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Títol: Modular architecture facilitates noise-driven control of synchrony in neuronal networks
Autor: Yamamoto, Hideaki
Spitzner, F. Paul
Takemuro, Taiki
Buendía, Victor
Murota, Hakuba
Morante, Carla
Konno, Tomohiro
Sato, Shigeo
Hirano-Iwata, Ayumi
Levina, Anna
Priesemann, Viola
Muñoz, Miguel A.
Zierenberg, Johannes
Soriano i Fradera, Jordi
Matèria: Xarxes neuronals (Informàtica)
Mamífers
Mètodes de simulació
Neural networks (Computer science)
Mammals
Simulation methods
Data de publicació: 25-ago-2023
Publicat per: American Association for the Advancement of Science
Resum: High-level information processing in the mammalian cortex requires both egregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.
Nota: Reproducció del document publicat a: https://doi.org/10.1126/sciadv.ade1755
És part de: Science Advances, 2023, vol. 9, p. 1-12
URI: https://hdl.handle.net/2445/221490
Recurs relacionat: https://doi.org/10.1126/sciadv.ade1755
Apareix en les col·leccions:Articles publicats en revistes (Física de la Matèria Condensada)
Articles publicats en revistes (Institut de Recerca en Sistemes Complexos (UBICS))

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