This special issue will bring together a broad range of topics discussed at the meeting in the form of Research articles and Tutorial papers. We expect that the primary contributions to the Special Issue will be Research articles, inspired by work presented at the meeting.

We also had a successful day of Tutorials, detailing topics from stochastic hybrid systems to information theory to plasticity. The community would benefit from having these ideas brought together in multiple articles, so we are soliciting the tutorial speakers and others for summary articles that would disseminate these concepts as educational background materials. Note, participants that were not Tutorial speakers may submit Tutorial papers, if they can assemble a helpful summary of a new method in mathematical neuroscience.

Topics may include, but are not limited to: stochastic dynamics and mean field methods; spatiotemporal dynamics; data-driven modeling; network connectivity and dynamics; neural coding; oscillations and synchrony; plasticity and learning; and statistical descriptions of stochastic models.

The Journal of Mathematical Neuroscience is fully Open Access. As a result, there are charges associated with publication. However, if you do not have funding to cover publication charges, please note this in your submission, and we can likely accommodate you by waiving the fees. Also, please check the journal website, which describes several different discount options that may be available to you.

We hope very much you will consider submitting to this Special Issue!

All the best

Zachary Kilpatrick (University of Colorado Boulder)

Robert Rosenbaum (University of Notre Dame)

Julijana Gjorgjieva (Max Planck Institute for Brain Research)