Bayesian Temporal Prediction: A Robust Algorithm for Real-Time EEG Phase-Dependent Brain Stimulation.

ABSTRACT:

Objective

Real-time estimation of brain state is essential for efficient brain stimulation. Specifically, the electroencephalography (EEG) oscillation phase arose as a promising biomarker for instantaneous brain excitability, making it ideal for state-dependent brain stimulation. Current methods for real-time EEG phase extraction lose accuracy in the presence of non-stationary noise, motivating the development of a more robust and accurate algorithm. Here, we propose and validate Bayesian Temporal Prediction (BTP) as an effective method for EEG phase detection in real-time.

Methods

BTP utilizes a short pre-session EEG recording and learning of the personalized prediction parameters, enabling subsequent high-precision real-time phase detection. We experimentally validate BTP

SUBMITTER: Shirinpour S 

PROVIDER: S-EPMC12395933 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature