Development of tools and paradigms to assess brain cortical activity during cognitive tasks

Abstract

Monitoring cortical activity is essential for explaining and understanding neurophysiological behavior. A wide range of tools and experimental setups have been developed to stimulate, record, and analyze brain activity. Finding a quantitative measure to analyze this activity in a specific task is essential, as it could lead to improved diagnostic procedures, explain objective self-reported states, or monitor changes in long-term studies. This paper presents the development of tools and paradigms for assessing cortical activity during cognitive tasks. The paper presents a comprehensive set of analyses based on EEG signals, in two main areas, schizophrenia and postural control. The first part of the project evaluates the impact of potential therapeutic solutions for patients with schizophrenia. A longitudinal case study is presented, where psychological data are compared with three types of EEG data analyses: temporal, spectral, and connectivity. The small sample size prevents us from drawing definitive conclusions, but this work demonstrates the interest in using EEG measures to complete a standardized psychological assessment. The second part of the work focuses on postural control, using a novel measurement setup called BioVRSea, which combines virtual reality and a moving platform. The cortical activity of more than 150 healthy subjects has been studied in this experiment. A robust neurophysiological reference has been found using power spectral density. Moreover, by combining brain connectivity and micro-postural segmentation, network activity reveals a continuous reconstruction of the brain throughout the session, which strengthens our current understanding of complex postural control. This study highlights the real benefits of using EEG signals to infer cortical activity. The tools developed in this thesis are important for building neurophysiological signatures of specific cognitive tasks, which are important for further understanding of neurodegenerative diseases.