ACh modulation in olfactory bulb and piriform cortex (de Almeida et al. 2013;Devore S, et al. 2014)

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Accession:146813
This matlab code was used in the papers de Almeida, Idiart and Linster, (2013), Devore S, de Almeida L, Linster C (2014) . This work uses a computational model of the OB and PC and their common cholinergic inputs to investigate how bulbar cholinergic modulation affects cortical odor processing.
References:
1 . de Almeida L, Idiart M, Linster C (2013) A model of cholinergic modulation in olfactory bulb and piriform cortex. J Neurophysiol 109:1360-77 [PubMed]
2 . Devore S, de Almeida L, Linster C (2014) Distinct roles of bulbar muscarinic and nicotinic receptors in olfactory discrimination learning. J Neurosci 34:11244-60 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Olfactory bulb main mitral cell; Piriform cortex anterior pyramidal layer II cell; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; Piriform cortex anterior interneuron superficial cell; Piriform cortex anterior interneuron deep layer cell;
Channel(s):
Gap Junctions:
Receptor(s): Nicotinic; Muscarinic; Cholinergic Receptors; Olfactory Receptors;
Gene(s):
Transmitter(s): Acetylcholine;
Simulation Environment: MATLAB;
Model Concept(s): Oscillations; Synchronization; Synaptic Plasticity; Noise Sensitivity; Olfaction;
Implementer(s): de Almeida, Licurgo [lbd38 at cornell.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral cell; Piriform cortex anterior pyramidal layer II cell; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; Piriform cortex anterior interneuron superficial cell; Piriform cortex anterior interneuron deep layer cell; Nicotinic; Muscarinic; Cholinergic Receptors; Olfactory Receptors; Acetylcholine;
Files displayed below are from the implementation
function [Ff,Py,Fb] = SetCortexParam(Ff,Py,Fb,Mod)
% [Ff,Py,Fb] = SetBulbParam(Ff,Py,Fb,Mod)
% This function set the cortical parameters, where:
% Ff,Py,Fb are objects;
% Mod is either between 1 (for Mod fully ON), 0 (for Mod fully OFF) or -1 
% (for Mod dynamic)


% Feedforward neurons (Ff)
Ff.AMPAFf.G = 200e-3;
Ff.tau = 5;
Ff.Tmin = [-0.3e-3,-0.3e-3];
Ff.Cmax = 5;
Ff.ModValue = Mod;


%Pyramidal cells
Py.AMPAFf.G = 759e-3;
Py.AMPAFb.G = [510,260];
Py.AMPAFb.tau1 = 1;
Py.AMPAFb.tau2 = 2;
Py.GABAFb.G = [550e-3,550e-3];
Py.GABAFf.G = 55e-3;
Py.AAHP = [40,0];
Py.Cmax = 5;
Py.ModValue = Mod;
Py.tauAHP = 100;
Py.tau = 10;
Py.Beta = 2; 
Py.Tau11 = 800;
Py.Tau01 = 400;
Py.Tau10 = 400;
Py.LearnUnlearn = false;
Py.MAMPAFf = Py.SetConnections(Py.ncells,Py.ConnAMPAFf,'normal');
Py.WAMPAFf = Py.MAMPAFf;


% Feedback cells (Fb)
Fb.AMPAFf.G = [250e-3,60e-3];
Fb.tau = 5;
Fb.Tmin = [0e-3,-0.1e-3];
Fb.Cmax = 5;
Fb.ModValue = Mod;

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