cureq 1.2.10

Library for analyzing MEA files.

This project is still in development.

CureQ

This is the repository of the CureQ consortium.
For more information about the CureQ project, visit https://cureq.nl/ This repository contains a library with functions for analyzing Microelectrode Array (MEA) experiments.
This repository is maintained by the Amsterdam University of Applied Sciences (AUMC).
This library can process both Multi Channel Systems and Axion Biosystems MEA data, although the latter will have to be converted to hdf5 format using our MATLAB script, which can be found in the repository. For more information about the analysis or how to use the library, check out the "CureQ MEA-analysis library User Guide.pdf" file.

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Install the library

First, make sure you have installed a version of python on your machine, all python releases can be found here: https://www.python.org/downloads/
Secondly, make sure you have installed a package manager, like pip or conda.
Next, open a terminal and navigate to your home folder.

Install library with pip

Install the MEA analyzer with the following command when you are using Pip:

pip install CureQ 

Install library with conda

Install the MEA analyzer with the following command when you are using Conda:

conda install CureQ::CureQ

More elaborate and simple installation instructions can be found in the user guide.

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Library usage

Now you can try the CureQ library functions in your Python environment.
Import the function you need, call this function and watch how the pipeline analyzes your MEA file!

Example for analyzing all MEA wells

from CureQ.mea import analyse_wells, get_default_parameters

fileadress='C:/mea_data/mea_experiment.h5'
sampling_rate=20000
electrode_amount=12

# Get and edit parameters
parameters = get_default_parameters()
parameters['use multiprocessing'] = True

if __name__ == '__main__':
    analyse_wells(fileadress=fileadress,
                  sampling_rate=sampling_rate,
                  electrode_amnt=electrode_amount,
                  parameters=parameters
                  )

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MEA GUI

Addionally, the CureQ mea library contains a graphical user interface that can be used to perform the analysis.
The GUI is also used to inspect the raw MEA data and the analysis results. Example visualisations can be found below.
The GUI can be opened as follows:

Opening the GUI

from CureQ.mea_analysis_tool import MEA_GUI

if __name__=="__main__":
    MEA_GUI()

Launch from command prompt

Additionally, he GUI can be launched from the command prompt. Simply open the command prompt, and enter “cureq”.

C:\Users>cureq
Successfully launched MEA GUI

The output should look like this, and the GUI should appear on your screen.

Create shortcuts

This process can be simplified by creating shortcuts that in essence perform the same process. In the command prompt, enter “cureq –create-shortcut”.

C:\Users>cureq --create-shortcut
Desktop shortcut created at C:\Users\Desktop\CureQ.lnk

The output should look like this, and a shortcut should appear on your desktop:

Additionally a shortcut can be added to the start menu. In the command prompt, enter “cureq –add-to-start-menu”.

C:\Users>cureq --add-to-start-menu
Start Menu shortcut created at C:\Users \AppData\Roaming\Microsoft\Windows\Start Menu\Programs\CureQ\CureQ.lnk

The output should look likes this, and the shortcut should appear in your start menu. The shortcut can also be added to the taskbar by pressing “Pin to taskbar”.

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Example visualisations

Spike detection

Single channel burst detection

Network burst detection

Batch processing

Group comparison