Priesemann, Viola

Authors Blümel M, Schneider AC, Neuhaus V, Ehrlich DA, Graetz M, Wibral M, Makkeh A, Priesemann V Journal Arxiv Citation arXiv:2511.02584 Abstract Associative memory, traditionally modeled by Hopfield networks, enables the retrieval of previously stored patterns from partial or noisy cues. Yet, the local computational principles which are required to

Authors Müller L, Mallick P, Marín-Carballo AB, Dönges P, Kettlitz RJN, Klett-Tammen CJ, Kretzschmar M, Priesemann V, Contreras S Journal Proceedings of the National Academy of Sciences of the United States of America Citation Proc Natl Acad Sci U S A. 2025 Nov 4;122(44):e2524944122. Abstract HIV pre-exposure prophylaxis (PrEP) is

Authors Lewen D, Ivanov V, Dehning J, Ruß J, Fischer A, Penke L, Schacht A, Gail A, Priesemann V, Kagan I Journal BioRxiv Citation bioRxiv 2025.05.28.655569. Abstract Real-life social interactions often unfold continuously and involve dynamic cooperation and competition, yet most studies rely on discrete games that do not capture

Authors Mikulasch FA, Georgiev SV, Rudelt L, Rizzoli SO, Priesemann V Journal Communications Biology Citation Commun Biol. 2025 Apr 2;8(1):542. Abstract After synaptic transmission, fused synaptic vesicles are recycled, enabling the synapse to recover its capacity for renewed release. The recovery steps, which range from endocytosis to vesicle docking and

Authors Wagner J, Bauer S, Contreras S, Fleddermann L, Parlitz U, Priesemann V Journal Physical Review Research Citation Phys. Rev. Research 7, 013308. Abstract Classically, endemic infectious diseases are expected to display relatively stable, predictable infection dynamics. Accordingly, basic disease models such as the susceptible-infected-recovered-susceptible model display stable endemic states

Authors Makkeh A, Graetz M, Schneider AC, Ehrlich DA, Priesemann V, Wibral M Journal Proceedings of the National Academy of Sciences of the United States of America Citation Proc Natl Acad Sci U S A. 2025 Mar 11;122(10):e2408125122. Abstract Despite the impressive performance of biological and artificial networks, an intuitive

Authors Reitenbach A, Sartori F, Banisch S, Golovin A, Calero Valdez A, Kretzschmar M, Priesemann V, Mäs M Journal Reports on Progress in Physics Citation Rep. Prog. Phys. 88 016601. Abstract To comprehend the dynamics of infectious disease transmission, it is imperative to incorporate human protective behavior into models of

Authors Schneider AC, Neuhaus V, Ehrlich DA, Makkeh A, Ecker AS, Priesemann V, Wibral M Journal Arxiv Citation arXiv:2412.02482. Abstract In modern deep neural networks, the learning dynamics of the individual neurons is often obscure, as the networks are trained via global optimization. Conversely, biological systems build on self-organized, local

Authors Reshetniak S, Bogaciu CA, Bonn S, Brose N, Cooper BH, D’Este E, Fauth M, Fernández-Busnadiego R, Fiosins M, Fischer A, Georgiev SV, Jakobs S, Klumpp S, Köster S, Lange F, Lipstein N, Macarrón-Palacios V, Milovanovic D, Moser T, Müller M, Opazo F, Outeiro TF, Pape C, Priesemann V, Rehling

Authors Rudelt L, González Marx D, Spitzner FP, Cramer B, Zierenberg J, Priesemann V. Journal PLoS Computational Biology Citation PLoS Comput Biol. 2024 Aug 22;20(8):e1012355. Abstract A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing