NeuronVisio An user interface for NEURON simulator environment
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visualization front-end 3D visualization NEURON GUI simulator environment NEURON

NeuronVisio Description

An user interface for NEURON simulator environment NeuronVisio connects with NEURON using the new Python NEURON interface.Installation:To install NeuronVisio you need to satisfy the following dependencies * pygtk * visual * matplotlibEasy InstallThe easiest way to get neuronvisio is if you have setuptools installed:easy_install neuronvisioWithout setuptools, it's still pretty easy. Download the neuronvisio.tgz file from neuronvisio's Cheeseshop page, untar it and run:python setup.py installDocumentationThe documentation is available in the doc folder or online.QuickstartThis code is just to give an idea in how to use nrnvisio module:1. fire up an ipython console with pylab switch.: ipython -pylab # If you don't use the switch you will not see any graph.2. Import the module: from neuronvisio.controls import Controls controls = Controls()When nrnvisio is started the thread is launched. In this thread all the process of nrnvisio will happen without blocking the console.As a quick example the following code: 1. Creates a single section called soma 2. Insert an Hodgkey-Huxley channel and a passive conductance 3. Insert an alphaSynapse to provide a stimul.A quick example can be the following::from nrnvisio.controls import Controlscontrols = Controls() # Starting the GUIfrom neuron import h # Getting the HocInterpretersoma = h.Section() # Creating a sectionsoma.insert('hh') # Inserting a HH channelsoma.insert('pas') # inserting a passive conductancesyn = h.AlphaSynapse(0.5, sec=soma) # synaptic inputsyn.onset = 0.5 # when to firesyn.gmax = 0.05 # the conductance of the synapsesyn.e = 0 # the reversal potentialMore example in the example directory show how to use Neuronvisio with more complex model. Here are some key features of "NeuronVisio": · 3D visualization of the model with the possibility to change it runtime · Creation of vectors to record any variables present in the section · Pylab integration to plot directly the result of the simulation · Exploration of the timecourse of any variable among time using a color coded scale · the GUI runs in its own thread so it's possible to use the console (strongly suggested ipython) Requirements: · Python

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