| Year |
Citation |
Score |
| 2022 |
Braun W, Memmesheimer RM. High-frequency oscillations and sequence generation in two-population models of hippocampal region CA1. Plos Computational Biology. 18: e1009891. PMID 35176028 DOI: 10.1371/journal.pcbi.1009891 |
0.333 |
|
| 2020 |
Klos C, Kalle Kossio YF, Goedeke S, Gilra A, Memmesheimer RM. Dynamical Learning of Dynamics. Physical Review Letters. 125: 088103. PMID 32909804 DOI: 10.1103/Physrevlett.125.088103 |
0.669 |
|
| 2019 |
Pallasdies F, Goedeke S, Braun W, Memmesheimer RM. From single neurons to behavior in the jellyfish . Elife. 8. PMID 31868586 DOI: 10.7554/eLife.50084 |
0.322 |
|
| 2019 |
Manz P, Goedeke S, Memmesheimer RM. Dynamics and computation in mixed networks containing neurons that accelerate towards spiking. Physical Review. E. 100: 042404. PMID 31770941 DOI: 10.1103/PhysRevE.100.042404 |
0.511 |
|
| 2018 |
Viriyopase A, Memmesheimer RM, Gielen S. Analyzing the competition of gamma rhythms with delayed pulse-coupled oscillators in phase representation. Physical Review. E. 98: 022217. PMID 30253475 DOI: 10.1103/PhysRevE.98.022217 |
0.5 |
|
| 2018 |
Kossio FYK, Goedeke S, van den Akker B, Ibarz B, Memmesheimer RM. Growing Critical: Self-Organized Criticality in a Developing Neural System. Physical Review Letters. 121: 058301. PMID 30118252 DOI: 10.1103/PhysRevLett.121.058301 |
0.382 |
|
| 2016 |
Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Memmesheimer R, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.515 |
|
| 2016 |
Thalmeier D, Uhlmann M, Kappen HJ, Memmesheimer RM. Learning Universal Computations with Spikes. Plos Computational Biology. 12: e1004895. PMID 27309381 DOI: 10.1371/journal.pcbi.1004895 |
0.516 |
|
| 2016 |
Viriyopase A, Memmesheimer RM, Gielen S. Cooperation and competition of gamma oscillation mechanisms. Journal of Neurophysiology. 116: 232-51. PMID 26912589 DOI: 10.1152/jn.00493.2015 |
0.412 |
|
| 2016 |
Abbott LF, DePasquale B, Memmesheimer RM. Building functional networks of spiking model neurons. Nature Neuroscience. 19: 350-5. PMID 26906501 DOI: 10.1038/Nn.4241 |
0.449 |
|
| 2015 |
Jahnke S, Timme M, Memmesheimer RM. A Unified Dynamic Model for Learning, Replay, and Sharp-Wave/Ripples. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 16236-58. PMID 26658873 DOI: 10.1523/Jneurosci.3977-14.2015 |
0.552 |
|
| 2014 |
Jahnke S, Memmesheimer RM, Timme M. Oscillation-induced signal transmission and gating in neural circuits. Plos Computational Biology. 10: e1003940. PMID 25503492 DOI: 10.1371/Journal.Pcbi.1003940 |
0.6 |
|
| 2014 |
Memmesheimer RM, Rubin R, Olveczky BP, Sompolinsky H. Learning precisely timed spikes. Neuron. 82: 925-38. PMID 24768299 DOI: 10.1016/j.neuron.2014.03.026 |
0.409 |
|
| 2014 |
Jahnke S, Memmesheimer RM, Timme M. Hub-activated signal transmission in complex networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 89: 030701. PMID 24730779 DOI: 10.1103/Physreve.89.030701 |
0.669 |
|
| 2014 |
Breuer D, Timme M, Memmesheimer RM. Statistical physics of neural systems with nonadditive dendritic coupling Physical Review X. 4. DOI: 10.1103/Physrevx.4.011053 |
0.68 |
|
| 2013 |
Jahnke S, Memmesheimer RM, Timme M. Propagating synchrony in feed-forward networks. Frontiers in Computational Neuroscience. 7: 153. PMID 24298251 DOI: 10.3389/Fncom.2013.00153 |
0.645 |
|
| 2013 |
Jahnke S, Memmesheimer R, Timme M. Oscillation induced propagation of synchrony in structured neural networks Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P390 |
0.701 |
|
| 2013 |
Breuer D, Timme M, Memmesheimer R. Computational optimum of recurrent neural circuits at intermediate numbers of nonlinear dendritic branches Bmc Neuroscience. 14: P273. DOI: 10.1186/1471-2202-14-S1-P273 |
0.664 |
|
| 2012 |
Memmesheimer RM, Timme M. Non-additive coupling enables propagation of synchronous spiking activity in purely random networks. Plos Computational Biology. 8: e1002384. PMID 22532791 DOI: 10.1371/Journal.Pcbi.1002384 |
0.731 |
|
| 2012 |
Jahnke S, Timme M, Memmesheimer RM. Guiding Synchrony through Random Networks Physical Review X. 2. DOI: 10.1103/Physrevx.2.041016 |
0.698 |
|
| 2011 |
van den Akker B, Ibarz B, Memmesheimer R. Self-organized criticality in a model for developing neural networks Bmc Neuroscience. 12: P221. DOI: 10.1186/1471-2202-12-S1-P221 |
0.312 |
|
| 2010 |
Memmesheimer RM. Quantitative prediction of intermittent high-frequency oscillations in neural networks with supralinear dendritic interactions. Proceedings of the National Academy of Sciences of the United States of America. 107: 11092-7. PMID 20511534 DOI: 10.1073/pnas.0909615107 |
0.514 |
|
| 2010 |
Memmesheimer RM, Timme M. Stable and unstable periodic orbits in complex networks of spiking neurons with delays Discrete and Continuous Dynamical Systems. 28: 1555-1588. DOI: 10.3934/Dcds.2010.28.1555 |
0.706 |
|
| 2009 |
Jahnke S, Memmesheimer RM, Timme M. How Chaotic is the Balanced State? Frontiers in Computational Neuroscience. 3: 13. PMID 19936316 DOI: 10.3389/Neuro.10.013.2009 |
0.694 |
|
| 2008 |
Jahnke S, Memmesheimer RM, Timme M. Stable irregular dynamics in complex neural networks. Physical Review Letters. 100: 048102. PMID 18352336 DOI: 10.1103/Physrevlett.100.048102 |
0.704 |
|
| 2007 |
Memmesheimer R, Timme M. Non-additive coupling enables stable propagation of synchronous spiking in purely random networks Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P31 |
0.689 |
|
| 2006 |
Memmesheimer RM, Timme M. Designing the dynamics of spiking neural networks. Physical Review Letters. 97: 188101. PMID 17155580 DOI: 10.1103/Physrevlett.97.188101 |
0.705 |
|
| 2006 |
Memmesheimer RM, Timme M. Designing complex networks Physica D: Nonlinear Phenomena. 224: 182-201. DOI: 10.1016/J.Physd.2006.09.037 |
0.694 |
|
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