Aburn, M. J. | bioRxiv Science

bioRxiv2017

The Brain Dynamics Toolbox for Matlab

The Brain Dynamics Toolbox provides a graphical tool for simulating user-defined dynamical systems in O_SCPLOWMATLABC_SCPLOW. It supports three classes of differential equations commonly used in computational neuroscience: Ordinary Differential Equations, Delay Differential Equations and Stochastic Differential Equations. The design of the graphical interface fosters intuitive exploration of the dynamics, yet there is no barrier to scripting large-scale simulations and parameter explorations. System variables and parameters may range in size from simple scalars to large vectors or matrices. The toolbox is intended for dynamical models in computational neuroscience but it can be applied to continuous dynamical systems from any domain.

neuroscience↗

bioRxiv2017

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain

Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain pushed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal rich club regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain.

neuroscience↗