Byron Galbraith

  • Spiking Neural Networks in Python (Part 1)

    March 6, 2011

    Previously I demonstrated how to represent and simulate models of individual neurons using Python. In this next series of articles I’m going to show how Python can be used to simulate connected networks of spiking neurons. Modeling and evaluating these networks can give us an insight into how populations of neurons in the brain interact [...]

  • Neural Modeling with Python (Part 5)

    February 22, 2011

    We’ve seen how Python can be an effective tool for simply and efficiently implementing and simulating four different neural models using Python: leaky Integrate-and-fire, Hodgkin-Huxley, Izhikevich, and active compartments. However, other than some convenience methods and simple tricks, these examples could have been done in MATLAB without too much pain for an experienced user. So [...]

  • Neural Modeling with Python (Part 4)

    February 11, 2011

    So far I’ve presented three different models for simulating neural spiking dynamics. A key assumption that was made but never stated in each of these examples was that the neuron we were modeling had no defined morphology. In other words, we were looking at models that assumed the neuron was a dimensionless sphere or point. [...]

  • Neural Modeling with Python (Part 3)

    February 2, 2011

    So far we’ve looked at how to simulate a simple LIF model neuron and a complex Hodgkin-Huxley model neuron. The LIF neuron is computationally simple but physiologically implausible, while Hodgkin-Huxley gives us a very good representation of actual neural dynamics but is parameter-heavy and computationally expensive. An intriguing compromise between the two exists — one [...]

  • Neural Modeling with Python (Part 2)

    January 26, 2011

    In my last post, I demonstrated how to simulate and plot a simple leaky integrate-and-fire (LIF) neuron using Python. The LIF neuron provides a simple representation of a spiking neuron, but lacks biological plausibility especially when it comes to the actual spike generation. A neural model that does have a solid foundation in physiology is [...]

  • Neural Modeling with Python (Part 1)

    January 19, 2011

    Representing the function and behavior of neurons in software is one of the core activities of computational neuroscience. As neurons communicate via electrochemical currents, this is typically accomplished through modeling the dynamical nature of the neuron’s electrical properties. Several models treat the neuron as an equivalent electrical circuit, with its membrane potential described by one [...]

  • Python in Computational Neuroscience

    December 20, 2010

    Python (http://www.python.org/) is a programming language that has gained a significant amount of traction in the scientific computing community over the last few years. It combines the rapid prototyping and expressiveness of MATLAB with the power and object-oriented nature of C++ or Java. In the fields of Computational Neuroscience and Neuroinformatics, Python has seen its [...]