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 LB, Idiart MA, Linster C (2013) A model of cholinergic modulation in olfactory bulb and piriform cortex. J Neurophysiol 109(5):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; Olfactory cortex anterior pyramidal neuron; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; Olfactory cortex anterior interneuron superficial layer; Olfactory cortex anterior interneuron deep layer;
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; Olfactory cortex anterior pyramidal neuron; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; Olfactory cortex anterior interneuron superficial layer; Olfactory cortex anterior interneuron deep layer; Nicotinic; Muscarinic; Cholinergic Receptors; Olfactory Receptors; Acetylcholine;
Files displayed below are from the implementation
A model of cholinergic modulation in olfactory bulb (OB) and piriform
cortex (PC).

Licurgo de Almeida, Marco Idiart and Christiane Linster, 2013.

So far the model was used in the following publications:

* de Almeida, L., Idiart, M., & Linster, C. (2013). A model of
  cholinergic modulation in olfactory bulb and piriform
  cortex. Journal of neurophysiology, 109(5), 1360-1377.
* Devore, S., de Almeida, L., & Linster, C. (2014). Distinct roles of
  bulbar muscarinic and nicotinic receptors in olfactory
  discrimination learning. Journal of Neuroscience, 34(34):
  11244-11260.

All codes presented here were implemented using Matlab 2011a and might
not work on other similar programs (i.e. Octave or very old versions
of Matlab).

To create the Bulb network using the integrate and fire model use the
following command:

[OSN,Pg,M1,M2,Gr] = CreateBulb(tsim,ncell,mod);

where:

tsim: simulation time
ncells: number of cells in each cell group
mod is either true (for mod ON) or false (for mod OFF)
The output are a group of networks:
OSN: Olfactory Sensory Neurons;
Pg: PG cells;
M1: Apical compartment from Mitral cells;
M2: Soma (spiking) compartment from Mitral cells;
Gr: Granule cells;

Parameters can be changed inside SetBulbParam.m and information about
these parameters are found in the publications cited above.

To create Mitral cell output using the simplified version of the model
(see de Almeida et al., 2013 for reasoning about the differences) use
the following command:

M2 = CreateSimpleBulb(tsim,ncell);
Where:
tsim: simulation time
ncells: number of cells in each cell group
The output is a Mitral network (M2) only.
Parameters can be changed inside SetBulbSimpleParam.m and information
about these parameters are found in the publications cited above.

You can plot the activation of a group of cells with the command:
Raster(M2);

After creating a pool of Mitral cells, one can use these neuronal
activities to feed the PC network with the following command:
[Ff,Py,Fb] = CreateCortex(M2,mod);
where:
M2 is the Mitral cell soma compartment generated by CreateBulb.m or
CreateSimpleBulb.m and mod is either true (for modulation ON) or false
(for modulation OFF)

The output are a group of networks:
OSN: Olfactory Sensory Neurons;
Ff: Feedforward neurons;
Py: Pyramidal cells;
Fb: Feedback neurons;
Parameters can be changed inside SetCortexParam.m and information
about these parameters are found in the publications cited above.

Other functions for the objects are:

Frequency(M2);  Calculates the average frequency for each cell in the
                network
Sparseness(M2); Calculates the level of sparseness
Coherence(M2);  Calculates the level of coherence

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