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

 Download zip file   Auto-launch 
Help downloading and running models
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]
Citations  Citation Browser
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
m4
src
README *
AUTHORS.txt *
CASE_A.ncb
CASE_A.vcproj
CASE_B.ncb
CASE_B.sln *
CASE_B.suo
configure *
configure.ac *
COPYING.txt *
Doxyfile *
flags.makefile.in *
INSTALL *
makefile.in *
noout2par.m *
rules.makefile.in *
static-variables.makefile *
varlog_reduced_VOR.m *
                            
Welcome to the EDLUT (Event-Driven Look-Up Table) project.
===============================================================



EDLUT (Event-Driven Look-Up Table) is a computer application for simulating 
networks of spiking neurons. It was developed in the University of Granada.
EDLUT uses event-driven simulation scheme and lookup tables to efficiently 
simulate medium or large spiking neural networks. This allows this application 
to simulate detailed biological neuron models and to interface with experimental 
setups (such as a robotic arm) in Real-time computing|real time.

The primary home page for this software can be found at 
http://edlut.googlecode.com.

EDLUTKernel is developed on Linux/x86 and Windows (with Cygwin) using the GNU Compiler
Collection. Version 4.x of g++ is supported. 

On Windows platforms, we are working on a new GUI which allows
you to generate networks, run simulations, show the simulation outputs, and more
funcionalities.

Platform notes:
===============

For further information about the installation/compilation process,
please, see the INSTALL file.

Windows:
========
To compile EDLUT in Windows you may need Cygwin be installed with the develope tools
(g++, make, socket libraries...).

Linux:
======
To compile EDLUT in Linux you need the develope tools (g++, make, socket libraries...).


Compiling the CVS version
=========================

If you checked out the sources from CVS you need to have a complete and
recent version of the GNU autotools to generate required files. Run:

$ make


Running simulations
===================

This package of EDLUTKernel includes an executable file which allows to run
spiking neural networks simulations. You can use network topologies, neural models,
input files and other resources existing in the project home page.

The different parameters for EDLUTKernel are the followings:

* Obligatory parameters:
	-time Simulation_Time(in_seconds) It sets the total simulation time.
 	-nf Network_File	It sets the network description file.
 	-wf Weights_File	It sets the weights file.
 
* Optional parameters:
	-info 	It shows the network information.
	-sf File_Name	It saves the final weights in file File_Name.
	-wt Save_Weight_Step	It sets the step time between weights saving.
	-st Step_Time(in_seconds) It sets the step time in simulation.
	-log File_Name It saves the activity register in file File_Name.
        -logp File_Name It saves all events register in file File_Name.
	-if Input_File	It adds the Input_File file in the input sources of the simulation.
	-of Output_File	It adds the Output_File file in the output targets of the simulation.
        -openmpQ number_of_OpenMP_queues It sets the number of OpenMP queues.
        -openmp number_of_OpenMP_threads It sets the number of OpenMP threads.
	-ic IPAddress:Port Server|Client	It adds the connection as a server or a client in 
	the specified direction in the input sources of the simulation.
	-oc IPAddress:Port Server|Client	It adds the connection as a server or a client in
	the specified direction in the output targets of the simulation.
	-ioc IPAddress:Port Server|Client	It adds the connection as a server or a client in
	the specified direction in the input sources and in the output targets.
	
Additional Notes
================
The EDLUTKernel Library is still in a stage of heavy development.  At this
point in the project, the API is likely to change from version to version.
Most changes to existing interfaces will be small and easy to adjust for,
but there will occasionally be major changes to some areas.  Please report
any bugs by using the bug tracking system on the development home page.
Suggestions for improvements are welcome.

Jesús Garrido Alcázar <jgarrido@atc.ugr.es>
Francisco Naveros Arrabal <fnaveros@atc.ugr.es>