Calcium dynamics and wave propagation

Wave Propagation

Calcium is a major second messenger molecule in cells, with roles in processes from fertilization to apoptotic cell death. In neurons, calcium enters the cell with each action potential and is then quickly pumped out or sequestered into intracellular stores. The store in the endoplasmic reticulum is particularly interesting, as it can be involved with calcium waves -- a slow, long-lasting regenerative phenomena -- that modulate neuronal excitability. I am interested in the role of these dynamics and the effect of geometry on wave propagation in general.

This research topic was explored in my dissertation, Neymotin, McDougal et al (2015), and Neymotin et al (2016).

Computational Neuroscience Methods

I am a developer for the NEURON simulator. Historically, NEURON focused primarily on neuron and network dynamics, but I work on adding support for intra- and extracellular reaction-diffusion dynamics (McDougal et al 2013a; McDougal et al 2013b). In addition to the implementation, I developed the specification format which was designed to be independent of dimension (1D vs 3D) or stochastic vs deterministic. As needed, I have improved other aspects of NEURON, including: expanding Python support, converting the help documentation to restructured text, and translating the help documentation into Python (in progress; a partial version is here).

As part of my dissertation work, I developed a simulator called snnet which attempted to combine the mathematical accuracy and clarity of XPPAUT (which it used as a back-end) with neuroscience domain-specific constructs (e.g. neurons and synapses) to facilitate the study of random-networks of Hodgkin-Huxley style neurons. Snnet is no longer under active development, but the code and documentation remain available for download.


Making computational neuroscience models more accessible.

ModelView and as-you-type search on ModelDB

The ModelDB repository is home to over 1000 published computational neuroscience models, which promotes model reproducibility and replicability (reviewed in general in McDougal et al 2016). I develop ways to make this library of models more accessible. This has included: improving the search capabilities, allowing the online visualization of model structure instead of just source code (McDougal et al 2015), and using 3D printing to transform models into the physical world (McDougal and Shepherd 2015).

In 2014 and 2015, I presented at SenseLab's demo at the INCF booth at the Society for Neuroscience annual conference.