Bayesian target optimisation for high-precision holographic optogenetics.

ABSTRACT: Two-photon optogenetics has transformed our ability to probe the structure and function of neural circuits. However, achieving precise optogenetic control of neural ensemble activity has remained fundamentally constrained by the problem of off-target stimulation (OTS): the inadvertent activation of nearby non-target neurons due to imperfect confinement of light onto target neurons. Here we propose a novel computational approach to this problem called Bayesian target optimisation. Our approach uses nonparametric Bayesian inference to model neural responses to optogenetic stimulation, and then optimises the laser powers and optical target locations needed to achieve a desired activity pattern with minimal OTS. We validate our approach in simulations and using data from in vitro experi

SUBMITTER: Triplett MA 

PROVIDER: S-EPMC10246014 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature