GSoC 2021 Project Idea 27.1 Brain Dynamics Toolbox for Matlab: Contribute new models to the collection

Computational neuroscience seeks to understand the brain by modelling the behaviour of

neurons (brain cells) using nonlinear dynamical systems. Likewise, computational cardiology uses nonlinear dynamics to understand the behaviour of cardiac myocytes (heart cells). In both cases, the nonlinear systems produce surprisingly complex behaviours that offer insights into the underlying electrophysiology.

The Brain Dynamics Toolbox ( is an open-source toolbox for simulating nonlinear dynamical systems in Matlab. It allows user-defined models to be rapidly prototyped in an intuitive graphical application where interchangeable solvers and plotting tools can be applied with no additional programming effort. This frees the researcher to focus on the core concepts with minimal implementation burden.

The Brain Dynamics Toolbox currently ships with approximately 40 example models, ranging from point models of neurons to spatially-extended neural fields. These examples serve as both

teaching tools and starting points for new models in research. Many of the examples are based on textbook models and published papers in computational neuroscience (e.g. Hodgkin-Huxley

action potential; Wilson-Cowan neural masses). Others are based on classic models from

dynamical systems (e.g. wave equation; the damped-and-driven pendulum; Brownian motion).

See Gallery | for a preview.

The aim of this Google Summer of Code project is to contribute more models to that collection.

Students are free to implement any model of their choosing from computational neuroscience,

computational cardiology or dynamical systems theory. These may be textbook examples or

models from published papers. Guidance will be provided in choosing an appropriate model. It is feasible that students will be able to implement several models in the time available. In doing so they gain practical programming experience in Matlab as well as exposure to theoretical problems in their chosen field. The students can publish their finished models on the Zenodo digital archive ( where they will be credited with authorship and assigned a digital object identifier (doi) for their work.

Requirements: Basic programming experience with Matlab is recommended. Training will be provided for programming dynamical systems.

Lead Mentor: Stewart Heitmann @heitmann, Creator of the Brain Dynamics Toolbox and Computational Scientist at the Victor Chang Cardiac Research Institute.

Co-Mentor: Adam Hill, Head of Computational Cardiology at the Victor Chang Cardiac Research Institute