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@INPROCEEDINGS{Dahmen:889319,
author = {Dahmen, David and Layer, Moritz and Deutz, Lukas and
Dabrowska, Paulina and Voges, Nicole and von Papen, Michael
and Brochier, Thomas and Riehle, Alexa and Diesmann, Markus
and Grün, Sonja and Helias, Moritz},
title = {{L}ong-range coordination patterns in cortex change with
behavioral context},
reportid = {FZJ-2021-00211},
year = {2021},
abstract = {The cerebral cortex is a network of subnetworks that is
organized onvarious spatial scales. Understanding how
neurons communicate at thedifferent scales is crucial for
understanding brain dynamics andfunction. On the microscopic
scale the connectivity stems mostly fromlocal axonal
arborizations, suggesting coordination is strongestbetween
nearby neurons in the range of a few hundred micrometers.
Yetrecent studies found activity of neurons across much
larger distancesto be organized in manifolds. The emergence
of such manifolds relieson complex coordination patterns
between neurons. We here analyzemulti-electrode recordings
of resting-state activity in macaque motorcortex that indeed
show strong positive and negative spike-countcovariances
between neurons that are millimeters apart. To understandthe
origin of such coordination we develop a conceptually
novelnetwork theory that combines the spatial extent and
heterogeneity ofthe connectivity with fluctuations of
activity treated beyond themean-field approximation. This
quantitative theory uncovers a simpleand ubiquitous
mechanism that generates long-range correlationpatterns
despite short-range connections: the heterogeneity
ofconnections causes a dynamical network state that
emphasizescooperation of neurons by multi-synaptic
interactions. The mechanismdoes not rely on specific
connectivity structures, but emerges inspatially organized
networks with even random connectivity. The theorynot only
explains the experimentally observed shallow
exponentialdecay of the width of the covariance distribution
at long distances,but also predicts that neuronal
coordination patterns can change in astate-dependent manner.
We confirm this prediction by comparingactivity in macaque
motor cortex across different behavioral epochs ofa
reach-to-grasp experiment. Our results explain how
spatiallyextended neural manifolds can emerge from the local
networkconnectivity.},
month = {Jan},
date = {2021-01-11},
organization = {SfN Global Connectome, virtual
(worldwide), 11 Jan 2021 - 13 Jan 2021},
subtyp = {After Call},
cin = {INM-6 / IAS-6 / INM-10},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
I:(DE-Juel1)INM-10-20170113},
pnm = {5231 - Neuroscientific Foundations (POF4-523) / 5232 -
Computational Principles (POF4-523) / MSNN - Theory of
multi-scale neuronal networks (HGF-SMHB-2014-2018) / HBP
SGA2 - Human Brain Project Specific Grant Agreement 2
(785907) / GRK 2416 - GRK 2416: MultiSenses-MultiScales:
Neue Ansätze zur Aufklärung neuronaler multisensorischer
Integration (368482240) / HBP SGA3 - Human Brain Project
Specific Grant Agreement 3 (945539)},
pid = {G:(DE-HGF)POF4-5231 / G:(DE-HGF)POF4-5232 /
G:(DE-Juel1)HGF-SMHB-2014-2018 / G:(EU-Grant)785907 /
G:(GEPRIS)368482240 / G:(EU-Grant)945539},
typ = {PUB:(DE-HGF)24},
url = {https://juser.fz-juelich.de/record/889319},
}