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Adaptive dual control of deep brain stimulation in Parkinsons disease simulations (Grado et al 2018)
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Model Information
Model File
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
]
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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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COMMIT_EDITMSG
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description
*
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HEAD
*
Other models using HEAD:
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Current Dipole in Laminar Neocortex (Lee et al. 2013)
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Optimal synaptic assignment for locomotory behavior in C. elegans (Rakowski & Karbowski 2017)
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Recurrent amplification of grid-cell activity (D'Albis and Kempter 2020)
Robust transmission in the inhibitory Purkinje Cell to Cerebellar Nuclei pathway (Abbasi et al 2017)
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