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 spiny direct pathway neuron; Neostriatum 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 spiny direct pathway neuron; Neostriatum spiny indirect pathway neuron; D1; D2; GabaA; Glutamate; I Sodium; I Potassium; Kir; Gaba; Glutamate;
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DamodaranEtAl2015
Matlab_files
Inputwithcorrelation.asv *
Inputwithcorrelation.m *
InputwithCorrelation2.m *
makeDaughterInput.m *
makeDaughterInsignal.m *
makeTrainInput.m *
makeTrainInsignal.m *
poissonMaxTime.m *
writeInput.asv *
writeInput.m *
                            
%
% Generates input for each cell with Nampa(nSyn)columns and rows proportional to freq*maxTime
% nSyn in the number of synapses
% corr_syn is the correlation between the synapses

function noise = makeDaughterInput(corr_syn, nSyn, freq, maxTime)

	nShare = nSyn - sqrt(corr_syn)*(nSyn-1);
	pShare = 1/nShare;
  
	motherSpikes = poissonMaxTime(freq*nShare, maxTime);
  
	len = length(motherSpikes); % # rows of final array

	v = (rand(len, nSyn) < pShare).*repmat(motherSpikes,1,nSyn); %0 indicates don't assign spikes and 1 assigns
	v(find(v == 0)) = inf;
	v = sort(v,1); % sorts each column in ascending order (2nd argument is ascending or descending)
	vlen = 1+max(mod(find(v < inf) - 1, len));
	v(find(v == inf)) = 0;
	noise = v(1:vlen,:);
  

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