Prognostication of Human Brain EEG Signal Dynamics Using a Refined Coupled Oscillator Energy Exchange Model

Abstract

This article introduces the coupled oscillator energy exchange model (COEEM) which simulates experimentally observed human brain EEG signal dynamics. This model is in some ways similar to the Kuramoto model, but essentially differs in that the Kuramoto model oscillator amplitude is constant, while the COEEM model oscillator amplitude is dependent on the phase of the oscillators. The reasoning behind the COEEM model construction is based on an energy exchange and synchronization simulation in a localized brain area using (i) the coupled oscillators approach and (ii) experimental (non-filtered and filtered) EEG observations. For this purpose, we proposed a unique and very narrow spectral band prognostication and superposition method of just 0.01-0.1 Hz. It has been shown that the COEEM model, is suitable not only for accurate short term prognoses of human brain EEG signal dynamics (several ms) but also for the long term (several seconds). In the latter case, for the chosen mind states and EEG channel prognostication, we created and effectively applied a method for the superposition of prognostication results for very narrow spectral bandwidths. In short, based on the promising prognostication results for the real EEG signals, we infer that the oscillatory model presented here well simulates energy exchange features characteristic to localized human brain activations dynamics.