Excitotoxic loss of dopaminergic cells in PD (Muddapu et al 2019)

 Download zip file 
Help downloading and running models
Accession:244384
"... A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD (Parkinson's disease) therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc (Substantia Nigra pars compacta) cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in ‘stress’ variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model."
Reference:
1 . Muddapu VR, Mandali A, Chakravarthy VS, Ramaswamy S (2019) A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity. Front Neural Circuits 13:11 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Basal ganglia; Subthalamic Nucleus;
Cell Type(s): Abstract Izhikevich neuron;
Channel(s):
Gap Junctions:
Receptor(s): AMPA; Gaba; NMDA;
Gene(s):
Transmitter(s): Dopamine; Glutamate; Gaba;
Simulation Environment: MATLAB;
Model Concept(s): Deep brain stimulation; Parkinson's;
Implementer(s): Muddapu, Vignayanandam R. [vignan.0009 at gmail.com]; Chakravarthy, Srinivasa V. [schakra at iitm.ac.in];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; Dopamine; Gaba; Glutamate;
function w = calclatwts(nlat, sig, rad)

%% Computing lateral weight matrix

% Arguments
%nlat is the size of the window. It must be an odd number.
%sig: strength of the connections
%rad: radius of neighborhood

% Output
%w: weight matrix with size (nlat x nlat)

%%
%Created on 2016
%@author: Vignayanandam R. Muddapu (CNS@IIT-Madras)

%%
w = zeros(nlat, nlat);
ic = (nlat+1)/2;
jc = (nlat+1)/2;


for i = 1:nlat,
   for j = 1:nlat,
        dis = (i-ic)*(i-ic) + (j-jc)*(j-jc);
        w(i, j) = sig*exp(-dis/(rad*rad)) ; 
        if(i==j)
            w(i,j)=0;
        end
   end
end