A framework for optimal control of oscillations and synchrony applied to non-linear models of neural population dynamics.

ABSTRACT: We adapt non-linear optimal control theory (OCT) to control oscillations and network synchrony and apply it to models of neural population dynamics. OCT is a mathematical framework to compute an efficient stimulation for dynamical systems. In its standard formulation, it requires a well-defined reference trajectory as target state. This requirement, however, may be overly restrictive for oscillatory targets, where the exact trajectory shape might not be relevant. To overcome this limitation, we introduce three alternative cost functionals to target oscillations and synchrony without specification of a reference trajectory. We successfully apply these cost functionals to single-node and network models of neural populations, in which each node is described by either the Wilson-Cowan model or

SUBMITTER: Salfenmoser L 

PROVIDER: S-EPMC11658993 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature