Excitability of DA neurons and their regulation by synaptic input (Morozova et al. 2016a, 2016b)

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This code contains conductance-based models of Dopaminergic (DA) and GABAergic neurons, used in Morozova et al 2016 PLOS Computational Biology paper in order to study the type of excitability of the DA neurons and how it is influenced by the intrinsic and synaptic currents. We identified the type of excitability by calculating bifurcation diagrams and F-I curves using XPP file. This model was also used in Morozova et al 2016 J. Neurophysiology paper in order to study the effect of synchronization in GABAergic inputs on the firing dynamics of the DA neuron.
1 . Morozova EO, Myroshnychenko M, Zakharov D, di Volo M, Gutkin B, Lapish CC, Kuznetsov A (2016) Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting. J Neurophysiol 116:1900-1923 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Substantia nigra pars compacta DA cell; Ventral tegmental area dopamine neuron; Ventral tegmental area GABA neuron ;
Channel(s): I K,Ca; I Calcium; I Na,t; I Potassium;
Gap Junctions:
Receptor(s): GabaA; NMDA; AMPA;
Transmitter(s): Gaba; Glutamate; Dopamine;
Simulation Environment: MATLAB; XPP;
Model Concept(s): Action Potentials; Bifurcation; Bursting; Synaptic Convergence;
Implementer(s): Morozova, Ekaterina O [emorozov at indiana.edu]; Kuznetsov, Alexey ;
Search NeuronDB for information about:  Substantia nigra pars compacta DA cell; GabaA; AMPA; NMDA; I Na,t; I K,Ca; I Calcium; I Potassium; Dopamine; Gaba; Glutamate;
%% -----control coditions, a model without spike-prodcing currents---------  
% To add spike producing currents set gbarNa=50 and gDR=2 in DAneuronDB.cpp
% this part produces voltage trace and a phase plane for the reduced model
%mex DAneuronDB.cpp % build mex file
dt=0.02; TT=5000; N=TT/dt; % step, total time (5000 msec or 5 sec), number of steps
gl=0.18,gh=0; % leak conductance, H-current conductance
gbarnmda=zeros(1,N); % NMDAR conductance (set to 0)
ggaba=zeros(1,N); % GABAR conductance (set to 0)
gampa=zeros(1,N); % AMPAR conductance (set to 0)
Iapp=zeros(1,N); % applied current (set to 0)
% ----------output---------------------- 
[V,Ca] = DAneuronDB(TT,ggaba,gbarnmda,gampa,gh,Iapp); % voltage and calcium
% plot voltage and calcium
close all
figure('Position', [10, 50, 1100, 770]);
subplot(1,3,1:2), plot(dt:dt:TT,V,'k','linewidth',2)
hold on, plot(dt:dt:TT,Ca,'b','linewidth',2)
xlabel('Time (ms)'), ylabel('Voltage (mV)')
title('Voltage and Ca traces')
set(gca, 'FontSize',14); set(gca,'box','off','color','none')

%plot phase space for the reduced model (no Na, DR and H currents)
% parameters to plot nullcline
k=160; buf=0.00023; zF=0.019298; tc=0.52; r=0.2; gL=0.18; ECa=50; caleak=0.1; gbarCa=2.5;
gbarKCa=7.8; EL=-35; ENa=55; gSNa=0.13; gbarK=1; EK=-90;
vhna=-50; slna=5; VHK=-10; VSK=7;Vcah=-52; Sca=3; Mg=0.5; me=0.062;
gbarnmda=0; ggaba=0;
h1=ezplot( @(V,Ca) gbarnmda./(1+0.28*Mg*exp(-me*V))*(0-V) + ggaba.*(-90-V)...
    + gbarCa.*((((-0.0032.*(V-Vcah)./(exp(-(V-Vcah)./Sca) - 1.)))./(((-0.0032.*(V-Vcah)./(exp(-(V-Vcah)/Sca) - 1.)))...
    +(0.05*exp(-(V-Vcah+5)./40.)))).^4).*(ECa-V)+ gL.*(EL-V)+ gSNa.*(1./(1+exp(-(V-vhna)./slna))).*(ENa-V)...
    + gbarK./(1. + exp(-(V-VHK)./VSK)).*(EK-V)+gbarKCa*(Ca.^4./(k.^4+Ca.^4)).*(EK-V),[-100 10],[0 200]);
title('Phase plane')
hold on, plot(V,Ca,'k','linewidth',2)
set(gca, 'FontSize',14); set(gca,'box','off','color','none')

%% ------------this part produces a figure for a disinhibition burst and a pause ------------------
dt=0.02; TT=8000; N=TT/dt; % step, total time, number of steps
gbarnmda=[repmat(20,1,4000/dt), repmat(0,1,2000/dt), repmat(20,1,2000/dt)]; % NMDAR conductance
ggaba=[repmat(5.9,1,1500/dt), repmat(0,1,1500/dt), repmat(5.9,1,5000/dt)]; % AMPAR conduactance
gampa=zeros(1,N); % AMPAR conductance
Iapp=zeros(1,N); % applied current
figure('Position', [50, 50, 1100, 770]);
subplot(3,1,1), plot(ggaba,'linewidth',2); hold on; plot(gbarnmda,'linewidth',2)
set(gca,'box','off','color','none'); set(gca, 'FontSize',14);
set(gca,'xTick',[]); set(gca,'xColor','w')
ylabel('g (mS/cm^2)')
text(7000,24,'NMDA','Fontsize',13); text(7000,0,'GABA_A','Fontsize',13);
Vm = DAneuronDB(TT,ggaba,gbarnmda,gampa,0,Iapp);
subplot(3,1,2:3), plot(dt:dt:TT,Vm,'k','linewidth',2)
xlabel ('Time (ms)'); ylabel('Voltage (mV)')
set(gca, 'FontSize',14);set(gca,'box','off','color','none')
ylim([-90 0])

%% ---------this part reproduces part of the figure 1 with asynchronous Glu and GABA inputs----------
% asynchronous Glu and GABA inputs produce low frequency firing in DA neuron
%mex DAneuronGABApopulationDB.cpp % 1 DA neurons and a population of GABA neurons

TT=5000; dt=0.02; N=TT/dt; lambda=0.01;% total time (ms), step, number of steps, poisson rate
[Gluinp,st1]=Glu_raster(lambda,TT); % spiketimes of Glu spikes
gbarnmda=repmat(4,1,N); ggaba=repmat(8,1,N);
NG=30; % number of GABA neurons
for i=1:size(Vgabaall1,1)
    stgaba{i}=(find(di(i,:)>0)); % GABA spiketimes
frgaba=length(stgaba{2})./(TT/10^3); % mean frequency of GABA neurons
figure('Position', [100, 50, 1100, 770]);
positionVector1 = [0.1, 0.82, 0.85, 0.13]; subplot('Position',positionVector1);
for ii=1:length(st1)
    t = st1{ii};
    for jj = 1:length(t)
        line([t(jj) t(jj)],[ii-1 ii],'Color','k','linewidth',1);
xlim([50 st1{1}(end)]); set(gca,'YTick',[0:10:35]); ylim([0 35])
ylabel('Neuron #');
set(gca,'box','off','color','none'); set(gca, 'FontSize',14)
set(gca,'xTick',[]); set(gca,'xColor','w')
title('Glu raster','FontSize',14)

positionVector2 = [0.1, 0.62, 0.85, 0.13]; subplot('Position',positionVector2)
for ii=1:length(stgaba)
    t = stgaba{ii};
    for jj = 1:length(t)
        line([t(jj) t(jj)],[ii-1 ii],'Color','k','linewidth',1);
xlim([50 stgaba{1}(end)]); set(gca,'YTick',[0:10:30]); ylim([0 30])
ylabel('Neuron #');
title('GABA raster','FontSize',14)
set(gca,'box','off','color','none'); set(gca, 'FontSize',14)
set(gca,'xTick',[]); set(gca,'xColor','w')

positionVector3 = [0.1, 0.48, 0.85, 0.08]; subplot('Position',positionVector3)
title('GABAR synaptic activation','FontSize',14)
set(gca,'box','off','color','none'); set(gca, 'FontSize',14)
set(gca,'xTick',[]); set(gca,'xColor','w')
ylabel('s_{GABA}');ylim([0 1])

positionVector4 = [0.1, 0.34, 0.85, 0.08]; subplot('Position',positionVector4)
title('NMDAR synaptic activation','FontSize',14)
set(gca,'xTick',[]); set(gca,'xColor','w')
set(gca,'box','off','color','none'); set(gca, 'FontSize',14)
ylabel('s_{NMDA}'); ylim([0 1])

positionVector5 = [0.1, 0.07, 0.85, 0.2];
title('DA neuron voltage','FontSize',14)
xlabel('Time (ms)'); ylabel('Voltage (mV)')
set(gca,'YTick',[-100:20:0]); ylim([-90 0])
set(gca,'box','off','color','none'); set(gca, 'FontSize',14)

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