Publikationen von Viola Priesemann

Alwan, N. A.; Burgess, R. A.; Ashworth, S.; Beale, R.; Bhadelia, N.; Bogaert, D.; Dowd, J.; Eckerle, I.; Goldman, L. R.; Greenhalgh, T. et al.; Gurdasani, D.; Hamdy, A.; Hanage, W. P.; Hodcroft, E. B.; Hyde, Z.; Kellam, P.; Kelly-Irving, M.; Krammer, F.; Lipsitch, M.; McNally, A.; McKee, M.; Nouri, A.; Pimenta, D.; Priesemann, V.; Rutter, H.; Silver, J.; Sridhar, D.; Swanton, C.; Walensky, R. P.; Yamey, G.; Ziauddeen, H.: Scientific consensus on the COVID-19 pandemic: we need to act now. The Lancet 396, S. e71 - e72 (2020)

Cramer, B.; Stöckel, D.; Kreft, M.; Wibral, M.; Schemmel, J.; Meier, K.; Priesemann, V.: Control of criticality and computation in spiking neuromorphic networks with plasticity. Nature Communications 11, 2853 (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 (2020)

Gurdasani, D.; Bear, L.; Bogaert, D.; Burgess, R. A.; Busse, R.; Cacciola, R.; Charpak, Y.; Colbourn, T.; Drury, J.; Friston, K. et al.; Gallo, V.; Goldman, L. R.; Greenhalgh, T.; Hyde, Z.; Kuppalli, K.; Majumder, M. S.; Martin-Moreno, J. M.; McKee, M.; Michie, S.; Mossialos, E.; Nouri, A.; Pagel, C.; Pimenta, D.; Popescu, S.; Priesemann, V.; Rasmussen, A. L.; Reicher, S.; Ricciardi, W.; Rice, K.; Silver, J.; Smith, T. C.; Wenham, C.; West, R.; Yamey, G.; Yates, C.; Ziauddeen, H.: The UK needs a sustainable strategy for COVID-19. The Lancet 396, S. 1800 - 1801 (2020)

Linden, M.; Mohr, S. B.; Dehning, J.; Mohring, J.; Meyer-Hermann, M.; Pigeot, I.; Schöbel, A.; Priesemann, V.: Case Numbers Beyond Contact Tracing Capacity Are Endangering the Containment of COVID-19. Deutsches Ärzteblatt International 117, S. 790 - 791 (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 (2), 022301 (2020)

Zierenberg, J.; Wilting, J.; Priesemann, V.; Levina, A.: Tailored ensembles of neural networks optimize sensitivity to stimulus statistics. Physical Review Research 2, 013115 (2020)

Wilting, J.; Priesemann, V.: 25 years of criticality in neuroscience - established results, open controversies, novel concepts. Current Opinion in Neurobiology 58, S. 105 - 111 (2019)

Wilting, J.; Priesemann, V.: Between perfectly critical and fully irregular: A reverberating model captures and predicts cortical spike propagation. Cerebral Cortex 29 (6), S. 2759 - 2770 (2019)

Datseris, G.; Ziereis, A.; Albrecht, T.; Hagmayer, Y.; Priesemann, V.; Geisel, T.: Microtiming deviations and swing feel in jazz. Scientific Reports 9, 19824 (2019)

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 (2018)

Zierenberg, J.; Wilting, J.; Priesemann, V.: Homeostatic plasticity and external input shape neural network dynamics. Physical Review X 8 (3), 031018 (2018)

Wilting, J.; Priesemann, V.: Inferring collective dynamical states from widely unobserved systems. Nature Communications 9, 2325 (2018)

Priesemann, V.; Shriki, O.: Can a time varying external drive give rise to apparent criticality in neural systems? PLOS Computational Biology 14 (5), e1006081 (2018)

Sogorski, M.; Geisel, T.; Priesemann, V.: Correlated microtiming deviations in jazz and rock music. PLoS One 13 (1), e0186361 (2018)

Wibral, M.; Finn, C.; Wollstadt, P.; Lizier, J. T.; Priesemann, V.: Quantifying information modification in developing neural networks via partial information decomposition. Entropy 19 (9), 494 (2017)

Wollstadt, P.; Sellers, K. K.; Rudelt, L.; Priesemann, V.; Hutt, A.; Fröhlich, F.; Wibral, M.: Breakdown of local information processing may underlie isoflurane anesthesia effects. PLoS Computational Biology 13 (6), e1005511 (2017)

Del Papa, B.; Priesemann, V.; Triesch, J.: Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network. PLoS One 12 (5), e0178683 (2017)

Levina, A.; Priesemann, V.: Subsampling scaling. Nature Communications 8, 15140 (2017)

Wibral, M.; Priesemann, V.; Kay, J. W.; Lizier, J. T.; Phillips, W. A.: Partial information decomposition as a unified approach to the specification of neural goal functions. Brain and Cognition 112, S. 25 - 38 (2017)