Abstract
Balance impairment or the loss of balance control is one of the most debilitating consequences of Traumatic Brain Injury (TBI). The levels of balance impairment may not be necessarily associated with the severity level of TBI, which makes it more difficult to do the correlational analysis of the balance impairment and its neural underpinnings. Therefore, we conducted a study where we collected the neurophysiological data (EEG and EMG) during a balance control task on a computerized posturography platform in a group of 17 TBIs and 15 age-matched healthy controls. Further, to distinguish balance-impaired TBIs (BI-TBI) from non-impaired TBIs (BN-TBI), we stratified the level of balance impairment using the Berg Balance Scale, a functional outcome measure widely used in both research and clinical settings. We computed the brain functional connectivity features between different cortical regions of interest using the imaginary part of coherence in different frequency bands. These features are then studied in a mean-centered Partial Least Squares Correlation analysis, which is a data-driven framework with the advantage of handling more features than the number of samples, thus making it suitable for a small-sample study. Based on the nonparametric significance testing using permutation and bootstrap procedure, we noticed that theta-band connectivity strength in the following ROIs significantly contributed to distinguishing balance impaired from non-impaired population: left middle frontal gyrus, right precuneus, right precentral gyrus, bilateral middle occipital gyrus, right middle temporal gyrus, left superior frontal gyrus, left post-central gyrus, right paracentral lobule. The knowledge of specific neural regions associated with balance impairment helps better understand neural mechanisms of TBI-associated balance dysfunction and may guide the development of novel therapeutic strategies, including targeted noninvasive brain stimulation. Our future studies will investigate the effects of balance platform training on sensorimotor connectivity.
Competing Interest Statement
The authors have declared no competing interest.
