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Data analysis tools
A variety of tools are needed for accurate interpretation of the electrical signals collected using the Myomatrix arrays. As well, evaluation of how the nervous system executes complex motor patterns requires integration of neural, motor and behavioral analyses. The list below is not exhaustive, yet represents a well-vetted list of of tools, including channel maps to popular data acquisition system interfaces, data sets with sample Matlab code, and links to open-source platforms for spike sorting and behavioral analysis.
Pinout maps
This PDF has the channel maps for the 1-threaded, 4-threaded and 8-threaded Myomatrix devices mapped to Intan headstages and then to Intan RHX software or the Open EPhys GUI.
EMUsort
This Github repository links to an open-source spike sorter built specifically for discriminating motor unit action potentials. A fuller description of the advantages of EMUsort for motor unit data and other technical details can be found HERE (courtesy of Sean O'Connell and Chethan Pandarinath, PhD; Emory University).
Data analysis example
Example data and simple MATLAB code for visualizing EMG data recorded with a Myomatrix array. Data are from an acute recording of an orofacial (digastric) muscle in an anesthetized mouse (see Fig. 6 in Lu et al., 2022).
Spike Interface
SpikeInterface is a Python module to analyze extracellular electrophysiology data.
With a few lines of code, SpikeInterface enables you to load and pre-process the recording, run several state-of-the-art spike sorters, post-process and curate the output, compute quality metrics, and visualize the results. (N.B.: the description is from SI website, accessed Jan. 2025).
With a few lines of code, SpikeInterface enables you to load and pre-process the recording, run several state-of-the-art spike sorters, post-process and curate the output, compute quality metrics, and visualize the results. (N.B.: the description is from SI website, accessed Jan. 2025).
Behavioral tracking
SLEAP is an open source deep-learning based framework for multi-animal pose tracking (Pereira et al., Nature Methods, 2022). DeepLabCut is a markerless pose estimation of user-defined features with deep learning for all animals including humans. (N.B.: the descriptions are from Pereira et al. and DLC website, accessed Jan. 2025).
Bonsai
Bonsai is a visual language for reactive programming. It is lightweight and easy to use with a variety of packages and modules for interfacing with hardware and for real-time processing and manipulation of data streams (N.B.: the description is from Bonsai website, accessed Jan 2025).