abring wrote:I am a new hand in study of neuronal network and just want to use NEURON. Can NEURON be used easily for analysing calcuim fluorescence signals get from many neurons in neocortex,such as 50 neurons or more?Can we use it for analying firing patterns?
A cusomer walked into a stationer's and said to the clerk, "I am starting to build a career
as a novelist, and I want to use a Parker fountain pen. Tell me, can Parkers be used
easily to write The Great American Novel?"
http://www.neuron.yale.edu/neuron/about/what.html contains a fairly accurate description
of the range of models that lie within NEURON's domain (although its ability to handle large-
scale models of single cells and networks--hundreds of thousands of cells with complex
morpohology--has been enhanced since that was written; see
Migliore, M, Cannia, C., Lytton, W.W., Markram, H. and Hines, M.L. Parallel network
simulations with NEURON. Journal of Computational Neuroscience 21:119-129, 2006.
Brette et al. Simulation of networks of spiking neurons: a review of tools and strategies.
J. Comput. Neurosci. DOI 10.1007/s10827-007-0038-6, 2007.
which are both available from
http://www.neuron.yale.edu/neuron/bib/nrnpubs.html ).
So it can certainly execute simulations of models that involve networks of spiking cells
with calcium accumulation. It has a complete programming language (hoc) with C-like
syntax and extensions for object-oriented programming, which can be used to create
data analysis programs. Even better, Python can be used as an alternative interpreter
for NEURON
(see
http://www.neuron.yale.edu/neuron/news/ ... 14_07.html
and
http://www.neuron.yale.edu/neuron/news/ ... 27_07.html),
which opens up enormous possibilities for sophisticated data analysis and grapical
display because of the huge amount of freely available scientific programming code that
has been developed with Python.
All you have to do is:
1. come up with the conceptual model(s) of your cells and networks
2. come up with specifications of the biological properties that are to be represented in
your model(s)
3. design experimental protocols that specify what will happen to your model(s) in the
course of simulation
4. use a programming language, or a simulation environment such as NEURON, to create
computational models that implement the specifications of biological properties, and to
create control code that implements the experimental protocols that you designed
5. run simulations that exercise your computational models according to your experimental
protocols, and record/measure the desired variables
6. analyze your measurements in whatever way you like, with whatever tools you have,
or can create using NEURON or anything else
So it's certainly doable, but it might take a little programming.
"You know how to program, don't you, Ernie? You just put your hands on the keyboard,
and type."
"Sounds pretty easy to me" said the customer. "I'll take a dozen."