PyMUS: A Python based Motor Unit Simulator (Kim & Kim 2018)

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Accession:239535
PyMUS is a simulation software that allows for integrative investigations on the input-output processing of the motor unit system in a hierarchical manner from a single channel to the entire system behavior. Using PyMUS, a single motoneuron, muscle unit and motor unit can be separately simulated under a wide range of experimental input protocols.
Reference:
1 . Kim H, Kim M (2018) PyMUS: Python-Based Simulation Software for Virtual Experiments on Motor Unit System. Front Neuroinform 12:15 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Spinal cord lumbar motor neuron alpha ACh cell; Skeletal muscle cell;
Channel(s): I Calcium; I h; I Potassium; I Sodium; I_AHP;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Python;
Model Concept(s): Motor control;
Implementer(s): Kim, Hojeong [hojeong.kim03 at gmail.com]; Kim, Minjung [reddkwl at gmail.com];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha ACh cell; I h; I Sodium; I Calcium; I Potassium; I_AHP;
1. Execution
PyMUS v2.0 is optimized for Windows 7 and 8.1. The Main Window of PyMUS v2.0 can be launched by running "GUI.py".

2. Dependencies
- Python (ver 2.7)
- Pandas (ver 0.15.2)
- Numpy (ver 1.9.2)
- Scipy (ver 0.15.1)
- Matplotlib (ver 1.4.3)
- PyQt4 (ver 4.10.4)

3. Software Usage
PyMUS v2.0 allows the simulations to be fully operated using a graphical user interface (GUI). The GUI was designed to allow for a generic computational procedure to be performed using modeling and simulation approaches. The Main Window of PyMUS v2.0 consists of one state window and six buttons for controlling simulation of motor unit system. A typical procedure for use of the PyMUS v2.0 is as follows:

[STEP 1] Model Selection
 - Using "Please Select!" drop-down menu, the target model to be simulated is chosen among the motoneuron, muscle unit and motor unit models.
 - The message on the result of STEP1 appears on the state window.

[STEP 2] Parameter Setting
 - Using "Model Parameter Settings" button, the Model Parameters window is popped up to provide the GUI interfaces for setting the model parameter values manually or automatically by importing pre-determined data into the software.
 - When "OK" or "Apply" button is pushed, STEP2 is completed along with the result message on the state window. 

[STEP 3] Simulation Setting
  - Using "Simulation Condition Settings" button, the Simulation Conditions window is generated to provide the GUI interfaces for setting the simulation time, display quality (sample time and plotting interval) and initial values of the model equations. 
  - When "OK" or "Apply" button is pushed, STEP3 is completed along with the result message on the state window.

[STEP 4] Input Setting
  - Using "Input Signal Settings" button, the Input Signals window is produced to allow the type and protocol for injecting the input signals into the model to be selected.
  - When "Generate" button is pushed, input signal data is produced and displayed on a separate figure window along with the result message on the state window. 
  - When "OK" or "Apply" button is pushed, STEP4 is completed along with the result message on the state window.

[STEP 5] Output Setting
- Using "Output Signal Settings" button, the Output Signals window is popped up to enable the output variables to be displayed and plotting options to be selected.
- To efficiently compare the multiple output variables simultaneously, PyMUS v2.0 allows for the output variables to be selected in the Output Signals window and displays these variables either individually on separate panels or together on the same panel.
 - When "OK" or "Apply" button is pushed, STEP5 is completed along with the result message on the state window. 

[STEP6] Run control
  - Using "Run" button, the simulation can be started or stopped.
  - The messages on the result of STEP6 are displayed on the state window.

STEP2-STEP6 can mutually transition among each other maintaining all changes made in each step unless the target model is changed through STEP1. To support offline analyses, the simulation data including simulation time and all output variables in the Output Signals window are also saved in a separate file.



Please see the paper for example usages of PyMUS ver 2.0 and the source code and executable file for the current version of PyMUS can also be found in "https://github.com/NMSL-DGIST/PyMUS".

Hojeong Kim
Convergence Research Institute
DGIST
Daegu Korea
hojeong.kim03@gmail.com

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