Validation of EEG data assimilation-based prefrontal excitation-inhibition balance estimation using TMS-EEG

Abstract

The excitation and inhibition (E/I) balance of neural circuits is a crucial index reflecting neurophysiological homeostasis. Although several cutting-edge methods have been established to assess E/I balance in an intact brain, they have inherent limitations, such as difficulties in tracking changes in E/I balance over time. To tackle this issue, we have proposed neural-mass-model-based tracking of the brain states using a data assimilation (DA) scheme in our previous work. However, although we verified that sleep-dependent changes in E/I balance can be estimated from electroencephalography data, the neurophysiological validity of the method was not evaluated. Therefore, in the current study, we directly compared estimated E/I states based on the DA methods with the concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) based methods. The results showed that the E/I changes estimated by the DA-based method correlated significantly with E/I in the dorsolateral prefrontal cortex, as indexed by TMS-evoked EEG. These findings indicate that our proposed method can estimate neurophysiologically valid changes in E/I balance.