We developed a computational model of the cortical basal ganglia network to investigate closed-loop control of deep brain stimulation (DBS) for Parkinson’s disease (PD). The cortical basal ganglia network model incorporates the (i) the extracellular DBS electric field, (ii) antidromic and orthodromic activation of STN afferent fibers, (iii) the LFP detected at non-stimulating contacts on the DBS electrode and (iv) temporal variation of network beta-band activity within the thalamo-cortico-basal ganglia loop. The model facilitates investigation of clinically-viable closed-loop DBS control approaches, modulating either DBS amplitude or frequency, using an LFP derived measure of network beta-activity.
Model Type: Realistic Network; Extracellular; Axon
Region(s) or Organism(s): Basal ganglia; Neocortex
Cell Type(s): Hodgkin-Huxley neuron
Currents: I K; I Sodium; I Calcium; I_AHP; I L high threshold; I T low threshold
Model Concept(s): Deep brain stimulation; Parkinson's; Beta oscillations; Activity Patterns; Extracellular Fields
Simulation Environment: NEURON; Python; PyNN
Implementer(s): Fleming, John E
References:
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