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Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019)

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Accession:256140
"Cerebellar Purkinje cells mediate accurate eye movement coordination. However, it remains unclear how oculomotor adaptation depends on the interplay between the characteristic Purkinje cell response patterns, namely tonic, bursting, and spike pauses. Here, a spiking cerebellar model assesses the role of Purkinje cell firing patterns in vestibular ocular reflex (VOR) adaptation. The model captures the cerebellar microcircuit properties and it incorporates spike-based synaptic plasticity at multiple cerebellar sites. ..."
Reference:
1 . Luque NR, Naveros F, Carrillo RR, Ros E, Arleo A (2019) Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLoS Comput Biol 15:e1006298 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell; Vestibular neuron; Abstract integrate-and-fire leaky neuron;
Channel(s): I K; I Na,t; I L high threshold; I M;
Gap Junctions:
Receptor(s): AMPA; Gaba;
Gene(s):
Transmitter(s):
Simulation Environment: EDLUT; NEURON; MATLAB;
Model Concept(s): Activity Patterns; Sleep; Long-term Synaptic Plasticity; Vestibular;
Implementer(s): Luque, Niceto R. [nluque at ugr.es];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell; AMPA; Gaba; I Na,t; I L high threshold; I K; I M;
/
LuqueEtAl2019
EDLUT
Articulo purkinje
CASE_B
include
integration_method
BDFn.h *
BDFn_GPU.h *
BDFn_GPU2.h *
Euler.h *
Euler_GPU.h *
Euler_GPU2.h *
FixedStep.h *
FixedStepSRM.h *
IntegrationMethod.h *
IntegrationMethod_GPU.h *
IntegrationMethod_GPU2.h *
LoadIntegrationMethod.h *
LoadIntegrationMethod_GPU.h *
LoadIntegrationMethod_GPU2.h *
RK2.h *
RK2_GPU.h *
RK2_GPU2.h *
RK4.h *
RK4_GPU.h *
RK4_GPU2.h *
RK45.h *
                            
/***************************************************************************
 *                           IntegrationMethod_GPU.h                       *
 *                           -------------------                           *
 * copyright            : (C) 2013 by Francisco Naveros                    *
 * email                : fnaveros@atc.ugr.es                              *
 ***************************************************************************/

/***************************************************************************
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 3 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 ***************************************************************************/

#ifndef INTEGRATIONMETHOD_GPU_H_
#define INTEGRATIONMETHOD_GPU_H_

/*!
 * \file IntegrationMethod_GPU.h
 *
 * \author Francisco Naveros
 * \date May 2013
 *
 * This file declares a class which abstracts all integration methods in GPU (this class is stored
 * in CPU memory and controles the allocation and deleting of GPU auxiliar memory). All integration
 * methods in GPU are fixed step due to the parallel architecture of this one.
 */

#include <string>
#include "../../include/integration_method/IntegrationMethod_GPU2.h"



using namespace std;

class TimeDrivenNeuronModel_GPU;


/*!
 * \class IntegrationMethod_GPU
 *
 * \brief Integration method in CPU for GPU.
 *
 * This class abstracts the initializacion in CPU of integration methods for GPU. This CPU class
 * controles the allocation and deleting of GPU auxiliar memory.
 *
 * \author Francisco Naveros
 * \date May 2013
 */
class IntegrationMethod_GPU {
	public:

		/*!
		 * \brief This vector contains all the necesary GPU memory witch have been reserved in the CPU (this memory
		 * could be reserved directly in the GPU, but this suppose some restriction in the amount of memory witch can be reserved).
		*/
		void ** Buffer_GPU;

		/*!
		 * \brief Number of state variables for each cell.
		*/
		int N_NeuronStateVariables;

		/*!
		 * \brief Number of state variables witch are calculate with a differential equation for each cell.
		*/
		int N_DifferentialNeuronState;

		/*!
		 * \brief Number of state variables witch are calculate with a time dependent equation for each cell.
		*/
		int N_TimeDependentNeuronState;

		/*!
		 * \brief Integration method type.
		*/
		char * IntegrationMethodType;


		/*!
		 * \brief Constructor of the class with 4 parameter.
		 *
		 * It generates a new IntegrationMethod_GPU object.
		 *
		 * \param integrationMethodType Integration method type.
		 * \param N_neuronStateVariables number of state variables for each cell.
		 * \param N_differentialNeuronState number of state variables witch are calculate with a differential equation for each cell.
		 * \param N_timeDependentNeuronState number of state variables witch ara calculate with a time dependent equation for each cell.
		 */
		IntegrationMethod_GPU(char * integrationMethodType, int N_neuronStateVariables, int N_differentialNeuronState, int N_timeDependentNeuronState);


		/*!
		 * \brief Class destructor.
		 *
		 * It destroys an object of this class.
		 */
		virtual ~IntegrationMethod_GPU();
		

		/*!
		 * \brief It gets the integration method type.
		 *
		 * It gets the integration method type.
		 *
		 * \return The integration method type.
		 */
		char * GetType();


		/*!
		 * \brief This method reserves all the necesary GPU memory (this memory could be reserved directly in the GPU, but this 
		 * suppose some restriction in the amount of memory witch can be reserved).
		 *
		 * This method reserves all the necesary GPU memory (this memory could be reserved directly in the GPU, but this 
		 * suppose some restriction in the amount of memory witch can be reserved).
		 *
		 * \param N_neurons Number of neurons.
		 * \param Total_N_thread Number of thread in GPU.
		 */
		virtual void InitializeMemoryGPU(int N_neurons, int Total_N_thread)=0;

	
		/*!
		 * \brief It prints the integration method info.
		 *
		 * It prints the current integration method characteristics.
		 *
		 * \param out The stream where it prints the information.
		 *
		 * \return The stream after the printer.
		 */
		ostream & PrintInfo(ostream & out);
};

#endif /* INTEGRATIONMETHOD_GPU_H_ */

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