Markus Diesmann

RIKEN Brain Science Institute, Wakō-shi, Saitama-ken, Japan 
Computational Neuroscience
"Markus Diesmann"
Mean distance: 14.77 (cluster 17)
Cross-listing: Computational Biology Tree

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Jordan J, Helias M, Diesmann M, et al. (2020) Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions. Frontiers in Neuroinformatics. 14: 12
Schmidt M, Bakker R, Hilgetag CC, et al. (2020) Correction to: Multi-scale account of the network structure of macaque visual cortex. Brain Structure & Function
Jordan J, Petrovici MA, Breitwieser O, et al. (2019) Deterministic networks for probabilistic computing. Scientific Reports. 9: 18303
Dahmen D, Grün S, Diesmann M, et al. (2019) Second type of criticality in the brain uncovers rich multiple-neuron dynamics. Proceedings of the National Academy of Sciences of the United States of America
Einevoll GT, Destexhe A, Diesmann M, et al. (2019) The Scientific Case for Brain Simulations. Neuron. 102: 735-744
Kass RE, Amari SI, Arai K, et al. (2018) Computational Neuroscience: Mathematical and Statistical Perspectives. Annual Review of Statistics and Its Application. 5: 183-214
Senk J, Carde C, Hagen E, et al. (2018) VIOLA-A Multi-Purpose and Web-Based Visualization Tool for Neuronal-Network Simulation Output. Frontiers in Neuroinformatics. 12: 75
Schmidt M, Bakker R, Shen K, et al. (2018) A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas. Plos Computational Biology. 14: e1006359
Maksimov A, Diesmann M, van Albada SJ. (2018) Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models. Frontiers in Computational Neuroscience. 12: 44
Jordan J, Ippen T, Helias M, et al. (2018) Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers. Frontiers in Neuroinformatics. 12: 34
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