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PhD thesis presentation: Fabio Barollo

PhD in Biomedical Engineering

  • 13.6.2022, 13:00 - 14:00, Háskólinn í Reykjavík

Fabio Barollo completed his BSc in Information Engineering and MSc in Biomedical Engineering at the University of Padova (Italy). In 2017 he joined the Institute of Biomedical and Neural Engineering at Reykjavik University, where he completed his Master's thesis under the supervision of Prof. Paolo Gargiulo. In 2018 Fabio started a joint PhD program in biomedical engineering with Reykjavik University and Aston University (Birmingham, UK). His research revolves around EEG applications for postural neuroscience, with particular focus on source reconstruction and brain network analysis. He defended his PhD thesis in Birmingham in April 2022.
The presentation will take place at Reykjavik University in M208, June 13th at 13:00.

Prof Paolo Gargiulo, Reykjavik University
Prof Antonio Fratini, Aston University
Prof Ceon Ramon, Washington University
Dr. Mahmoud Hassan, Reykjavik University
Prof Hanne Petersen, University of Iceland

EEG-based investigation of cortical activity during Postural Control

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 analyzed 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 characterize 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, it was possible 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.
Keywords: Postural control · Electroencephalography (EEG) · Functional connectivity · Brain network analysis · Proprioceptive vibrations

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