Michael Reimann

Affiliations: 
2015-2019 Department of Life Sciences EPFL / Blue Brain Project 
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"Michael Reimann"
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Roussel Y, Verasztó C, Rodarie D, et al. (2023) Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons. Plos Computational Biology. 19: e1010058
Rodarie D, Verasztó C, Roussel Y, et al. (2022) A method to estimate the cellular composition of the mouse brain from heterogeneous datasets. Plos Computational Biology. 18: e1010739
Reimann MW, Riihimäki H, Smith JP, et al. (2022) Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies. Plos One. 17: e0261702
Newton TH, Reimann MW, Abdellah M, et al. (2021) In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations. Nature Communications. 12: 3630
Ecker A, Romani A, Sáray S, et al. (2020) Data-driven integration of hippocampal CA1 synaptic physiology in silico. Hippocampus
Nolte M, Gal E, Markram H, et al. (2020) Impact of higher order network structure on emergent cortical activity. Network Neuroscience (Cambridge, Mass.). 4: 292-314
Reimann MW, Gevaert M, Shi Y, et al. (2019) A null model of the mouse whole-neocortex micro-connectome. Nature Communications. 10: 3903
Nolte M, Reimann MW, King JG, et al. (2019) Cortical reliability amid noise and chaos. Nature Communications. 10: 3792
Reimann MW, Nolte M, Scolamiero M, et al. (2017) Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function. Frontiers in Computational Neuroscience. 11: 48
Reimann MW, Horlemann AL, Ramaswamy S, et al. (2017) Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity. Cerebral Cortex (New York, N.Y. : 1991). 1-16
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