Striatal NN model of MSNs and FSIs investigated effects of dopamine depletion (Damodaran et al 2015)

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Accession:169984
This study investigates the mechanisms that are affected in the striatal network after dopamine depletion and identifies potential therapeutic targets to restore normal activity.
Reference:
1 . Damodaran S, Cressman JR, Jedrzejewski-Szmek Z, Blackwell KT (2015) Desynchronization of Fast-Spiking Interneurons Reduces beta-Band Oscillations and Imbalance in Firing in the Dopamine-Depleted Striatum. J Neurosci 35:1149-59 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Axon; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neostriatum medium spiny direct pathway neuron; Neostriatum medium spiny indirect pathway neuron; Neostriatum fast spiking interneuron;
Channel(s): I Sodium; I Potassium; Kir;
Gap Junctions: Gap junctions;
Receptor(s): D1; D2; GabaA; Glutamate;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Synchronization; Detailed Neuronal Models; Parkinson's;
Implementer(s): Damodaran, Sriraman [dsriraman at gmail.com];
Search NeuronDB for information about:  Neostriatum medium spiny direct pathway neuron; Neostriatum medium spiny indirect pathway neuron; D1; D2; GabaA; Glutamate; I Sodium; I Potassium; Kir; Gaba; Glutamate;
[nid_spk,t_spk] = textread('SPcell.spikes', '%d    %f'      );
t_count=1;
t_hist=0:0.025:0.25;
for w=1:(length(t_hist)-1)
    for i=1:max(nid_spk)
        count=0;
        for j=1:length(nid_spk)
            if (t_spk(j)>t_hist(w) & t_spk(j)<t_hist(w+1))
                if (nid_spk(j)==i)
                count=count+1;
                spikes(t_count,i) = count;
                else     
                end
%             elseif (t_spk(j)>t_hist(w) & t_spk(j)>t_hist(w+1))
%                 if (nid_spk(j)==i)
%                 count=0;
%                 spikes(t_count,i) = count;
%                 else
%                 end
            end
        end
    end
t_count=t_count+1;
end

t_hist1=0.5:0.025:0.75;
for w=1:(length(t_hist1)-1)
    for i=1:max(nid_spk)
        count=0;
        for j=1:length(nid_spk)
            if (t_spk(j)>t_hist1(w) & t_spk(j)<t_hist1(w+1))
                if (nid_spk(j)==i)
                count=count+1;
                spikes(t_count,i) = count;
                else     
                end
%             elseif (t_spk(j)>t_hist1(w) & t_spk(j)>t_hist1(w+1))
%                 if (nid_spk(j)==i)
%                 count=0;
%                 spikes(t_count,i) = count;
%                 else 
%                 end
            end
        end
    end
t_count=t_count+1;
end
for i=1:(t_count-2)
temp_m=spikes(i,:);    
mean_spk(i)=mean(temp_m);
std_spk(i)=std(temp_m);
end
x=[0.125,0.175,0.225,0.6,0.65,0.7,0.75];
latency=min(t_spk)

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