Open-source tools for dynamical analysis of Liley's mean-field cortex model

https://doi.org/10.1016/j.jocs.2013.06.001Get rights and content
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Highlights

  • A parallel open-source implementation of Liley's mean-field cortex model, in PETSc.

  • We implement fully implicit time integration of nonlinear and variational equations.

  • We perform equilibrium continuation, with computation of inhomogeneous eigenmodes.

  • We compute periodic solutions with Newton–Krylov iteration.

Abstract

Mean-field models of the mammalian cortex treat this part of the brain as a two-dimensional excitable medium. The electrical potentials, generated by the excitatory and inhibitory neuron populations, are described by nonlinear, coupled, partial differential equations that are known to generate complicated spatio-temporal behaviour. We focus on the model by Liley et al. (Network: Computation in Neural Systems 13 (2002) 67–113). Several reductions of this model have been studied in detail, but a direct analysis of its spatio-temporal dynamics has, to the best of our knowledge, never been attempted before. Here, we describe the implementation of implicit time-stepping of the model and the tangent linear model, and solving for equilibria and time-periodic solutions, using the open-source library PETSc. By using domain decomposition for parallelization, and iterative solving of linear problems, the code is capable of parsing some dynamics of a macroscopic slice of cortical tissue with a sub-millimetre resolution.

Keywords

Mean-field modelling
Hyperbolic partial differential equations
Numerical partial differential equations
35Q92
65Y05

Cited by (0)

Kevin R. Green is a PhD candidate in the Modelling and Computational Science programme at UOIT. His research interests span nonlinear dynamics, scientific computing, and neural mean-field modelling.

Lennaert van Veen is a Professor in the Faculty of Science at UOIT. His main research interest is the application of computational dynamical systems analysis to complex phenomena, such as fluid turbulence and mean-field cortex models.