pSpitzner 7c0c848720 gin commit from vigsoe 1 anno fa
..
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

README.md

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