Adaptive dual control of deep brain stimulation in Parkinsons disease simulations (Grado et al 2018)

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Accession:247310

Reference:
1 . Grado LL, Johnson MD, Netoff TI (2018) Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson's disease. PLoS Comput Biol 14:e1006606 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neural mass;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Python;
Model Concept(s): Parkinson's;
Implementer(s):
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MFM_BayesADC_ModelDB
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Initial commit for ModelDB

# Please enter the commit message for your changes. Lines starting
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# Date:      Mon Nov 26 15:02:11 2018 -0600
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# On branch master
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# Initial commit
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# Changes to be committed:
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#	new file:   dbs.py
#	new file:   fig_3.py
#	new file:   mfm.py
#	new file:   plot.py
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#	new file:   utils.py
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