[SciPy-User] Optimizing odeint without a for loop

[Rob Clewley]

On Wed, Jun 4, 2014 at 4:41 PM, Sturla Molden <sturla.molden at gmail.com> wrote:
> If you are solving Hodkin-Huxley equations you might consider NEURON.

While I don't disagree that you should consider all the available
tools (and there is a python interface for it these days), you want to
balance the overheads of model set up and learning curve with what
kinds of study you are doing. For instance, for relatively small
models (a handful of equations, maybe just single compartment
neurons), even if they are conductance-based, NEURON is overkill, IMO.
NEURON is particularly well suited for straight-up simulations of
multi-compartment, highly anatomically realistic neurons. However, if
you expect to do bifurcation analysis or some exploratory mathematical
simplifications involving reduced model components, then NEURON will
not be an appropriate tool. Also, as you mentioned, Barrett, Brian has
some limitations regarding its numerical schemes, and focuses on
spiking (I&F-like) models, although NEURON's numerical solvers are
sound. If you want robust numerics and analytical capabilities,
PyDSTool is a good place to go (it uses industry standard implicit
solvers, Dopri and Radau as well as arbitrarily accurate zero-crossing
detection). So it all depends what you are trying to achieve in your
project. If you do want more advice, I'd suggest you describe your
project more.

-Rob