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License for Use:
- Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0) 
- https://creativecommons.org/licenses/by-nc-nd/4.0/

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System Requirements:
- MATLAB - Software has been tested on version R2020b
- MATLAB Parallel Computing Toolbox
- MATLAB Communications Toolbox
- Chronux MATLAB package (v2.12) - Scripts provided in this package in the Chronux folder within the Supporting Functions folder. Scripts originally downloaded from http://chronux.org/

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Installation Guide: 
- Download MATLAB and all required Toolboxes
- Download the 'Repository data and code' folder, it should only take a few seconds on a typical computer
- Add the repository folder to the MATLAB path, ensuring to include all sub-folders

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Demo: 
- Open the 'Demo.m' script to run the demo
- The Demo function shows how to run the model using a single stimulation pattern, and how to run the model using the stimulation frequency sweep used in the paper
- The Demo function then shows an example of how to plot the resulting data
- The expected run time is approximately 5 minutes on a typical computer per stimulation pattern tested. However, the model is designed to work with the Parallel Computing Toolbox, so computers with multiple processors can run multiple stimulation patterns simultaneously.

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Instructions for Use:
The primary MATLAB functions to run the model are 'Run_Model', 'Soma_Model', 'Axon_Model', and 'Synapse_Model'. Additional supporting functions included in the Supporting Functions folder.

'Run_Model': 
- The primary function that runs the whole model based on an input of different stimulation patterns. It runs the Soma_Model, then Axon_Model, then Synapse_Model, and then quantifies different metrics of synchronicity with the resulting population conductances. 
- It requires an input struct with stimulation patterns. The two pattern sets used in the model are 'Patterns_to_Score-Sweep' and 'Patterns_to_Score-CV'. 
- To get started, load one of the 'Patterns_to_Score' files, then run Run_Model(Patterns,osc_freq), with osc_freq being the selected beta band oscillation frequency for that model run. 

'Soma_Model': Creates intrinsic spiking for the somas

'Axon_Model': Adds DBS pulses according to the input patterns, then models collision, refractory periods, and antidromic spike failure. 

'Synapse_Model': Takes the output of the Axon_Model and models synaptic vesicle release. It outputs the population conductance. 

Model_Results:
- The model results are given in the same format as the 'Patterns_to_Score' files, but with the Scores field filled in. 
- The results for the stimulation frequency sweep are 'Patterns_Scored-Sweep', and the results for the CV sweep are 'Patterns_Scored-CV'
- Within the results structures, the model scores are held in the Scores field, which is a cell array with each stimulation pattern having its own cell. Each cell then contains an array with each row indicating a different model output and each column indicating the results from an individual model run.
- The legend for what each row represents in the Scores field is kept in the Labels field. Each Labels refer to two terms, the model output and the model version. Details for each are below:
- The model outputs are:
	Coh = beta band coherence between group activated by DBS and group not activated
	Cross Beta = beta band cross power between group activated by DBS and group not activated
	Phase = beta band phase difference between group activated by DBS and group not activated
	Beta = beta band power of group activated by DBS
	cEP = antidromic spike success rate 
	Act = somatic spikes per second
	Spike Rate = collateral synapse spikes per second
- The model versions are:
	No = antidromic spike failure at the soma and static vesicle release
	Syn = antidromic spike failure at the soma and stochastic vesicle release
	Axon = antidromic spike failure at the STN branch point and static vesicle release
	Both = antidromic spike failure at the STN branch point and stochastic vesicle release
	Hillock = antidromic spike failure at the soma (this output is not dependent on the synapse)
	Low = antidromic spike failure at the STN branch point (this output is not dependent on the synapse)
- Additionally, the first row gives the average stimulation frequency of the pattern, and the second row gives the beta band oscillation frequency selected for that column's run