From dawn till dusk: Time-adaptive bayesian optimization for neurostimulation.

ABSTRACT: Stimulation optimization has garnered considerable interest in recent years in order to efficiently parametrize neuromodulation-based therapies. To date, efforts focused on automatically identifying settings from parameter spaces that do not change over time. A limitation of these approaches, however, is that they lack consideration for time dependent factors that may influence therapy outcomes. Disease progression and biological rhythmicity are two sources of variation that may influence optimal stimulation settings over time. To account for this, we present a novel time-varying Bayesian optimization (TV-BayesOpt) for tracking the optimum parameter set for neuromodulation therapy. We evaluate the performance of TV-BayesOpt for tracking gradual and periodic slow variations over time. The a

SUBMITTER: Fleming JE 

PROVIDER: S-EPMC10718444 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature