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@ARTICLE{Schmidt:851363,
author = {Schmidt, Maximilian and Bakker, Rembrandt and Shen, Kelly
and Bezgin, Gleb and Diesmann, Markus and van Albada, Sacha
Jennifer},
title = {{A} multi-scale layer-resolved spiking network model of
resting-state dynamics in macaque visual cortical areas},
journal = {PLoS Computational Biology},
volume = {14},
number = {10},
issn = {1553-734X},
address = {San Francisco, Calif.},
publisher = {Public Library of Science},
reportid = {FZJ-2018-05048},
pages = {e1006359 -},
year = {2018},
abstract = {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.},
cin = {INM-6 / INM-10 / IAS-6},
ddc = {570},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)INM-10-20170113 /
I:(DE-Juel1)IAS-6-20130828},
pnm = {571 - Connectivity and Activity (POF3-571) / 574 - Theory,
modelling and simulation (POF3-574) / HBP SGA2 - Human Brain
Project Specific Grant Agreement 2 (785907) / HBP SGA1 -
Human Brain Project Specific Grant Agreement 1 (720270) /
HBP - The Human Brain Project (604102) / SMHB -
Supercomputing and Modelling for the Human Brain
(HGF-SMHB-2013-2017) / Brain-Scale Simulations
$(jinb33_20121101)$ / SPP 2041 347572269 - Integration von
Multiskalen-Konnektivität und Gehirnarchitektur in einem
supercomputergestützten Modell der menschlichen
Großhirnrinde (347572269) / BRAINSCALES - Brain-inspired
multiscale computation in neuromorphic hybrid systems
(269921) / HBP - Human Brain Project (284941)},
pid = {G:(DE-HGF)POF3-571 / G:(DE-HGF)POF3-574 /
G:(EU-Grant)785907 / G:(EU-Grant)720270 / G:(EU-Grant)604102
/ G:(DE-Juel1)HGF-SMHB-2013-2017 /
$G:(DE-Juel1)jinb33_20121101$ / G:(GEPRIS)347572269 /
G:(EU-Grant)269921 / G:(EU-Grant)284941},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:30335761},
UT = {WOS:000450712400004},
doi = {10.1371/journal.pcbi.1006359},
url = {https://juser.fz-juelich.de/record/851363},
}