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Data-driven burst shape analysis for functional phenotyping of neuronal cultures

corresponding to Schäfer et al., 2025, bioRxiv: Data-driven burst shape analysis for functional phenotyping of neuronal cultures

@article{schaefer2025data-driven,
	author = {Sch{\"a}fer, Tim J. and Giannakakis, Emmanouil and Schmidt-Barbo, Paul and Levina, Anna and Vinogradov, Oleg},
	title = {Data-driven burst shape analysis for functional phenotyping of neuronal cultures},
	year = {2025},
	doi = {10.1101/2025.09.29.679256},
	journal = {bioRxiv},
}

Tutorial

notebooks/tutorial.ipynb walks you through the basic pipeline step-by-step.

Online tools

You can also try out the analysis pipeline without installing anything using the following online tools.

Burst visualization

Try burst visualization (10s loading time)! This is used to visualize all recordings and for adjusting burst detection hyperparameters.

Embedding visualization

Try embedding visualization (10s loading time)! This is used for visualizing the spectral embedding (of individual burst shapes) and exploring this burst shape space.

Links for other datasets

Setup

Installation

[Optional] Create a conda environment named burst-shape and python=3.11 with

conda create -n burst-shape python=3.11

Activate the environment with

conda activate burst-shape

Install src module with

pip install -e .

which will run setup.py, making the src module available.

[Optional] If this fails to install the dependencies, you can install them manually with

pip install -r requirements.txt

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Data-driven burst shape analysis for functional phenotyping of neuronal cultures

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