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Front. Neuroinform. | doi: 10.3389/fninf.2018.00087

Xolotl: An Intuitive and Approachable Neuron and Network Simulator for Research and Teaching

  • 1Brandeis University, United States

Conductance-based models of neurons are used extensively in computational neuroscience. Working with these models can be challenging due to their high dimensionality and large number of parameters. Here, we present a neuron and network simulator built on a novel automatic type system that binds object-oriented code written in C++ to objects in MATLAB. Our approach builds on the tradition of uniting the speed of languages like C++ with the ease-of-use and feature-set of scientific programming languages like MATLAB. Xolotl allows for the creation and manipulation of hierarchical models with components that are named and searchable, permitting intuitive high-level programmatic control over all parts of the model. The simulator's architecture allows for the interactive manipulation of any parameter in any model, and for visualizing the effects of changing that parameter immediately. Xolotl is fully featured with hundreds of ion channel models from the electrophysiological literature, and can be extended to include arbitrary conductances, synapses, and mechanisms. Several core features like bookmarking of parameters and automatic hashing of source code facilitate reproducible and auditable research. Its ease of use and rich visualization capabilities make it an attractive option in teaching environments. Finally, xolotl is written in a modular fashion, includes detailed tutorials and worked examples, and is freely available at https://github.com/sg-s/xolotl, enabling seamless integration into the workflows of other researchers.

Keywords: code:Matlab., code:C++, Software, Hodgkin-Huxley, Conductance-based

Received: 17 Aug 2018; Accepted: 05 Nov 2018.

Edited by:

Sean L. Hill, Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Canada

Reviewed by:

Ivan Raikov, Stanford University, United States
Srikanth Ramaswamy, École Polytechnique Fédérale de Lausanne, Switzerland  

Copyright: © 2018 Gorur-Shandilya, Hoyland and Marder. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Srinivas Gorur-Shandilya, Brandeis University, Waltham, 02453, Massachusetts, United States, frontiers@srinivas.gs