Real-time analysis of high-density EEG signals for closed-loop applications

The brain is the most complex organ of our body, and a large bulk of research is conducted to understand its basic mechanisms and its impairments associated with neurological deficits. Notably, there are a variety of empirical methods that allow scientists to examine brain functioning. In particular, it is necessary to rely on non-invasive techniques to study brain activity in healthy people and patients. An emerging technique for brain imaging is the high-density electroencephalography (hdEEG), which records the changes in electrical potential on the scalp. These variations are directly related to neuronal activity in the gray matter. HdEEG systems have more than 100 electrodes placed over the scalp. HdEEG data, if combined with precise information of the head anatomy and sophisticated source localization algorithms, permit the reconstruction of neural activity in the brain. However, several processing steps are needed to move from EEG recordings to 3-dimensional images of neuronal activity. Nowadays, hdEEG analyses have been conducted in an offline manner. Important technical issues need to be addressed for real-time hdEEG analyses. The purpose of this PhD thesis is to develop a complete analysis workflow for low complexity real-time analysis of source-level hdEEG data. To ensure reliable real-time source activity reconstruction using EEG, we aim to design computationally-efficient artifact removal techniques and source localization. A further goal is to develop a software package with a graphic user interface, which simplifies online analysis procedures. The results of the PhD thesis work suggest that it is possible to use hdEEG as a non-invasive technique for real-time estimation of neuronal activity. We believe that the tools we developed for real-time hdEEG data analysis can find several new applications, such as source-based neurofeedback and closed-loop neuromodulation, holding great potential for the enhancement of brain plasticity and the treatment of neurological diseases.

Jaar van publicatie:2021

Toegankelijkheid:Open