pSpitzner 7c0c848720 gin commit from vigsoe		1 anno fa
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README.md	7c0c848720 gin commit from vigsoe	1 anno fa
s7_k=3_0Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
s8_k=3_20Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=10_80Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=10_90Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=1_80Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=1_90Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=5_80Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=5_90Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_k=5_combined.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_merged_80Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sx_merged_90Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=10_0Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=10_20Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=1_0Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=1_20Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=5_0Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa
sy_k=5_20Hz.mp4	7c0c848720 gin commit from vigsoe	1 anno fa

Movies of simulations

The files that start with sx_ stem from the initial submission, where we simulated noise applied to all modules (global stimulation). In this case, the freuqency is the total stimulation rate.

The rest (mostly sy_) were created later, applying 20Hz extra, only in the lower two modules (orange). Also, for those topologies, the in-degree was fixed to 30 (this was not the case for those above).

datacite.yml
Title	Data for 'Modular architecture facilitates noise-driven control of synchrony in neuronal networks'
Authors	Yamamoto,Hideaki;Research Institute of Electrical Communication (RIEC), Tohoku University, Sendai, Japan Spitzner,F. Paul;Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany Takemuro,Taiki;Research Institute of Electrical Communication (RIEC), Tohoku University, Sendai, Japan Buendía,Victor;Max Planck Institute for Biological Cybernetics, Tübingen, Germany Murota,Hakuba;Research Institute of Electrical Communication (RIEC), Tohoku University, Sendai, Japan Morante,Carla;Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain Konno,Tomohiro;Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan Sato,Shigeo;Research Institute of Electrical Communication (RIEC), Tohoku University, Sendai, Japan Hirano-Iwata,Ayumi;Research Institute of Electrical Communication (RIEC), Tohoku University, Sendai, Japan Levina,Anna;Max Planck Institute for Biological Cybernetics, Tübingen, Germany Priesemann,Viola;Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany Muñoz,Miguel A.;Departamento de Electromagnetismo y Física de la Materia, Universidad de Granada, Granada, Spain Zierenberg,Johannes;Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany Soriano,Jordi;Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain
Description	In this data repository, we provide raw data and intermediate analysis results accompanying our publication. Files are compressed zip-archives, downloadable separately in order to reproduce expiermental results and simulations independently. The preliminary publication title is "Modular architecture facilitates noise-driven control of synchrony in neuronal networks". A preprint can be found at https://arxiv.org/abs/2205.10563. The accompanying code repository can be found at https://github.com/Priesemann-Group/stimulating_modular_cultures.
License	CC-BY-NC 4.0 (http://creativecommons.org/licenses/by-nc/4.0/)
References	Yamamoto et al.: 'Modular architecture facilitates noise-driven control of synchrony in neuronal networks'. Science Advances, submitted. [doi:tba] (IsSupplementTo) Yamamoto et al. (2022) Preprint of 'Modular architecture facilitates noise-driven control of synchrony in neuronal networks' based on the data. arXiv. https://doi.org/10.48550/arXiv.2205.10563 [arXiv:2205.10563] (IsSupplementTo) StimulatingModularCultures: Analysis code. Github. https://github.com/Priesemann-Group/stimulating_modular_cultures [url:https://github.com/Priesemann-Group/stimulating_modular_cultures] (IsReferencedBy)
Funding
Keywords	Neuroscience in vitro cultures modularity optogenetics spiking neuronal network model
Resource Type	Dataset

README.md

Movies of simulations