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001014811 037__ $$aFZJ-2023-03481
001014811 041__ $$aEnglish
001014811 1001_ $$0P:(DE-Juel1)171572$$aGutzen, Robin$$b0$$ufzj
001014811 1112_ $$aConcluding Event of the Human Brain Project$$cJülich$$d2023-09-12 - 2023-09-13$$wGermany
001014811 245__ $$aExploring the diversity of cortical wave activity with a unifying workflow approach
001014811 260__ $$c2023
001014811 3367_ $$033$$2EndNote$$aConference Paper
001014811 3367_ $$2DataCite$$aOther
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001014811 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1695101919_21354$$xAfter Call
001014811 520__ $$aAlthough brain waves have been studied for a long time, the complex spatial dynamics of such waves became observable only with high-resolution measurement technology. Recent studies of cortical wave activity present various propagation patterns, cortical localization, frequency regimes, and potentially functional roles [e.g. Denker et al. 2018,  Davis et al. 2020].Such heterogeneity warrants analysis approaches that enable the combination and comparison of data and results from different sources, facilitating a cumulative understanding of cortical wave activity. We developed an adaptable and reusable workflow approach to combine various data modalities and analysis methods, by combining existing software tools and standards from the EBRAINS environment.We showcase how this approach enables large meta-studies, comparing slow wave activity in anesthetized mice across heterogenous data sources [Gutzen et al. 2022] and the calibration and validation of corresponding network models [Capone et al. 2023]. Further, we demonstrate its extension to new applications, data modalities, and wave types. Specifically, we analyze LFP phase waves in the visual cortex of the macaque monkey in the context of visual perception and the coordination of corresponding saccadic eye movements.In doing so, we illustrate how the adaptable reusability of research software accelerates research, enhances automation, supports collaboration, promotes reproducibility, and enables cross-domain comparisons.
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001014811 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x2
001014811 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x3
001014811 536__ $$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$$x4
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001014811 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)171572$$aForschungszentrum Jülich$$b0$$kFZJ
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001014811 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$$x1
001014811 9141_ $$y2023
001014811 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
001014811 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x1
001014811 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x2
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