EEG-based investigation of cortical activity during Postural Control

Abstract

The postural control system regulates the ability to maintain a stable upright stance and to react to changes in the external environment. Although once believed to be dominated by low-level reflexive mechanisms, mounting evidence has highlighted a prominent role of the cortex in this process. Nevertheless, the high-level cortical mechanisms involved in postural control are still largely unexplored. The aim of this thesis is to use electroencephalography, a widely used and non-invasive neuroimaging tool, to shed light on the cortical mechanisms which regulate postural control and allow balance to be preserved in the wake of external disruptions to one’s quiet stance.

EEG activity has been initially analysed during a well-established postural task - a sequence of proprioceptive stimulations applied to the calf muscles to induce postural instability – traditionally used to examine the posturographic response. Preliminary results, obtained through a spectral power analysis of the data, highlighted an increased activation in several cortical areas, as well as different activation patterns in the two tested experimental conditions: open and closed eyes.

An improved experimental protocol has then been developed, allowing a more advanced data analysis based on source reconstruction and brain network analysis techniques. Using this new approach, it was possible to characterise with greater detail the topological structure of cortical functional connections during the postural task, as well as to draw a connection between quantitative network metrics and measures of postural performance.

Finally, with the integration of electromyography in the experimental protocol, we were able to gain new insights into the cortico-muscular interactions which direct the muscular response to a postural challenge.

Overall, the findings presented in this thesis provide further evidence of the prominent role played by the cortex in postural control. They also prove how novel EEG-based brain network analysis techniques can be a valid tool in postural research and offer promising perspectives for the integration of quantitative cortical network metrics into clinical evaluation of postural impairment.

Date of Award	Jan 2022
Original language	English
Supervisor	Antonio Fratini (Supervisor)