000908305 001__ 908305
000908305 005__ 20240313095011.0
000908305 037__ $$aFZJ-2022-02525
000908305 1001_ $$0P:(DE-Juel1)162130$$aSenk, Johanna$$b0$$eCorresponding author$$ufzj
000908305 1112_ $$aEBRAINS Workshop: Brain Activity across Scales and Species: Analysis of Experiments and Simulations$$cRome$$d2022-06-13 - 2022-06-15$$gBASSES$$wItaly
000908305 245__ $$aSimulating spatially organized networks with NEST
000908305 260__ $$c2022
000908305 3367_ $$033$$2EndNote$$aConference Paper
000908305 3367_ $$2DataCite$$aOther
000908305 3367_ $$2BibTeX$$aINPROCEEDINGS
000908305 3367_ $$2DRIVER$$aconferenceObject
000908305 3367_ $$2ORCID$$aLECTURE_SPEECH
000908305 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1661142827_7222$$xInvited
000908305 500__ $$aHands-on Session III
000908305 520__ $$aThis live demo ramps up from basic concepts to recent research on spatially organized neuronal network models with the simulator NEST (https://ebrains.eu/service/nest-simulator). Starting with the graphical user interface NEST Desktop (https://ebrains.eu/service/nest-desktop), we interactively construct a network model and explore its dynamics in the web browser. Afterwards, we turn to scripted PyNEST code and investigate the relationship between distance-dependent connectivity and spatially and temporally resolved patterns in spiking activity using Jupyter Notebooks. All examples will be made available in the EBRAINS Collaboratory.
000908305 536__ $$0G:(DE-HGF)POF4-5235$$a5235 - Digitization of Neuroscience and User-Community Building (POF4-523)$$cPOF4-523$$fPOF IV$$x0
000908305 536__ $$0G:(DE-HGF)POF4-5231$$a5231 - Neuroscientific Foundations (POF4-523)$$cPOF4-523$$fPOF IV$$x1
000908305 536__ $$0G:(DE-HGF)POF4-5234$$a5234 - Emerging NC Architectures (POF4-523)$$cPOF4-523$$fPOF IV$$x2
000908305 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x3
000908305 536__ $$0G:(DE-Juel1)JL SMHB-2021-2027$$aJL SMHB - Joint Lab Supercomputing and Modeling for the Human Brain (JL SMHB-2021-2027)$$cJL SMHB-2021-2027$$x4
000908305 7001_ $$0P:(DE-Juel1)180539$$aAlbers, Jasper$$b1$$ufzj
000908305 909CO $$ooai:juser.fz-juelich.de:908305$$pec_fundedresources$$pVDB$$popenaire
000908305 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162130$$aForschungszentrum Jülich$$b0$$kFZJ
000908305 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)180539$$aForschungszentrum Jülich$$b1$$kFZJ
000908305 9131_ $$0G:(DE-HGF)POF4-523$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5235$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vNeuromorphic Computing and Network Dynamics$$x0
000908305 9131_ $$0G:(DE-HGF)POF4-523$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5231$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vNeuromorphic Computing and Network Dynamics$$x1
000908305 9131_ $$0G:(DE-HGF)POF4-523$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5234$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vNeuromorphic Computing and Network Dynamics$$x2
000908305 9141_ $$y2022
000908305 920__ $$lno
000908305 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000908305 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x1
000908305 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x2
000908305 980__ $$aconf
000908305 980__ $$aVDB
000908305 980__ $$aI:(DE-Juel1)INM-6-20090406
000908305 980__ $$aI:(DE-Juel1)IAS-6-20130828
000908305 980__ $$aI:(DE-Juel1)INM-10-20170113
000908305 980__ $$aUNRESTRICTED
000908305 981__ $$aI:(DE-Juel1)IAS-6-20130828