Tilo Schwalger

Affiliations: 
EPFL, Brain Mind Institute, Lausanne, Vaud, Switzerland 
Area:
stochastic processes, mean-field methods, spike train statistics, spike-frequency adaptation
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"Tilo Schwalger"
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Publications

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Gastaldi C, Schwalger T, De Falco E, et al. (2021) When shared concept cells support associations: Theory of overlapping memory engrams. Plos Computational Biology. 17: e1009691
Schwalger T. (2021) Mapping input noise to escape noise in integrate-and-fire neurons: a level-crossing approach. Biological Cybernetics. 115: 539-562
Pietras B, Gallice N, Schwalger T. (2020) Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons. Physical Review. E. 102: 022407
Schmutz V, Gerstner W, Schwalger T. (2020) Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity. Journal of Mathematical Neuroscience. 10: 5
Pietras B, Gallice N, Schwalger T. (2020) Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons Physical Review E. 102
Schwalger T, Chizhov AV. (2019) Mind the last spike - firing rate models for mesoscopic populations of spiking neurons. Current Opinion in Neurobiology. 58: 155-166
Muscinelli SP, Gerstner W, Schwalger T. (2019) How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. Plos Computational Biology. 15: e1007122
Schwalger T, Deger M, Gerstner W. (2017) Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size. Plos Computational Biology. 13: e1005507
Kastner DB, Schwalger T, Ziegler L, et al. (2016) A Model of Synaptic Reconsolidation. Frontiers in Neuroscience. 10: 206
Schwalger T, Lindner B. (2015) Analytical approach to an integrate-and-fire model with spike-triggered adaptation. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 92: 062703
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