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<p>Network model of the cortico-basal ganglia network with closed-loop DBS to test closed-loop DBS control strategies.
</p>
<p>This is the readme for the models associated with the paper:<p/>
Fleming JE, Dunn E, Lowery MM (2020) Simulation of Closed-Loop Deep
Brain Stimulation Control Schemes for Suppression of Pathological
Beta Oscillations in Parkinson's Disease. Frontiers in Neuroscience
14:166<br/>
<a href="http://dx.doi.org/10.3389/fnins.2020.00166">http://dx.doi.org/10.3389/fnins.2020.00166</a><p/>
</p>
<p>The model files were contributed by JE Fleming
</p>
<p>Model Requirements: - Model is simulated using PyNN with NEURON as
it's backend simulator, thus follow their installation instructions
at:
<ol>
<li> Neuron - <a href="https://www.neuron.yale.edu/neuron/download">https://www.neuron.yale.edu/neuron/download</a>
</li><li> PyNN -
<a href="https://pypi.org/project/PyNN/">https://pypi.org/project/PyNN/</a> - <a href="http://neuralensemble.org/docs/PyNN/">http://neuralensemble.org/docs/PyNN/</a>
</li></ol>
</p>
<p>Model Setup:
</p>
<ol>
<li>Copy the included PyNN files from the downloaded model folder to
their corresponding location on your computer (i.e. the directory of
your PyNN instatllation - Updated PyNN files are needed for correct
simulation of the multicompartmental cortical neurons and for loading
model simulations from a presimulated steady state.
</li><li>Compile the NEURON model mod files using either mknrndll or
nrnivmodl, for windows or Linux, respectively.
</li><li>Run run_CBG_Model_to_SS.py
<dl>
<dt>Example</dt>
<dd>
</dd></dl>
</li><li>From the command line/terminal navigate to the folder containing
the model.
</li><li>Execute "python run_CBG_Model_to_SS.py neuron"
<dl>
<dt>Explanation</dt>
<dd>
</dd></dl>
</li></ol>
<p>There is an initial transient period in the model (~6 seconds). This
model simulation runs the model for the transient period and
creates a binary file (steady_state.bin) at the end of the
simulation. This binary file captures the state of the model at
the end of this transient simulation (i.e. after the model has
reasched the steady state)
</p>
<p>Subsequent runs of the model can use either
</p><p> run_CBG_Model_Amplitude_Modulation_Controller.py or
run_CBG_Model_Frequency_Modulation_Controller.py to load the
previously saved model steady state and run a model simulation
from this point simulating either amplitude or frequency
modeulation, respectively.
</p>
<p>Running the Model: - Once the steady state of the model has been saved
you can run the model by navigating to the model directory in the
command line and typing:
</p>
<p>"python run_CBG_Model_Amplitude_Modulation_Controller.py neuron"
</p>
<p>Output files of the simulation are then written to a
"Simulation_Output_Results" folder when the simulation is finished.
Model outputs are structured using the neo file format as detailed in
<a href="https://neo.readthedocs.io/en/stable/.">https://neo.readthedocs.io/en/stable/.</a></p>
</html>