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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 GLU cell; Piriform cortex anterior pyramidal layer II GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell; Piriform cortex anterior interneuron superficial GABA cell; Piriform cortex anterior interneuron deep layer GABA 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 GLU cell; Piriform cortex anterior pyramidal layer II GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell; Piriform cortex anterior interneuron superficial GABA cell; Piriform cortex anterior interneuron deep layer GABA cell; Nicotinic; Muscarinic; Cholinergic Receptors; Olfactory Receptors; Acetylcholine;
Files displayed below are from the implementation
function [OSN,Pg,M1,M2,Gr,Ff,Py,Fb] = CreateOlfacSys(tsim,ncells,Mod,OdorConc,OdorTime)
% [OSN,Pg,M1,M2,Gr,Ff,Py,Fb] = CreateOlfacSysNE(tsim,ncells,Mod,OdorConc,OdorTime)
% This function creates the cell groups and runs the simulation:
% tsim: simulation time
% ncells: number of cells in each cell group
% Mod is a value between 1 (for Mod ON) or 0 (for Mod OFF)
% OdorConc: Odor concentration (between 0 and 1)
% OdorTime: time of odor presentation [tinit,tfinal]

if nargin < 5
    OdorTime = [0, tsim];
end
if nargin < 4
    OdorConc = 0;
end
% Creating cell groups:
% Bulb:

OSN = classOSN(tsim,ncells);
Pg = classPglo(tsim,ncells);
M1 = classMitglo(tsim,ncells);
M2 = classMitsoma(tsim,ncells);
Gr = classGranule(tsim,ncells);

% Cortex:
Ff = classFeedforward(tsim,ncells);
Py = classPyramidal(tsim,ncells);
Fb = classFeedback(tsim,ncells);

% Set network parameters
[OSN,Pg,M1,M2,Gr] = SetBulbParam(OSN,Pg,M1,M2,Gr,Mod);
OSN.InputTimes = OdorTime; % sets the new odor time
OSN.OdorInput = SetOdorInput(OSN);
OSN.OdorInput = OSN.OdorInput .* OdorConc; % changes odor concentration
[Ff,Py,Fb] = SetCortexParam(Ff,Py,Fb,Mod);

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