Electroencephalography-driven brain-network models for personalized interpretation and prediction of neural oscillations


Loading...

Date

2025-06

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Objective: Develop an encephalography (EEG)-driven method that integrates interpretability, predictiveness, and personalization to assess the dynamics of the brain network, with a focus on pathological conditions such as pharmacoresistant epilepsy. Methods: We propose a method to identify dominant coherent oscillations from EEG recordings. It relies on the Koopman operator theory to achieve individualized EEG prediction and electrophysiological interpretability. We extend it with concepts from adiabatic theory to address the nonstationary and noisy EEG signals. Results: By simultaneously capturing the local spectral and connectivity aspects of patient-specific oscillatory dynamics, we are able to clarify the underlying dynamical mechanism. We use it to construct the corresponding generative models of the brain network. We demonstrate the proposed approach on recordings of patients in status epilepticus. Conclusions: The proposed EEG-driven method opens new perspectives on integrating interpretability, predictiveness, and personalization within a unified framework. It provides a quantitative approach for assessing EEG recordings, crucial for understanding and modulating pathological brain activity. Significance: This work bridges theoretical neuroscience and clinical practice, offering a novel framework for understanding and predicting brain network dynamics. The resulting approach paves the way for data-driven insights into brain network mechanisms and the design of personalized neuromodulation therapies.

Publication status

published

Editor

Book title

Volume

174

Pages / Article No.

1 - 9

Publisher

Elsevier

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

Notes

Funding

197766 - Modulation of epileptic networks by brain stimulation (SNF)
758604 - Enhancing brain function and cognition via artificial entrainment of neural oscillations (EC)
ETH-25 18-2 - Artificially regulating reward processing via non-invasive deep brain stimulation (ART-REWARD) (ETHZ)

Related publications and datasets