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000863678 037__ $$aFZJ-2019-03684
000863678 041__ $$aEnglish
000863678 1001_ $$0P:(DE-Juel1)162130$$aSenk, Johanna$$b0$$eCorresponding author
000863678 1112_ $$aNEST Conference 2019$$cAas$$d2019-06-24 - 2019-06-25$$wNorway
000863678 245__ $$aConnectivity Concepts for Neuronal Networks
000863678 260__ $$c2019
000863678 3367_ $$033$$2EndNote$$aConference Paper
000863678 3367_ $$2BibTeX$$aINPROCEEDINGS
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000863678 520__ $$aA statement like “$N_\text{s}$ source neurons and $N_\text{t}$ target neurons are connected randomly with connectionprobability $p$” may be used to describe the structure of a neuronal network model, but itsinterpretation is inherently ambiguous. A lacking detail is, for example, information on thedistribution of in- and outgoing connections, resulting in substantial differences in networkdynamics. For reproducible research, unambiguous network descriptions and correspondingalgorithmic implementations are necessary [1]. Here, we review simulation software (e.g., NEST[2]), specification languages (e.g., CSA [3]), and published network models made available by thecommunity in databases like ModelDB [4] and Open Source Brain [5]. We investigate the networkstructures computational neuroscientists use in their models and the terminology they use todescribe these models. From this, we derive a set of connectivity concepts providing modelers withguidelines to specify connectivity in a complete and concise way. Furthermore, this work aims toguide the comprehensive and efficient implementation of connection routines in simulationsoftware like NEST, thereby facilitating reproducible research on network models.$\qquad$References: $\qquad$1. Nordlie E, et al. (2009) Towards Reproducible Descriptions of Neuronal Network Models. PLoS Comput Biol. 5(8): e1000456. doi:10.1371/journal.pcbi.1000456 $\qquad$2. Gewaltig M-O and Diesmann M (2007). NEST (NEural Simulation Tool). Scholarpedia. 2(4):1430, doi:10.4249/scholarpedia.1430 $\qquad$3. Djurfeldt M (2012) The Connection-set Algebra—A Novel Formalism for the Representation of Connectivity Structure in Neuronal Network Models. Neuroinform. 10:287–304. doi:10.1007/s12021-012-9146-1 $\qquad$4. ModelDB [https://senselab.med.yale.edu/modeldb] $\qquad$5. Gleeson P, Cantarelli M, Marin B, . . . van Albada SJ, van Geit W, R Silver RA (in press) Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. Neuron.
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000863678 536__ $$0G:(EU-Grant)720270$$aHBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)$$c720270$$fH2020-Adhoc-2014-20$$x1
000863678 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x2
000863678 536__ $$0G:(DE-Juel1)jinb33_20121101$$aBrain-Scale Simulations (jinb33_20121101)$$cjinb33_20121101$$fBrain-Scale Simulations$$x3
000863678 536__ $$0G:(GEPRIS)347572269$$aSPP 2041 347572269 - Integration von Multiskalen-Konnektivität und Gehirnarchitektur in einem supercomputergestützten Modell der menschlichen Großhirnrinde (347572269)$$c347572269$$x4
000863678 536__ $$0G:(DE-Juel1)aca_20190115$$aAdvanced Computing Architectures (aca_20190115)$$caca_20190115$$fAdvanced Computing Architectures$$x5
000863678 7001_ $$0P:(DE-HGF)0$$aKriener, Birgit$$b1
000863678 7001_ $$0P:(DE-Juel1)164166$$aHagen, Espen$$b2
000863678 7001_ $$0P:(DE-Juel1)162131$$aBos, Hannah$$b3
000863678 7001_ $$0P:(DE-Juel1)169781$$aPlesser, Hans Ekkehard$$b4$$ufzj
000863678 7001_ $$0P:(DE-HGF)0$$aGewaltig, Marc-Oliver$$b5
000863678 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, Markus$$b6$$ufzj
000863678 7001_ $$0P:(DE-HGF)0$$aDjurfeldt, Mikael$$b7
000863678 7001_ $$0P:(DE-Juel1)168479$$aVoges, Nicole$$b8$$ufzj
000863678 7001_ $$0P:(DE-Juel1)138512$$avan Albada, Sacha$$b9$$ufzj
000863678 8564_ $$uhttps://indico-jsc.fz-juelich.de/event/92/
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000863678 9131_ $$0G:(DE-HGF)POF3-571$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vConnectivity and Activity$$x0
000863678 9141_ $$y2019
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000863678 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000863678 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x1
000863678 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x2
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