Brain network dynamics in the alpha band during a complex postural control task.

Objective.To decipher brain network dynamic remodeling from electroencephalography (EEG) during a complex postural control (PC) task combining virtual reality and a moving platform.Approach.EEG (64 electrodes) data from 158 healthy subjects were acquired. The experiment is divided into several phases, and visual and motor stimulation is applied progressively. We combined advanced source-space EEG networks with clustering algorithms to decipher the brain networks states (BNSs) that occurred during the task.Main results.The results show that BNS distribution describes the different phases of the experiment with specific transitions between visual, motor, salience, and default mode networks coherently. We also showed that age is a key factor that affects the dynamic transition of BNSs in a healthy cohort.Significance.This study validates an innovative approach, based on a robust methodology and a consequent cohort, to quantify the brain networks dynamics in the BioVRSea paradigm. This work is an important step toward a quantitative evaluation of brain activities during PC and could lay the foundation for developing brain-based biomarkers of PC-related disorders.

Postural control paradigm (BioVRSea): towards a neurophysiological signature.

Objective.To define a new neurophysiological signature from electroencephalography (EEG) during a complex postural control task using the BioVRSea paradigm, consisting of virtual reality (VR) and a moving platform, mimicking the behavior of a boat on the sea.Approach.EEG (64 electrodes) data from 190 healthy subjects were acquired. The experiment is composed of 6 segments (Baseline, PRE, 25%, 50%, 75%, POST). The baseline lasts 60 s while standing on the motionless platform with a mountain view in the VR goggles. PRE and POST last 40 s while standing on the motionless platform with a sea simulation. The 3 other tasks last 40 s each, with the platform moving to adapt to the waves, and the subject holding a bar to maintain its balance. The power spectral density (PSD) difference for each task minus baseline has been computed for every electrode, for five frequency bands (delta, theta, alpha, beta, and low-gamma). Statistical significance has been computed.Main results.All the bands were significant for the whole cohort, for each task regarding baseline. Delta band shows a prefrontal PSD increase, theta a fronto-parietal decrease, alpha a global scalp power decrease, beta an increase in the occipital and temporal scalps and a decrease in other areas, and low-gamma a significant but slight increase in the parietal, occipital and temporal scalp areas.Significance.This study develops a neurophysiological reference during a complex postural control task. In particular, we found a strong localized activity associated with certain frequency bands during certain phases of the experiment. This is the first step towards a neurophysiological signature that can be used to identify pathological conditions lacking quantitative diagnostics assessment.