Olfactory bulb network model of gamma oscillations (Bathellier et al. 2006; Lagier et al. 2007)

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Accession:91387
This model implements a network of 100 mitral cells connected with asynchronous inhibitory "synapses" that is meant to reproduce the GABAergic transmission of ensembles of connected granule cells. For appropriate parameters of this special synapse the model generates gamma oscillations with properties very similar to what is observed in olfactory bulb slices (See Bathellier et al. 2006, Lagier et al. 2007). Mitral cells are modeled as single compartment neurons with a small number of different voltage gated channels. Parameters were tuned to reproduce the fast subthreshold oscillation of the membrane potential observed experimentally (see Desmaisons et al. 1999).
Reference:
1 . Bathellier B, Lagier S, Faure P, Lledo PM (2006) Circuit properties generating gamma oscillations in a network model of the olfactory bulb. J Neurophysiol 95:2678-91 [PubMed]
2 . Lagier S, Panzanelli P, Russo RE, Nissant A, Bathellier B, Sassoè-Pognetto M, Fritschy JM, Lledo PM (2007) GABAergic inhibition at dendrodendritic synapses tunes gamma oscillations in the olfactory bulb. Proc Natl Acad Sci U S A 104:7259-64 [PubMed]
3 . Bathellier B, Lagier S, Faure P, Lledo PM (2006) Corrigendum for Bathellier et al., J Neurophysiol 95 (4) 2678-2691. J Neurophysiol 95:3961-3962
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell;
Channel(s): I Na,p; I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaA;
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Oscillations; Delay; Olfaction;
Implementer(s):
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; GabaA; I Na,p; I Na,t; I A; I K; 
/**************************************************************************

	Noise.h													JJS 24/03/2003
	
		addition to CONICAL, the Computational Neuroscience Class Library
	
	A Noise is a Current source in Sink.  Its value 
    is aleatory with Mean = 0 and Variance = 0.1 nA.
	
	This is implemented by keeping G equal to 0, but letting EG return
	E (as if G=1) -- a bit of a double standard.  Additional methods
	SetI and GetI are implemented to allow this class to be used in
	a more technically correct manner.


	Requires:
		Channel			-- base class
		NoiseI          -- gaussian white noise generator
**************************************************************************/

#ifndef NOISE_H
#define NOISE_H

#include "ChannelRk4.h"
#include "NoiseSource.h"



class Noise : public Channel
{
  public:

	Noise( Compartment *pTo )				// constructor
	: Channel( pTo, 0), Amplitude(0.1E-9){}
	
	virtual void Step(const real dt){E=NoiseI(Amplitude);}   //stepper
			
	virtual real GetEG( void ) const { return E; }   // inspectors
	
    virtual real GetEGk1(void) const { return E; }   // inspectors Runge Kutta
	virtual real GetEGk2(void) const { return E; }
	virtual real GetEGk3(void) const { return E; }
	virtual real GetEGk4(void) const { return E; }
	
	virtual void SetAmplitude(real pAmp) { Amplitude = pAmp; } // Amplitude setter
	
  protected:
	real Amplitude;
};

#endif