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Localizing EEG Recordings Associated With a Balance Threat During Unexpected Postural Translations in Young and Elderly Adults

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Abstract

Balance perturbations are accompanied by global cortical activation that increases in magnitude when postural perturbations are unexpected, potentially due to the addition of a startle response. A specific site for best recording the response to unexpected destabilization has not been identified. We hypothesize that a single sensor located near to subcortical brainstem mechanisms could serve as a marker for the response to unpredictable postural events. Twenty healthy young (20.8 ± 2.9 yrs) and 20 healthy elder (71.7 ± 4.2 yrs) adults stood upright on a dynamic platform with eyes open. Platform translations (20 cm at 100 cm/s) were delivered in the posterior (29 trials) and anterior (5 catch trials) directions. Active EEG electrodes were located at Fz and Cz and bilaterally on the mastoids. Following platform acceleration onset, 300 ms of EEG activity from each trial was detrended, baseline-corrected, and normalized to the first trial. Average Root-Mean-Square (RMS) values across "unpredictable" and "predictable" events were computed for each channel. EEG RMS responses were significantly greater with unpredictable than predictable disturbances: Cz ( [Formula: see text]), Fz ( [Formula: see text]), and mastoid ( [Formula: see text]). EEG RMS responses were also significantly greater in elderly than young adults at Cz ( [Formula: see text]) and mastoid ( [Formula: see text]). A significant effect of sex in the responses at the mastoid sensors ( [Formula: see text]) revealed that elderly male adults were principally responsible for the age effect. These results confirm that the cortical activity resulting from an unexpected postural disturbance could be portrayed by a single sensor located over the mastoid bone in both young and elderly adults.

Citing Articles

Real-Time Postural Disturbance Detection Through Sensor Fusion of EEG and Motion Data Using Machine Learning.

Wang Z, Noah A, Graci V, Keshner E, Griffith M, Seacrist T Sensors (Basel). 2024; 24(23).

PMID: 39686319 PMC: 11645098. DOI: 10.3390/s24237779.

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