Multiscale model of excitotoxicity in PD (Muddapu and Chakravarthy 2020)

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Accession:266637
Parkinson's disease (PD) is a neurodegenerative disorder caused by loss of dopaminergic neurons in Substantia Nigra pars compacta (SNc). Although the exact cause of cell death is not clear, the hypothesis that metabolic deficiency is a key factor has been gaining attention in recent years. In the present study, we investigate this hypothesis using a multi-scale computational model of the subsystem of the basal ganglia comprising Subthalamic Nucleus (STN), Globus Pallidus externa (GPe) and SNc. The proposed model is a multiscale model in that interactions among the three nuclei are simulated using more abstract Izhikevich neuron models, while the molecular pathways involved in cell death of SNc neurons are simulated in terms of detailed chemical kinetics. Simulation results obtained from the proposed model showed that energy deficiencies occurring at cellular and network levels could precipitate the excitotoxic loss of SNc neurons in PD. At the subcellular level, the models show how calcium elevation leads to apoptosis of SNc neurons. The therapeutic effects of several neuroprotective interventions are also simulated in the model. From neuroprotective studies, it was clear that glutamate inhibition and apoptotic signal blocker therapies were able to halt the progression of SNc cell loss when compared to other therapeutic interventions, which only slows down the progression of SNc cell loss.
Reference:
1 . Muddapu VR, Chakravarthy VS (2020) A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson's Disease. Front Neuroinform 14:34 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Basal ganglia; Subthalamic Nucleus;
Cell Type(s): Substantia nigra pars compacta DA cell; Globus pallidus principal GABA cell; Abstract Izhikevich neuron; Subthalamus nucleus projection neuron;
Channel(s): Ca pump; I A, slow; I Ca SOCC; I h; I_Na,Ca; I_SERCA; Na/K pump; Na/Ca exchanger;
Gap Junctions:
Receptor(s): NMDA; AMPA; GabaA; Dopaminergic Receptor;
Gene(s):
Transmitter(s): Dopamine; Glutamate; Gaba;
Simulation Environment: MATLAB; MATLAB (web link to model);
Model Concept(s): Action Potentials; Activity Patterns; Bursting; Calcium dynamics; Deep brain stimulation; Detailed Neuronal Models; Neurotransmitter dynamics; Multiscale; Neuromodulation; Pacemaking mechanism; Pathophysiology; Parkinson's; Simplified Models;
Implementer(s): Muddapu, Vignayanandam R. [vignan.0009 at gmail.com]; Chakravarthy, Srinivasa V. [schakra at iitm.ac.in];
Search NeuronDB for information about:  Substantia nigra pars compacta DA cell; Globus pallidus principal GABA cell; GabaA; AMPA; NMDA; Dopaminergic Receptor; I h; I A, slow; Na/Ca exchanger; I_Na,Ca; I_SERCA; Na/K pump; Ca pump; I Ca SOCC; Dopamine; Gaba; Glutamate;
function [firings]=ConvertAPtoST(input_firings,Pnrn)
%% CREDITS
% Created by
% Vignayanandam R. Muddapu (Ph.D. scholar)
% C/o Prof. V. Srinivasa Chakravarthy
% Indian Institute of Technology Madras
% India

% Converting Action potential to spike train
% input_firings = times of action action potential above certain threshold
% Pnrn = number of neurons

%% CODE
% Pnrn=16;
firings=[];
for i=1:Pnrn
    inds=input_firings((input_firings(:,2)==i));
    zero=zeros(1000,1);
    inds1=[zero;inds];
    isi=diff(inds1);
    ind=find(isi>10)-999;
    spikes=inds(ind);
    firings=[firings; spikes,i+0*spikes];
end

% [Y,I]=sort(firings(:,1));
% firings=firings(I,:);

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