Optimal deep brain stimulation of the subthalamic nucleus-a computational study (Feng et al. 2007)

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Accession:93449
Here, we use a biophysically-based model of spiking cells in the basal ganglia (Terman et al., Journal of Neuroscience, 22, 2963-2976, 2002; Rubin and Terman, Journal of Computational Neuroscience, 16, 211-235, 2004) to provide computational evidence that alternative temporal patterns of DBS inputs might be equally effective as the standard high-frequency waveforms, but require lower amplitudes. Within this model, DBS performance is assessed in two ways. First, we determine the extent to which DBS causes Gpi (globus pallidus pars interna) synaptic outputs, which are burstlike and synchronized in the unstimulated Parkinsonian state, to cease their pathological modulation of simulated thalamocortical cells. Second, we evaluate how DBS affects the GPi cells' auto- and cross-correlograms.
Reference:
1 . Terman D, Rubin JE, Yew AC, Wilson CJ (2002) Activity patterns in a model for the subthalamopallidal network of the basal ganglia. J Neurosci 22:2963-76 [PubMed]
2 . Rubin JE, Terman D (2004) High frequency stimulation of the subthalamic nucleus eliminates pathological thalamic rhythmicity in a computational model. J Comput Neurosci 16:211-35 [PubMed]
3 . Feng XJ, Shea-Brown E, Greenwald B, Kosut R, Rabitz H (2007) Optimal deep brain stimulation of the subthalamic nucleus--a computational study. J Comput Neurosci 23:265-82 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Basal ganglia;
Cell Type(s): Globus pallidus neuron;
Channel(s): I T low threshold; I Sodium; I Potassium;
Gap Junctions:
Receptor(s): Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: C or C++ program;
Model Concept(s): Parkinson's; Deep brain stimulation;
Implementer(s): Feng, Xiao-Jiang [xfeng at mahler.princeton.edu];
Search NeuronDB for information about:  Glutamate; Gaba; I T low threshold; I Sodium; I Potassium; Gaba; Glutamate;
//GA parameters
#define PI 3.1415926
#define POPSIZE 25 //control population size, excluding master
#define MAXGEN 200 //maximum generations for control GA
#define NCTRL 12 //total no. of controls (10 PDF, 1 width, 1 amplitude)
#define NSAVED 3 //best gene saved in each generation (elitism)
#define NUSED 20 //no. of gene templates used for crossover and mutation
#define NMUT 10 //number of mutations
#define PMUT 2 //no. of mutation points

//current input boundaries
#define CTRL_L 0 //lower control limit
#define CTRL_H 50 //high control limit
#define CTRL_S 1 //control step size
#define DUR_L 1 //duration low
#define DUR_H 100 //duration high
#define DUR_S 1 //duration step
#define AMP_L 10 //amplitude low
#define AMP_H 100 //amplitude high
#define AMP_S 10 //amplitude step

void popInitializer( int [][NCTRL] ); //random current generator
int randGen( int, int, int ); //random number generator
void piksr2( int, double [], int [][NCTRL] ); //sorting
void crossOver( int [][NCTRL] ); //crossover
void muTation( int [][NCTRL] ); //mutation