NetBurstDynamics

Fitting a simplified population bursting model to neural data. Code for Vinogradov et al. 2024.

The repository to reroduce the analysis and visualizations from

"Effective excitability captures network dynamics across development and phenotypes" Vinogradov et al., 2024

Installation

Clone the repository

pip clone https://github.com/LevinaLab/NetBurstDynamics.git

Making a new conda environment and installing the dependencies with conda

env create --name NetBurstDynamics --file dependencies.yml

install the code in you local environment as

pip install -e . 

Workflow

• Exploring the model dynamics
• Data processing and burst detection
• Model fitting
• Visualization

The project is being update to ensure compatibility.

Project structure

• data/
• src/
• trained/
• scripts/
  • Figures/
  • DataProcessing/

Data folder should be populated from figshare directory and data contains spikes from 24-well MEA recorded at DIV Figshare

Citation

@article{vinogradov2024effective,
  title={Effective excitability captures network dynamics across development and phenotypes},
  author={Vinogradov, Oleg and Giannakakis, Emmanouil and Buendia, Victor and Uysal, Betuel and Ron, Shlomo and Weinreb, Eyal and Schwarz, Niklas and Lerche, Holger and Moses, Elisha and Levina, Anna},
  journal={bioRxiv},
  pages={2024--08},
  year={2024},
  publisher={Cold Spring Harbor Laboratory}
}

Liscence for the code

Apache 2.0