Tilo Schwalger - Publications

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

17/31 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Schmutz V, Gerstner W, Schwalger T. Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity. Journal of Mathematical Neuroscience. 10: 5. PMID 32253526 DOI: 10.1186/s13408-020-00082-z  1
2019 Muscinelli SP, Gerstner W, Schwalger T. How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. Plos Computational Biology. 15: e1007122. PMID 31181063 DOI: 10.1371/journal.pcbi.1007122  1
2017 Schwalger T, Deger M, Gerstner W. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size. Plos Computational Biology. 13: e1005507. PMID 28422957 DOI: 10.1371/journal.pcbi.1005507  1
2016 Kastner DB, Schwalger T, Ziegler L, Gerstner W. A Model of Synaptic Reconsolidation. Frontiers in Neuroscience. 10: 206. PMID 27242410 DOI: 10.3389/Fnins.2016.00206  1
2015 Schwalger T, Lindner B. Analytical approach to an integrate-and-fire model with spike-triggered adaptation. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 92: 062703. PMID 26764723 DOI: 10.1103/PhysRevE.92.062703  1
2015 Wieland S, Bernardi D, Schwalger T, Lindner B. Slow fluctuations in recurrent networks of spiking neurons. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 92: 040901. PMID 26565154 DOI: 10.1103/PhysRevE.92.040901  1
2015 Schwalger T, Droste F, Lindner B. Statistical structure of neural spiking under non-Poissonian or other non-white stimulation. Journal of Computational Neuroscience. 39: 29-51. PMID 25936628 DOI: 10.1007/s10827-015-0560-x  1
2015 Shiau L, Schwalger T, Lindner B. Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation. Journal of Computational Neuroscience. 38: 589-600. PMID 25894991 DOI: 10.1007/s10827-015-0558-4  1
2014 Deger M, Schwalger T, Naud R, Gerstner W. Fluctuations and information filtering in coupled populations of spiking neurons with adaptation. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 90: 062704. PMID 25615126 DOI: 10.1103/PhysRevE.90.062704  1
2013 Schwalger T, Lindner B. Patterns of interval correlations in neural oscillators with adaptation. Frontiers in Computational Neuroscience. 7: 164. PMID 24348372 DOI: 10.3389/fncom.2013.00164  1
2013 Bauermeister C, Schwalger T, Russell DF, Neiman AB, Lindner B. Characteristic effects of stochastic oscillatory forcing on neural firing: analytical theory and comparison to paddlefish electroreceptor data. Plos Computational Biology. 9: e1003170. PMID 23966844 DOI: 10.1371/Journal.Pcbi.1003170  1
2013 Droste F, Schwalger T, Lindner B. Interplay of two signals in a neuron with heterogeneous synaptic short-term plasticity. Frontiers in Computational Neuroscience. 7: 86. PMID 23882211 DOI: 10.3389/fncom.2013.00086  1
2012 Fisch K, Schwalger T, Lindner B, Herz AV, Benda J. Channel noise from both slow adaptation currents and fast currents is required to explain spike-response variability in a sensory neuron. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 32: 17332-44. PMID 23197724 DOI: 10.1523/JNEUROSCI.6231-11.2012  1
2011 Touya C, Schwalger T, Lindner B. Relation between cooperative molecular motors and active Brownian particles. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 83: 051913. PMID 21728577 DOI: 10.1103/PhysRevE.83.051913  1
2010 Schwalger T, Fisch K, Benda J, Lindner B. How noisy adaptation of neurons shapes interspike interval histograms and correlations. Plos Computational Biology. 6: e1001026. PMID 21187900 DOI: 10.1371/journal.pcbi.1001026  1
2008 Schwalger T, Lindner B. Higher-order statistics of a bistable system driven by dichotomous colored noise. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 78: 021121. PMID 18850800 DOI: 10.1103/PhysRevE.78.021121  1
2007 Lindner B, Schwalger T. Correlations in the sequence of residence times. Physical Review Letters. 98: 210603. PMID 17677758 DOI: 10.1103/PhysRevLett.98.210603  1
Low-probability matches
2008 Schwalger T, Schimansky-Geier L. Interspike interval statistics of a leaky integrate-and-fire neuron driven by Gaussian noise with large correlation times. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 77: 031914. PMID 18517429 DOI: 10.1103/PhysRevE.77.031914  0.08
2011 Schwalger T, Fisch K, Benda J, Lindner B. How stochastic adaptation of neurons shapes interspike interval statistics – theory and experiment Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P199  0.04
2020 Pietras B, Gallice N, Schwalger T. Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons. Physical Review. E. 102: 022407. PMID 32942450 DOI: 10.1103/PhysRevE.102.022407  0.01
2020 Pietras B, Gallice N, Schwalger T. Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons Physical Review E. 102. DOI: 10.1103/PhysRevE.102.022407  0.01
2019 Schwalger T, Chizhov AV. Mind the last spike - firing rate models for mesoscopic populations of spiking neurons. Current Opinion in Neurobiology. 58: 155-166. PMID 31590003 DOI: 10.1016/j.conb.2019.08.003  0.01
2015 Schwalger T, Deger M, Gerstner W. Bridging spiking neuron models and mesoscopic population models - a general theory for neural population dynamics Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P79  0.01
2013 Schwalger T, Lindner B. Non-renewal spiking and neural dynamics - a simple theory of interspike-interval correlations in adapting neurons Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-O9  0.01
2013 Schwalger T, Miklody D, Lindner B. When the leak is weak – how the first-passage statistics of a biased random walk can approximate the ISI statistics of an adapting neuron The European Physical Journal Special Topics. 222: 2655-2666. DOI: 10.1140/EPJST/E2013-02045-4  0.01
2012 Schwalger T, Tiana-Alsina J, Torrent MC, Garcia-Ojalvo J, Lindner B. Interspike-interval correlations induced by two-state switching in an excitable system Epl (Europhysics Letters). 99: 10004. DOI: 10.1209/0295-5075/99/10004  0.01
2012 Droste F, Schwalger T, Lindner B. Heterogeneous short-term plasticity enables spectral separation of information in the neural spike train Bmc Neuroscience. 13. DOI: 10.1186/1471-2202-13-S1-P98  0.01
2009 Schwalger T, Goedeke S, Diesmann M. Bifurcation analysis of synchronization dynamics in cortical feed-forward networks in novel coordinates Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P256  0.01
2009 Schwalger T, Lindner B. Serial interspike interval correlations of excitable neurons with memory Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P122  0.01
2008 Goedeke S, Schwalger T, Diesmann M. Theory of neuronal spike densities for synchronous activity in cortical feed-forward networks Bmc Neuroscience. 9: P143. DOI: 10.1186/1471-2202-9-S1-P143  0.01
2006 Schwalger T, Dzhanoev A, Loskutov A. May chaos always be suppressed by parametric perturbations? Chaos (Woodbury, N.Y.). 16: 023109. PMID 16822012 DOI: 10.1063/1.2195787  0.01
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