF III
536 _ _ |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|x 2
|f H2020-SGA-FETFLAG-HBP-2017
536 _ _ |a HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)
|0 G:(EU-Grant)720270
|c 720270
|x 3
|f H2020-Adhoc-2014-20
536 _ _ |a HBP - The Human Brain Project (604102)
|0 G:(EU-Grant)604102
|c 604102
|x 4
|f FP7-ICT-2013-FET-F
536 _ _ |a SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)
|0 G:(DE-Juel1)HGF-SMHB-2013-2017
|c HGF-SMHB-2013-2017
|x 5
|f SMHB
536 _ _ |a Brain-Scale Simulations (jinb33_20121101)
|0 G:(DE-Juel1)jinb33_20121101
|c jinb33_20121101
|x 6
|f Brain-Scale Simulations
536 _ _ |a SPP 2041 347572269 - Integration von Multiskalen-Konnektivität und Gehirnarchitektur in einem supercomputergestützten Modell der menschlichen Großhirnrinde (347572269)
|0 G:(GEPRIS)347572269
|c 347572269
|x 7
536 _ _ |a BRAINSCALES - Brain-inspired multiscale computation in neuromorphic hybrid systems (269921)
|0 G:(EU-Grant)269921
|c 269921
|x 8
|f FP7-ICT-2009-6
536 _ _ |a HBP - Human Brain Project (284941)
|0 G:(EU-Grant)284941
|c 284941
|x 9
|f FP7-ICT-2011-FET-F
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Bakker, Rembrandt
|0 P:(DE-Juel1)145578
|b 1
700 1 _ |a Shen, Kelly
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Bezgin, Gleb
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Diesmann, Markus
|0 P:(DE-Juel1)144174
|b 4
700 1 _ |a van Albada, Sacha Jennifer
|0 P:(DE-Juel1)138512
|b 5
|e Corresponding author
773 _ _ |a 10.1371/journal.pcbi.1006359
|g Vol. 14, no. 10, p. e1006359 -
|0 PERI:(DE-600)2193340-6
|n 10
|p e1006359 -
|t PLoS Computational Biology
|v 14
|y 2018
|x 1553-734X
856 4 _ |u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.pdf
856 4 _ |x icon
|u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.gif?subformat=icon
856 4 _ |x icon-1440
|u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.jpg?subformat=icon-1440
856 4 _ |x icon-180
|u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.jpg?subformat=icon-180
856 4 _ |x icon-640
|u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.jpg?subformat=icon-640
856 4 _ |x pdfa
|u https://juser.fz-juelich.de/record/851363/files/InvoicePAB225705-R50002-1.pdf?subformat=pdfa
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/851363/files/journal.pcbi.1006359.pdf
856 4 _ |y OpenAccess
|x pdfa
|u https://juser.fz-juelich.de/record/851363/files/journal.pcbi.1006359.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:851363
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p ec_fundedresources
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)145578
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)144174
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|6 P:(DE-Juel1)138512
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-571
|2 G:(DE-HGF)POF3-500
|v Connectivity and Activity
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-574
|2 G:(DE-HGF)POF3-500
|v Theory, modelling and simulation
|x 1
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2018
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b PLOS COMPUT BIOL : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)INM-6-20090406
|k INM-6
|l Computational and Systems Neuroscience
|x 0
920 1 _ |0 I:(DE-Juel1)INM-10-20170113
|k INM-10
|l Jara-Institut Brain structure-function relationships
|x 1
920 1 _ |0 I:(DE-Juel1)IAS-6-20130828
|k IAS-6
|l Theoretical Neuroscience
|x 2
980 1 _ |a APC
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-6-20090406
980 _ _ |a I:(DE-Juel1)INM-10-20170113
980 _ _ |a I:(DE-Juel1)IAS-6-20130828
980 _ _ |a APC
981 _ _ |a I:(DE-Juel1)IAS-6-20130828

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21