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DeePhys was created to facilitate the analysis of extracellular recordings of neuronal cultures using high-density microelectrode arrays (HD-MEAs)

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Welcome to DeePhys

The package for Deep electrophysiological phenotype characterization:

Analysis schematic

Created with BioRender

Overview

DeePhys was created to facilitate the analysis of extracellular recordings of neuronal cultures using high-density microelectrode arrays (HD-MEAs). DeePhys allows users to easily:

  • Extract electrophysiological features from spikesorted HD-MEA recordings
  • Visualize differential developmental trajectories
  • Apply machine learning algorithms to classify different conditions
  • Obtain biomarkers predictive of the respective condition
  • Evaluate the effect of treatments
  • Dissect heterogeneous cell populations/cultures on the single-cell level

Requirements

Currently DeePhys is only available on MATLAB, so a recent MATLAB installation (>2019b) is required. We plan on expanding DeePhys to Python in the near future.

Installation

The package is ready-to-use right after cloning.

Usage

Code requires spikesorted data in the phy format. For help with spikesorting check out the Spikeinterface package.

The analysis pipeline is subdivided into the following modules (links to the tutorials):

Citation

The DeePhys package was first published on bioRxiv, but was since heavily updated and is no longer compatible to the prior version.

Disclaimer

This package uses several packages/toolboxes:

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DeePhys was created to facilitate the analysis of extracellular recordings of neuronal cultures using high-density microelectrode arrays (HD-MEAs)

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