Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)

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Accession:144027
"... The network simulations were also based on a previously published model(Latham et al. 2000), but with modifications to allow the addition and detection of extra spikes (see Supplementary Information, section 7)."
Reference:
1 . London M, Roth A, Beeren L, Häusser M, Latham PE (2010) Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466:123-7 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Activity Patterns;
Implementer(s):
#ifndef GAUSS_H
#define GAUSS_H

//  headers
#include <cmath>
#include <cstdlib>
#include <lib.h>

//  definitions

//  prototypes
class rgauss
{
private:
	int n;
	float* y;

public:
	// constructor
	rgauss(int nn);

	// destructor
	~rgauss();

	// return random number with gaussian distribution.  second
	// call truncates from below, third trucates from below and above.
	float ran(float sigma);
	float ran(float sigma, float xmin);
	float ran(float sigma, float xmin, float xmax);

	// return array of numbers with gaussian distribution.  second
	// call truncates from below, third trucates from below and above.
	float* ran(float sigma, int ntot);
	float* ran(float sigma, int ntot, float xmin);
	float* ran(float sigma, int ntot, float xmin, float xmax);

	// return array of numbers with gaussian distribution.  second
	// call truncates from below, third trucates from below and above.
	// allow the possibility of saving alpha and beta for future calls.
	float* ran(
		float sigma, int ntot, float xmin, float xmax,
		float& alpha, float& beta);
};

#endif