Cortical Pathways During Postural Control: new insights from functional EEG source connectivity

Abstract

Postural control is a complex feedback system that relies on vast array of sensory inputs in order to maintain a stable upright stance. The brain cortex plays a crucial role in the processing of this information and in the elaboration of a successful adaptive strategy to external stimulation preventing loss of balance and falls. In the present work, the participants postural control system was challenged by disrupting the upright stance via a mechanical skeletal muscle vibration applied to the calves. The EEG source connectivity method was used to investigate the cortical response to the external stimulation and highlight the brain network primarily involved in high-level coordination of the postural control system. The cortical network reconfiguration was assessed during two experimental conditions of eyes open and eyes closed and the network flexibility (i.e. its dynamic reconfiguration over time) was correlated with the sample entropy of the stabilogram sway. The results highlight two different cortical strategies in the alpha band: the predominance of frontal lobe connections during open eyes and the strengthening of temporal-parietal network connections in the absence of visual cues. Furthermore, a high correlation emerges between the flexibility in the regions surrounding the right temporo-parietal junction and the sample entropy of the CoP sway, suggesting their centrality in the postural control system. These results open the possibility to employ network-based flexibility metrics as markers of a healthy postural control system, with implications in the diagnosis and treatment of postural impairing diseases.

Publication DOI: https://doi.org/10.1109/TNSRE.2022.3140888
Divisions: College of Health & Life Sciences > School of Optometry > Optometry
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords: Band-pass filters,Brain Network Connectivity,EEG,Electroencephalography,Mathematical models,Muscles,Neuroscience,Postural Control,Task analysis,Vibrations,Internal Medicine,Neuroscience(all),Biomedical Engineering,Rehabilitation
Publication ISSN: 1558-0210
Full Text Link:
Related URLs: https://ieeexpl ... ocument/9672093 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-01-06
Published Online Date: 2022-01-06
Accepted Date: 2022-01-01
Authors: Barollo, Fabio
Hassan, Mahmoud
Petersen, Hannes
Rigoni, Isotta
Ramon, Ceon
Gargiulo, Paolo
Fratini, Antonio (ORCID Profile 0000-0001-8894-461X)

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