MEA Tools

Tools for viewing, analyzing, and processing multi-electrode array data.

MEA Tools consists of three main components: (1) a Python module (pymea) and command line script for interacting with multi-electrode recordings, (2) a Python GUI application for high performance visualization of raw analog recordings and spike raster data, and (3) a Mathematica library for manipulating and analyzing analog and spike data.

Requirements

MEA Tools requires:

Python 3.4
vispy (best to install this from source due to its rapid development)
PyQt4
numpy
scipy
pandas
PyOpenGL

Typically it is easiest to install Anaconda Python 3.4 to obtain these packages.

Installation

Clone to a suitable directory:

cd ~
git clone https://github.com/dbridges/mea-tools.git

Add the following to your shell startup file (~/.bash_profile on Mac or ~/.bashrc on Linux):

alias mea='python3 ~/mea-tools/mea-runner.py'
export PYTHONPATH=$PYTHONPATH:$HOME/mea-tools

PyMEA

The core of the package is a Python 3 module, PyMEA, which has many components for interacting with data acquired by MultiChannel Systems software. Data files must be converted to HDF5 files using MultiChannel Systems Data Manager before they can be viewed or analyzed with PyMEA.

MEA Script Commands

view

Open a data file for viewing in the MEA Viewer application. MEA Viewer displays analog and spike data in an interactive application. Input data files should have a *.h5 or *.csv file extension. All csv files should be built with the detect command listed below.

Interactively view an analog file:

mea view 2015-03-20_I9119.h5

or show an interactive raster plot of spike data:

mea view 2015-03-20_I9119.h5

info

Display information about an analog recording.

$ mea info 2014-10-30_I9119_Stimulate_D3.h5

File:           2014-10-30_I9119_Stimulate_D3.h5
Date:           Thu, 30 Oct 2014 02:36:35 PM
MEA:            120MEA200/30iR
Sample Rate:    20000.0 Hz
Duration:       19.00 s

detect

Find spikes in input files and export their timestamps to a csv file. Output files have the same filename as the input file, but with a .csv extension.

Export one file:

mea detect 2015-03-20_I9119.h5

Export all files in directory:

mea detect *.h5

Export a file using a threshold cutoff of 5 times the standard deviation of the input file noise:

mea detect --amplitude=5 2015-03-20_I9119.h5

Mathematica Tools

A Mathematica library is also included to analyze analog and spike data, as well as to create useful static visualizations. See mathematica/MEA_Examples.nb for more information.

wukoe/mea-tools