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  Modular architecture facilitates noise-driven control of synchrony in neuronal networks

Yamamoto, H., Spitzner, F. P., Takemuro, T., Buendía, V., Murota, H., Morante, C., et al. (2023). Modular architecture facilitates noise-driven control of synchrony in neuronal networks. Science Advances, 9(34): eade175. doi:10.1126/sciadv.ade1755.

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 Creators:
Yamamoto, Hideaki, Author
Spitzner, F. Paul1, Author           
Takemuro, Taiki, Author
Buendía, Victor, Author
Murota, Hakuba, Author
Morante, Carla, Author
Konno, Tomohiro, Author
Sato, Shigeo, Author
Hirano-Iwata, Ayumi, Author
Levina, Anna, Author
Priesemann, Viola1, Author           
Muñoz, Miguel A., Author
Zierenberg, Johannes1, Author           
Soriano, Jordi, Author
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1Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2616694              

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 Abstract: High-level information processing in the mammalian cortex requires both segregated 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.

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Language(s): eng - English
 Dates: 2023-08-252023
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1126/sciadv.ade1755
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Project name : H.Y., A.H.-I., and S.S. acknowledge MEXT Grant-in-Aid for Transformative Research Areas (B) “Multicellular Neurobiocomputing” (21H05164), JSPS KAKENHI (18H03325, 19H00846, 20H02194, 20K20550, 22H03657, 22K19821, 22KK0177, and 23H03489), JST-PRESTO (JMPJPR18MB), JST-CREST (JPMJCR19K3), and Tohoku University RIEC Cooperative Research Project Program for financial support. F.P.S., V.P., and J.Z. received support from the Max-Planck-Society. F.P.S. acknowledges funding by SMARTSTART, the joint training program in computational neuroscience by the VolkswagenStiftung and the Bernstein Network. F.P.S. and V.P. were funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), SFB-1528–Cognition of Interaction. V.P. was supported by the DFG under Germany’s Excellence Strategy EXC 2067/1- 390729940. V.B. and A.L. were supported by a Sofja Kovalevskaja Award from the Alexander von Humboldt Foundation, endowed by the Federal Ministry of Education and Research. A.L. is a member of the Machine Learning Cluster of Excellence EXC 2064/1- 39072764. M.A.M. acknowledges the Spanish Ministry and Agencia Estatal de investigación (AEI) through Project of I + D + i (PID2020-113681GB-I00), financed by MICIN/AEI/10.13039/501100011033 and FEDER “A way to make Europe”, and the Consejería de Conocimiento, Investigación Universidad, Junta de Andalucía and European Regional Development Fund (P20-00173) for financial support. J.Z. received financial support from the Joachim Herz Stiftung. J.S. acknowledges Horizon 2020 Future and Emerging Technologies (grant agreement 964877-NEUChiP), Ministerio de Ciencia, Innovación y Universidades (PID2019-108842GB-C21), and Departament de Recerca i Universitats, Generalitat de Catalunya (2017-SGR-1061 and 2021-SGR-00450) for financial support.
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Title: Science Advances
  Other : Sci. Adv.
Source Genre: Journal
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Publ. Info: Washington : AAAS
Pages: 12 Volume / Issue: 9 (34) Sequence Number: eade175 Start / End Page: - Identifier: ISSN: 2375-2548
CoNE: https://pure.mpg.de/cone/journals/resource/2375-2548