Digital twin brain simulator for real-time consciousness monitoring and virtual intervention using primate electrocorticogram data.

ABSTRACT: At the forefront of bridging computational brain modeling with personalized medicine, this study introduces a novel, real-time, electrocorticogram (ECoG) simulator, based on the digital twin brain concept. Utilizing advanced data assimilation techniques, specifically a Variational Bayesian Recurrent Neural Network model with hierarchical latent units, the simulator dynamically predicts ECoG signals reflecting real-time brain latent states. By assimilating broad ECoG signals from macaque monkeys across awake and anesthetized conditions, the model successfully updated its latent states in real-time, enhancing precision of ECoG signal simulations. Behind successful data assimilation, self-organization of latent states in the model was observed, reflecting brain states and individuality. This

SUBMITTER: Takahashi Y 

PROVIDER: S-EPMC11811282 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature