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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;
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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 *
                            
/***************************************************************************
 *                           RK4_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 RK4_GPU_H_
#define RK4_GPU_H_

/*!
 * \file RK4_GPU.h
 *
 * \author Francisco Naveros
 * \date May 2013
 *
 * This file declares a class which implement a fourth order Runge-Kutta integration method 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 "./IntegrationMethod_GPU.h"


/*!
 * \class RK4_GPU
 *
 * \brief RK4 integration method in CPU for GPU.
 *
 * This class abstracts the initializacion in CPU of a fourth order Runge-Kutta integration methods for GPU. This CPU class
 * controles the reservation and freeing of GPU auxiliar memory.
 *
 * \author Francisco Naveros
 * \date May 2013
 */


class RK4_GPU: public IntegrationMethod_GPU{
	public:

		/*!
		 * \brief These vectors are used as auxiliar vectors.
		*/
		float * AuxNeuronState;
		float * AuxNeuronState1;
		float * AuxNeuronState2;
		float * AuxNeuronState3;
		float * AuxNeuronState4;


		/*!
		 * \brief Constructor of the class with 3 parameter.
		 *
		 * It generates a new fourth order Runge-Kutta object.
		 *
		 * \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.
		 */
		RK4_GPU(int N_neuronStateVariables, int N_differentialNeuronState, int N_timeDependentNeuronState);


		/*!
		 * \brief Class destructor.
		 *
		 * It destroys an object of this class.
		 */
		virtual ~RK4_GPU();

	
		/*!
		 * \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.
		 */	
		void InitializeMemoryGPU(int N_neurons, int Total_N_thread);
};

#endif /* EULER_GPU_H_ */

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