| Year |
Citation |
Score |
| 2023 |
Rowland JM, van der Plas TL, Loidolt M, Lees RM, Keeling J, Dehning J, Akam T, Priesemann V, Packer AM. Propagation of activity through the cortical hierarchy and perception are determined by neural variability. Nature Neuroscience. 26: 1584-1594. PMID 37640911 DOI: 10.1038/s41593-023-01413-5 |
0.692 |
|
| 2023 |
Yamamoto H, Spitzner FP, Takemuro T, Buendía V, Murota H, Morante C, Konno T, Sato S, Hirano-Iwata A, Levina A, Priesemann V, Muñoz MA, Zierenberg J, Soriano J. Modular architecture facilitates noise-driven control of synchrony in neuronal networks. Science Advances. 9: eade1755. PMID 37624893 DOI: 10.1126/sciadv.ade1755 |
0.694 |
|
| 2021 |
Contreras S, Dehning J, Loidolt M, Zierenberg J, Spitzner FP, Urrea-Quintero JH, Mohr SB, Wilczek M, Wibral M, Priesemann V. The challenges of containing SARS-CoV-2 via test-trace-and-isolate. Nature Communications. 12: 378. PMID 33452267 DOI: 10.1038/s41467-020-20699-8 |
0.607 |
|
| 2020 |
de Heuvel J, Wilting J, Becker M, Priesemann V, Zierenberg J. Characterizing spreading dynamics of subsampled systems with nonstationary external input. Physical Review. E. 102: 040301. PMID 33212575 DOI: 10.1103/PhysRevE.102.040301 |
0.696 |
|
| 2020 |
Dehning J, Zierenberg J, Spitzner FP, Wibral M, Neto JP, Wilczek M, Priesemann V. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science (New York, N.Y.). PMID 32414780 DOI: 10.1126/science.abb9789 |
0.678 |
|
| 2020 |
Zierenberg J, Wilting J, Priesemann V, Levina A. Description of spreading dynamics by microscopic network models and macroscopic branching processes can differ due to coalescence. Physical Review. E. 101: 022301. PMID 32168601 DOI: 10.1103/PhysRevE.101.022301 |
0.699 |
|
| 2019 |
Datseris G, Ziereis A, Albrecht T, Hagmayer Y, Priesemann V, Geisel T. Microtiming Deviations and Swing Feel in Jazz. Scientific Reports. 9: 19824. PMID 31882842 DOI: 10.1038/S41598-019-55981-3 |
0.469 |
|
| 2018 |
Wilting J, Dehning J, Pinheiro Neto J, Rudelt L, Wibral M, Zierenberg J, Priesemann V. Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements. Frontiers in Systems Neuroscience. 12: 55. PMID 30459567 DOI: 10.3389/fnsys.2018.00055 |
0.705 |
|
| 2018 |
Sogorski M, Geisel T, Priesemann V. Correlated microtiming deviations in jazz and rock music. Plos One. 13: e0186361. PMID 29364920 DOI: 10.1371/Journal.Pone.0186361 |
0.498 |
|
| 2017 |
Del Papa B, Priesemann V, Triesch J. Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network. Plos One. 12: e0178683. PMID 28552964 DOI: 10.1371/journal.pone.0178683 |
0.581 |
|
| 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, ... ... Priesemann V, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.547 |
|
| 2014 |
Priesemann V, Wibral M, Valderrama M, Pröpper R, Le Van Quyen M, Geisel T, Triesch J, Nikoli? D, Munk MH. Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Frontiers in Systems Neuroscience. 8: 108. PMID 25009473 DOI: 10.3389/Fnsys.2014.00108 |
0.662 |
|
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