Failure of Deep Brain Stimulation in a basal ganglia neuronal network model (Dovzhenok et al. 2013)

 Download zip file 
Help downloading and running models
Accession:148637
"… Recently, a lot of interest has been devoted to desynchronizing delayed feedback deep brain stimulation (DBS). ... This study explores the action of delayed feedback stimulation on partially synchronized oscillatory dynamics, similar to what one observes experimentally in parkinsonian patients. …" Implemented by Andrey Dovzhenok, to whom questions should be addressed.
Reference:
1 . Dovzhenok A, Park C, Worth RM, Rubchinsky LL (2013) Failure of delayed feedback deep brain stimulation for intermittent pathological synchronization in Parkinson's disease. PLoS One 8:e58264 [PubMed]
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): Subthalamus nucleus projection neuron; Globus pallidus neuron;
Channel(s): I Na,t; I T low threshold; I K; I_AHP; I Ca,p;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: XPP; MATLAB;
Model Concept(s): Synchronization; Parkinson's; Deep brain stimulation;
Implementer(s): Dovzhenok, Andrey [andrey.dovzhenok at uc.edu];
Search NeuronDB for information about:  I Na,t; I T low threshold; I K; I_AHP; I Ca,p;
function [sign_eigenval]=Sign_subset

%uses PCA analysis to find the # of significant eigenvalues among those 
%computed via PCAgenerator.m

%we would use 80% threshold to choose the significant subset of eigenvalues

load PCA_eigenval_w0.3.mat
S = 0;
M = 0;
sign_eigenval = zeros(31,10,5);
for i = 1:31
    for j = 1:10
       for k = 1:5
            if size(pca_eigenval{i,j,k}) ~= 0
                n = 10;
                S = sum(pca_eigenval{i,j,k});
                M = pca_eigenval{i,j,k}(n);
              while n >= 1
               n = n - 1;
               if M > 0.8*S
                   sign_eigenval(i,j,k) = 10 - n;
                   n = 0;
               else M = M + pca_eigenval{i,j,k}(n);
               end                 
              end
            else
            sign_eigenval(i,j,k) = 0;
            end
       end
    end
end
save('Sign_eig_w0.3.mat','sign_eigenval')

%Don't use Choongseok data
%format = '%*f32%*f32%f32';
%fid = fopen('pca_number.dat', 'r');
%pca_number = textscan(fid, format);
%fclose(fid);

x1_ix = 0;

for iapp = 4:8
  x1_ix=x1_ix+1;
  x2_ix = 0;
  for gsyn = .5:.1:1.4
    x2_ix=x2_ix+1;
    x3_ix = 0;
    for Kn = 0:2:60
        x3_ix=x3_ix+1;
        %use our own eigenvalues with Cn=0 as a baseline      
        ii = sign_eigenval(x3_ix,x2_ix,x1_ix)-sign_eigenval(1,x2_ix,x1_ix);
            
            if ii <= -2
                color='k';
            elseif ii == -1
                color='r';
            elseif ii == 0 
                color='w';
            elseif ii == 1
                color='b';
            elseif ii ==2
                color='y';
            elseif ii >= 3
                color='g';
            end
                   
           scatter(gsyn,Kn,50,color,'filled')
           hold on
   end
 end
    
val='# of PCA components with stim - without stim';
xlabel('gsyn');ylabel('Kn');
title(strcat(val,': <=2 blk, -1 r, 0 w, 1 b, 2 y, >=3 g'))
fOut2 = sprintf('diffgsynKnplane_w0.3_%s%1.1f.fig','Iapp',iapp);
hgsave(fOut2);

end

end



Loading data, please wait...