A synapse model for developing somatosensory cortex (Manninen et al 2020)

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We developed a model for an L4-L2/3 synapse in somatosensory cortex to study the role of astrocytes in modulation of t-LTD. Our model includes the one-compartmental presynaptic L4 spiny stellate cell, two-compartmental (soma and dendrite) postsynaptic L2/3 pyramidal cell, and one-compartmental fine astrocyte process.
1 . Manninen T, Saudargiene A, Linne ML (2020) Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex. PLoS Comput Biol 16:e1008360 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Glia;
Brain Region(s)/Organism: Barrel cortex;
Cell Type(s): Neocortex L2/3 pyramidal GLU cell; Astrocyte; Neocortex spiny stellate cell;
Channel(s): Ca pump; I CAN; I Na,p; I_SERCA; I_KD; I A; I K; I N; I L high threshold; I C;
Gap Junctions:
Receptor(s): NMDA; AMPA; IP3; mGluR;
Transmitter(s): Glutamate; Endocannabinoid;
Simulation Environment: Python;
Model Concept(s): Development; Long-term Synaptic Plasticity; Synaptic Plasticity; Calcium dynamics; STDP;
Implementer(s): Manninen, Tiina [tiina.h.manninen at gmail.com]; Saudargiene, Ausra [ausra.saudargiene at gmail.com];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; AMPA; NMDA; mGluR; IP3; I Na,p; I L high threshold; I N; I A; I K; I CAN; I_SERCA; I_KD; Ca pump; I C; Glutamate; Endocannabinoid;
% Plots of inputs, saved state variables, and other saved ouput variables with certain temporal difference
% Tiina Manninen
% September 2020 

clear all;

% Loading data
folderName1 = 'results_post_pre_pairing_100x';
folderName2 = '10ms';
statevar = load(fullfile('..', folderName1, folderName2, 'state_var_results.mat'));
othervar = load(fullfile('..', folderName1, folderName2, 'other_var_results.mat'));
timestim = load(fullfile('..', folderName1, folderName2, 'time_stimuli.mat'));
par = load(fullfile('..', folderName1, folderName2, 'stimulation_parameters.mat'));

% Plotting inputs
set(gcf,'Name', 'Pre- and postsynaptic stimulus');
plot(timestim.time, timestim.I_ext_pre(1:length(timestim.time)),'k');
xlabel('Time (s)');
ylabel('{I_{extpre}}','FontSize', 11,'FontName', 'times');
title({['Temporal difference: -', num2str(par.T_shift), ' ms'] ['Presynaptic stimulus: ', num2str(par.pulserate), ' Hz']});

plot(timestim.time, timestim.I_ext_post,'k');
xlabel('Time (s)');
ylabel('{I_{extpost}}','FontSize', 11,'FontName', 'times');
title(['Postsynaptic stimulus: ', num2str(par.pulserate), ' Hz']);

% Plotting saved state variables
hold all;
set(gcf,'Name', 'State variables');
statenames = fieldnames(statevar);
for i = 1:1:length(statenames)
	hold all;
	x = statevar.(statenames{i});
	plot(timestim.time, x);
	xlabel('Time (s)'); ylabel(char(statenames(i)),'Interpreter','none');
hold off;

%% Plotting other saved output variables
hold all;
set(gcf,'Name', 'Other output variables');
othernames = fieldnames(othervar);
for i = 1:1:length(othernames)
	hold all;
	x = othervar.(othernames{i});
	plot(timestim.time(2:end), x);
	xlabel('Time (s)'); ylabel(char(othernames(i)),'Interpreter','none');
hold off;

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