How Eye Movements Stabilize Posture in Patients With Bilateral Vestibular Hypofunction

Abstract

Chronic patients with bilateral vestibular hypofunction (BVH) complain of oscillopsia and great instability particularly when vision is excluded and on irregular surfaces. The real nature of the visual input substituting to the missing vestibular afferents and improving posture control remains however under debate. Is retinal slip involved? Do eye movements play a substantial role? The present study tends to answer this question in BVH patients by investigating their posture stability during quiet standing in four different visual conditions: total darkness, fixation of a stable space-fixed target, and pursuit of a visual target under goggles delivering visual input rate at flicker frequency inducing either slow eye movements (4.5 Hz) or saccades (1.2 Hz). Twenty one chronic BVH patients attested by both the caloric and head impulse test were examined by means of static posturography, and compared to a control group made of 21 sex-and age-matched healthy participants. The posturography data were analyzed using non-linear computation of the center of foot pressure (CoP) by means of the wavelet transform (Power Spectral Density in the visual frequency part, Postural Instability Index) and the fractional Brownian-motion analysis (stabilogram-diffusion analysis, Hausdorff fractal dimension). Results showed that posture stability was significantly deteriorated in darkness in the BVH patients compared to the healthy controls. Strong improvement of BVH patients' posture stability was observed during fixation of a visual target, pursuit with slow eye movements, and saccades, whereas the postural performance of the control group was less affected by the different visual conditions. It is concluded that BVH patients improve their posture stability by (1) using extraocular signals from eye movements (efference copy, muscle re-afferences) much more than the healthy participants, and (2) shifting more systematically than the controls to a more automatic mode of posture control when they are in dual-task conditions associating the postural task and a concomitant visuo- motor task.

Keywords: bilateral vestibular hypofunction patients; darkness; saccades; slow eye movements; static posturography; visual fixation.

Figure 1

Illustration of eye movements and postural performance in one representative BVH patient during the different visual conditions. (A). The BVH patient must pursuit a visual target moving sinusoidally in the horizontal plane (25° amplitude; 0.13 Hz frequency) in stroboscopic light at either the 4.5 Hz flicker frequency, which elicits slow eye movements (smooth pursuit: strob 1), or the 1.2 Hz flicker frequency, which induces saccadic eye movements (strob 2). (B). Comparison of the wavelet transform applied on the antero-posterior CoP displacements between the BVH patient (B1) and one representative healthy subject (B2) tested in total darkness. The wavelet analysis provides a 3D chart of body sway with time on the abscissae (in seconds), frequency content of the stabilogram on the ordinates (log scale in Hz), and spectral power density shown as a color code for the third dimension (expressed in decimal log). The Postural Instability Index (PII) and the spectral power density (PSD, expressed in decimal log) in the frequency range of the visual system (0.05–0.5 Hz), derived from the wavelet plots, show both higher values in the BVH patient (3.48 and 94.55, respectively) compared to the healthy control (1.32 and 72.40, respectively). (C). 3D chart of the antero-posterior sway of the BVH patient tested during visual fixation of the target (C1), tracking of the target with slow eye movements (C2: strob 1), and saccadic pursuit (C3: strob 2). Compared to the recording made in total darkness (B1), fixation, smooth pursuit, and saccades improve the BVH patient's postural stability, as shown by the strong reduction of the PII and SPD (1.84 and 82.08, 1.33 and 75.03, and 1.94 and 81.00 for the three visual conditions, respectively).

Figure 2

Illustration of the stabilogram-diffusion analysis and fractal analysis in one representative BVH patient and one representative healthy subject. (A). Stabilogram-diffusion analysis provides a linear-linear plot of mean square antero-posterior CoP displacement vs. time interval. Planar stabilogram plots show the critical point as the intersection of the two regression lines performed on the raw CoP displacements data. The critical point provides the critical time interval (abscissae: in seconds) and the critical mean square displacement (ordinates: Δr², in square millimeters). The critical time interval is similar in both the patient (upper graph) and the healthy subject (lower graph), while the critical mean square displacement is strongly increased in the BVH patient compared to the control (247.6 vs. 22.4 mm²). (B) Fractal analysis applied to the antero-posterior CoP displacements of the BVH patient (upper graph) and the healthy control (lower graph), illustrating the points in the samples (Hausdorff dimension) that are not correlated each other (in blue on the plots). These uncorrelated points illustrate the stochastic process in posture regulation, i.e., the events in the stabilogram which do not induce postural corrections (open loop or automatic control). The plots show a higher number of Hausdorff points in the control compared to the BVH patient, indicating a better postural stability in the control subject.

Figure 3

Effect of visual input and eye movements on posture stability in bilateral vestibular hypofunction patients and healthy participants. Mean results recorded in the population of BVH patients (N = 21: filled squares) and the control group (N = 21: open circles) in the four experimental visual conditions during quiet standing. (A) Mean postural instability index (±SD) derived from the wavelet transform recorded in darkness, during vision of a space-fixed target, eye pursuit of the sinusoidally moving visual target in the strob 1 condition (slow eye movements) and strob 2 condition (saccades). The vertical dashed arrow indicates significant differences in total darkness between the patients and the controls, while the heavy and light horizontal arrows show significant differences between darkness and the three other visual conditions in the patients and the controls, respectively. (B) Mean spectral power density (±SD) in the visual system frequency part (0.05–0.5 Hz), expressed in decimal logarithm and derived from the wavelet analysis. Same conventions as in (A). (C) Mean amplitude (±SD) of the critical point calculated with the stabilogram-diffusion analysis. Same conventions. (D) Mean Hausdorff frequency (±SD) derived from the fractal analysis. The frequency was evaluated by dividing the number of uncorrelated points by the recording time. A higher frequency indicates a better body stabilization. Note that all four parameters point to a better postural stability when BVH patients fixate a visual target, do slow eye movements or saccades by comparison with quiet standing in darkness. In contrast, the different visual conditions do not modify so drastically the postural parameters in the control group compared to the patients. ^*p < 0.05; ^**p < 0.01; ^***p < 0.001; ^****p < 0.0001.