NeuronVisio 0.8.3

NeuronVisio connects with NEURON using the new Python NEURON interface.

Installation:

To install NeuronVisio you need to satisfy the following dependencies

 * pygtk
 * visual
 * matplotlib

Easy Install

The easiest way to get neuronvisio is if you have setuptools installed:

easy_install neuronvisio

Without setuptools, it's still pretty easy. Download the neuronvisio.tgz file from neuronvisio's Cheeseshop page, untar it and run:

python setup.py install

Documentation

The documentation is available in the doc folder or online.

Quickstart

This 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 Controls
controls = Controls() # Starting the GUI

from neuron import h # Getting the HocInterpreter

soma = h.Section() # Creating a section
soma.insert('hh') # Inserting a HH channel
soma.insert('pas') # inserting a passive conductance
syn = h.AlphaSynapse(0.5, sec=soma) # synaptic input
syn.onset = 0.5 # when to fire
syn.gmax = 0.05 # the conductance of the synapse
syn.e = 0 # the reversal potential

More example in the example directory show how to use Neuronvisio with more complex model.


Product's homepage

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