Sensorimotor adaptation to Galvanic Vestibular Stimulation: a longitudinal study

Our previous study showed that exposure to Galvanic Vestibular Stimulation (GVS) induces temporary postural deficits similar to the ones experienced by astronauts after microgravity exposure. Preliminary evidence suggests that repeated exposures to GVS might induce adaptation of sway response. We studied whether repeated exposure to pseudorandom GVS over a 3 month period facilitates the adaptation response. Twenty healthy subjects were randomly assigned into 2 groups: suprathreshold (5mA) GVS, and subthreshold (1mA). The test battery included: Romberg, sensory organization test (posturography), dynamic visual acuity, and torsional eye movement. Each test was performed with no GVS, and then with 10 min of GVS per session for 12 consecutive weeks. Sensorimotor adaptation was also measured during two follow up sessions at weeks 18 and 36. Results showed that subthreshold GVS did not affect vestibular scores. Suprathreshold GVS significantly decreased vestibular scores during the first few weeks, with postural performance returning to baseline around the 6th week of exposure. This improvement was maintained during the follow up sessions. Our results suggest that 60 min of subthreshold GVS are sufficient to elicit adaptation to the stimulus. No significant changes were shown in low-level vestibulo-ocular reflexes during torsional eye movement, or vestibulo-spinal reflexes during Romberg; confirming that adaptation only occurs at the level of the CNS. NASA NCC 9-58; NNX09AL14G
Listed In: Biomechanical Engineering, Neuroscience, Posturography

Adaptive fractal analysis of postural sway

Fractal time series analysis methods are commonly used for analyzing center of pressure (COP) signals with the goal of revealing the underlying neuromuscular processes for upright stance control. The use of fractal methods is often coupled with the assumption that the COP is an instance of fractional Gaussian noise (fGn) or fractional Brownian motion (fBm). Our purpose was to evaluate the applicability of the fGn-fBm framework to the COP in light of several characteristics of COP signals revealed by a new method, adaptive fractal analysis (AFA; Riley et al., 2012). Our results showed that there are potentially three fractal scaling regions in the COP as opposed to one as expected from a pure fGn or fBm process. The scaling region at the fastest scale was anti-persistent and spanned ~30-90 msec, the intermediate was persistent and spanned ~200 msec-1.9 sec, and the slowest was anti-persistent and spanned ~5-40 sec. The intermediate fractal scaling region was the most clearly defined, but it only contributed around 11% of the total spectral energy of the COP signal, indicating that other features of the COP signal contribute more importantly to the overall dynamics. Also, more than half of the Hurst exponents estimated for the intermediate region were greater than the theoretically expected range [0,1] for fGn-fBm processes. These results suggest the fGn-fBm framework is not appropriate for modeling COP signals. ON-OFF intermittency might provide a better modeling framework for the COP, and multiscale approaches may be more appropriate for analyzing COP data.

Listed In: Neuroscience, Posturography