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Identifying Network State from Extracellular Recordings during Wakefulness in Neocortex

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Network State Index (NSI)

Identifying Network State from Extracellular Recordings during Wakefulness in Neocortex

This module provides a quantitative characterization of network states in neocortex from extracellular signals. It implements the analysis described in the following article (please cite if you use this code !):

Network States Classification based on Local Field Potential Recordings in the Awake Mouse Neocortex Yann Zerlaut, Stefano Zucca, Tommaso Fellin, Stefano Panzeri bioRxiv 2022.02.08.479568; doi: https://doi.org/10.1101/2022.02.08.479568


GUI Screenshot

screenshot


Installation

  1. Install a python distribution for scientific analysis:

    get the latest Miniconda distribution and install it on your home folder.

  2. Run the following in the Anaconda prompt:

git clone https://github.com/yzerlaut/Network_State_Index.gitb
cd Network_State_Index
pip install .

If you do not wish to clone the repository you can also directly:

pip install git+https://github.com/yzerlaut/Network_State_Index

Usage

  • Run the software GUI
python -m NSI
  • Using the notebook implmentation
jupyter notebook notebook_demo.ipynb

GUI features

Load data:

Electrophysiological data supported
  • Axon Instruments (pClamp) ".abf" format

  • HDF5 ".h5" format

  • Numpy storing formats (".npz" storing a dictionary)

You can set the desired channel to analyze and the gain that should be applied (only if you want it in uV)

Run analysis:

It computes the NSI measure over the whole data. It can be a bit long if the data are large.

Visualize the data and the output of the NSI analysis

In the top 3 plots, we show the full (subsampled) data.

In the bottom 3 plots, we show a zoomed (subsampled) portion of the data. Highlighted with a red filled rectangle in the top plot.

Zoom :

  • Zoom1: When clicking on this button, you can select a time window in the top plot
  • Zoom2: When clicking on this button, you can select a time window in the bottom-Vext plot

Save the output of the analysis:

The output is stored as an hdf5 datafile. It containes the sample times of validated network states and their associated NSI level.

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Identifying Network State from Extracellular Recordings during Wakefulness in Neocortex

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