Constrain synaptic connections in a neural model

As paired recordings between connected cells become more prevalent in the experimental literature, we have a better ability to include detailed, biologically-constrained connectivity in our neural network models. Here I give my strategy for characterizing experimental data about synaptic connections between cells, for use in a detailed, data-driven neural model. Continue reading

Speed up your NEURON code

I use NEURON for my neural simulations and I recommend it. Not only is it well documented, but it is consistently well supported – Michael Hines and Ted Carnevale (NEURON developers) are always quick to respond to questions on the NEURON forum or by email. NEURON has been used in well over a thousand publications.

Most every programmer is interested in having their program execute as quickly as possible. This concern is held by computational neuroscientists as well. Most important is your time: the faster you can get results, the faster your research progresses and the sooner you can get published. But computing time is also an issue – people often run their simulations on shared machines and can only get (or afford) a limited amount of computing time. Continue reading