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Human postural control is a multimodal process involving visual and vestibular information. The aim of the present study was to measure individual differences in the contributions of vision and vestibular senses to postural control, and to investigate if the individual weights could be modulated by long-term adaptation to visual motion or galvanic...
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... sways induced by visual and GVS motions. An example of postural sway induced by GVS for a trial of a subject is shown in Figure 4(a). We applied FFT to each trial data, and extracted postural-sway powers at the frequency of the visual or GVS motion (see Figure 4[b]). The postural sway of an observer typically occurs at the same frequency as the stimulus motion or modulation. We obtained two types of indexes for postural sway: center of gravity and head motion. However, as the results of these two indexes were similar, only the center of gravity data are presented. 3.3.1 Individual Differences. Postural-sway powers were presented at the same frequency of the stimulus motion for visual- and GVS-modality conditions (see Figure 5), and individual data ( n 1⁄4 24) were plotted to observe large individual differences. The individual differences were larger for visually-induced sways than for GVS-induced sways. The absolute power of the most sensitive participant was 1,000 times larger than less sensitive participants for vision, and 100 times larger for GVS. To determine the ratios of contributing weights of vision and vestibular for each subject’s postural control, correlations of visually-induced sways and GVS-induced sways were plotted (see Figure 6), where each dot represents a subject. Data were divided into three motion-fre- quency conditions. The horizontal axis indicates power of visually-induced postural sways at the stimulus frequency, and the vertical axis indicates power of GVS- induced sways. There were significant positive correlations between visually- and GVS-induced sways ( r 1⁄4 0.58 and p 1⁄4 .0030 for 0.1 Hz, r 1⁄4 0.52 and p 1⁄4 .0089 for 0.2 Hz, and r 1⁄4 0.53 and p 1⁄4 .0081 for 0.3 Hz). Thus, subjects who were sensitive to the visual motion were also sensitive to the GVS for the induced postural sway. Since many subjects were plotted in the upper-left side of the center oblique line, the GVS- induced sways were larger than the visually-induced sway for many subjects. Frequency. Data were normalized using the individual averages as absolute values of the postural sways were large. Normalized data (relative value to the individual average) are shown in Figure 7. Data are averages of all 24 participants with error bars of the standard errors. The GVS-induced postural sway was larger than the visually-induced postural sway, particularly at low frequencies. The GVS-induced sway decreased with a high frequency. A repeated measures ANOVA (two ways; two modalities  three frequencies) showed a significant main effect of the modality ( p 1⁄4 .0002) and the frequency ( p 1⁄4 .0087), and an interaction between them ( p 1⁄4 .0211). These data were identical to those presented in our previous study (Kitazaki & Kimura, 2008). Participants were randomly divided into four groups prior to pretests: the inhibiting body-movement- yoked vision group (six participants), the enhancing body-movement-yoked vision group (five participants), the inhibiting body-movement-yoked GVS group (seven participants), and the enhancing body-movement-yoked GVS group (six participants). The apparatus was identical to the pretests except that the force plate was excluded. The motion of each participant’s head was monitored by a motion tracker, and visual motion or GVS were continuously manipulated online depending on their motion at 60 Hz. In the enhancing vision adaptation, when the participant inclined rightward, the random dots moved rightward to induce more rightward postural sway (and vice versa). In the inhibiting vision adaptation, when the participant inclined rightward, the random dots moved leftward. For these two conditions, the manipulation of visual motion was the opposite. In the enhancing GVS adaptation, when the participant inclined rightward, the GVS induced a rightward postural sway. In the inhibiting GVS adaptation, when the participant inclined leftward, the GVS induced a rightward postural sway. For these two conditions, the manipulation of GVS was the opposite. Participants were asked to sway their body laterally back and forth with a 30 cm travel distance (15 cm left and right from the center) at 0.2 Hz. To guide this body motion, two vertical bars in red and green were presented on the screen (see Figure 8). The red bar moved left and right with sinusoidal speed modulation at 0.2 Hz. The green bar represented the current (online) position of the participant’s head. We asked participants to move the green bar on the red bar as accurately as possi- ble. Each trial continued for 60 s. Each subject performed 10 trials a day, and continued for 7 days. Thus, every participant performed 70 trials in total. The methods were identical to the pretest. All participants performed the same experiment. 5.2.1 Amplitude of Postural Sways. Identical analyses to those of the pretest were performed. Data were plotted for inhibiting vision (see Figure 9), enhancing vision (see Figures 10 and 11), inhibiting GVS (see Figure 12), and enhancing GVS (see Figures 13 and 14) groups. In Figures 9, 10, 12 and 13, the left graph represents pretest data of the same group subjects, while the center graph represents posttest data. To determine individual changes before and after the adaptation, the difference of the induced postural sway before and after the adaptation was calculated by subtracting the pretest data from the posttest data; these data are plotted in the right-side graph of Figures 9, 10, 12 and 13. There were no effects of the adaptation for the inhibiting vision adaptation condition (see Figure 9), while the visually-induced sway slightly increased and the GVS- induced sway decreased at low frequency (0.1 Hz) for the enhancing vision adaptation condition (see Figure 10). Repeated measures ANOVA for the data from Figure 9 (right) and Figure 10 (right) were performed to examine the effects of the adaptation (three ways: two adaptation groups  two modalities  three frequen- cies). There was a significant three-way interaction between adaptation (inhibiting/enhancing)  modality  frequency ( p 1⁄4 .0491), which supports the observa- tion that the enhancing vision adaptation only decreased GVS-induced sway and increased visually-induced sway at the low frequency. Single-sample t -tests were performed to test whether power changes of postural sways were different from zero for each condition; there was a near-significant effect suggesting that GVS-induced sway was decreased at 0.1 Hz ( p 1⁄4 .079). Next, paired t -tests were performed to test the difference between the GVS- induced sways and the visually-induced sways for each frequency condition; there was only a weak tendency for a difference between GVS- and visually-induced sways with the enhancing vision adaptation at 0.1 Hz ( p 1⁄4 .1441). For the 0.1 Hz condition of the enhancing vision group before and after the adaptation, each subject’s sway power was plotted to determine the visually- induced sways and GVS-induced sways (see Figure 11); these data were not normalized by individual averages. For four of the five subjects, contributing weights of vision increased while those of GVS decreased. For the inhibiting GVS adaptation condition, the GVS-induced sway increased particularly at the high frequency (0.3 Hz), while the visually-induced sway slightly decreased (see Figure 12). For the enhancing GVS adaptation condition, the GVS-induced sway slightly increased and the visually-induced sway decreased at the low frequency (see Figure 13). Repeated measures ANOVA for the data from Figure 12 (right) and 13 (right; three ways: two adaptation groups  two modalities  three frequencies) was performed to test the effects of the adaption; however, there were no effects as the individual differences were too large. Next, single-sample t -tests were performed to determine whether the power changes of postural sway were different from zero for each condition. There was a near-significant effect of increased GVS-induced sway at 0.3 Hz by inhibiting GVS adaptation ( p 1⁄4 .054). Paired t -tests were performed to test the difference between GVS-induced sway and visually-induced sway for each frequency condition. For the inhibiting GVS condition, there was a significant effect of the adaptation ( p 1⁄4 .026) at 0.3 Hz where the GVS-induced sway increased signifi- cantly more than the visually-increased sway. For the enhancing GVS condition, there was a near significant effect of the adaptation ( p 1⁄4 .060) at 0.1 Hz, where the GVS-induced sway increased more than the visually- induced sway. For the 0.3 Hz condition of the inhibiting GVS group and the 0.1 Hz condition of the enhancing GVS group before and after the adaptation, each subject’s sway power was plotted to determine ratios of the visually- induced sways and the GVS-induced sways (see Figures 14 and 15, respectively). For five of the seven subjects in the inhibiting GVS group, the contributing weights of GVS increased and those of vision decreased (see Figure 14). For three of the six subjects in the enhancing GVS group, contributing weights of GVS increased and those of vision decreased (see Figure 15). 5.2.2 Phase Delay of Postural Sways. The phases of postural sway at the same frequency of visual or GVS stimuli were calculated, and pretests, posttests, and their difference were plotted in Figures 16, 17, 18, and 19. Postural sway delays to stimulus motions, particularly GVS-induced sways, have a large delay for 30–120 8 (Kitazaki & Kimura, 2008), which may affect the delay of postural sways. Similar ANOVAs (three ways: two adaptation groups [inhibiting/enhancing]  two modalities  three frequencies) were performed for visual adaptations and GVS adaptations. Single-sample t -tests and paired t -tests were also performed, similar to the power/amplitude analysis. There was no effect of adaptation in the inhibiting vision group (see Figure 16). For the enhancing vision group, the delay of visually- induced sway ...
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... postural sway, particularly at low frequencies. The GVS-induced sway decreased with a high frequency. A repeated measures ANOVA (two ways; two modalities  three frequencies) showed a significant main effect of the modality ( p 1⁄4 .0002) and the frequency ( p 1⁄4 .0087), and an interaction between them ( p 1⁄4 .0211). These data were identical to those presented in our previous study (Kitazaki & Kimura, 2008). Participants were randomly divided into four groups prior to pretests: the inhibiting body-movement- yoked vision group (six participants), the enhancing body-movement-yoked vision group (five participants), the inhibiting body-movement-yoked GVS group (seven participants), and the enhancing body-movement-yoked GVS group (six participants). The apparatus was identical to the pretests except that the force plate was excluded. The motion of each participant’s head was monitored by a motion tracker, and visual motion or GVS were continuously manipulated online depending on their motion at 60 Hz. In the enhancing vision adaptation, when the participant inclined rightward, the random dots moved rightward to induce more rightward postural sway (and vice versa). In the inhibiting vision adaptation, when the participant inclined rightward, the random dots moved leftward. For these two conditions, the manipulation of visual motion was the opposite. In the enhancing GVS adaptation, when the participant inclined rightward, the GVS induced a rightward postural sway. In the inhibiting GVS adaptation, when the participant inclined leftward, the GVS induced a rightward postural sway. For these two conditions, the manipulation of GVS was the opposite. Participants were asked to sway their body laterally back and forth with a 30 cm travel distance (15 cm left and right from the center) at 0.2 Hz. To guide this body motion, two vertical bars in red and green were presented on the screen (see Figure 8). The red bar moved left and right with sinusoidal speed modulation at 0.2 Hz. The green bar represented the current (online) position of the participant’s head. We asked participants to move the green bar on the red bar as accurately as possi- ble. Each trial continued for 60 s. Each subject performed 10 trials a day, and continued for 7 days. Thus, every participant performed 70 trials in total. The methods were identical to the pretest. All participants performed the same experiment. 5.2.1 Amplitude of Postural Sways. Identical analyses to those of the pretest were performed. Data were plotted for inhibiting vision (see Figure 9), enhancing vision (see Figures 10 and 11), inhibiting GVS (see Figure 12), and enhancing GVS (see Figures 13 and 14) groups. In Figures 9, 10, 12 and 13, the left graph represents pretest data of the same group subjects, while the center graph represents posttest data. To determine individual changes before and after the adaptation, the difference of the induced postural sway before and after the adaptation was calculated by subtracting the pretest data from the posttest data; these data are plotted in the right-side graph of Figures 9, 10, 12 and 13. There were no effects of the adaptation for the inhibiting vision adaptation condition (see Figure 9), while the visually-induced sway slightly increased and the GVS- induced sway decreased at low frequency (0.1 Hz) for the enhancing vision adaptation condition (see Figure 10). Repeated measures ANOVA for the data from Figure 9 (right) and Figure 10 (right) were performed to examine the effects of the adaptation (three ways: two adaptation groups  two modalities  three frequen- cies). There was a significant three-way interaction between adaptation (inhibiting/enhancing)  modality  frequency ( p 1⁄4 .0491), which supports the observa- tion that the enhancing vision adaptation only decreased GVS-induced sway and increased visually-induced sway at the low frequency. Single-sample t -tests were performed to test whether power changes of postural sways were different from zero for each condition; there was a near-significant effect suggesting that GVS-induced sway was decreased at 0.1 Hz ( p 1⁄4 .079). Next, paired t -tests were performed to test the difference between the GVS- induced sways and the visually-induced sways for each frequency condition; there was only a weak tendency for a difference between GVS- and visually-induced sways with the enhancing vision adaptation at 0.1 Hz ( p 1⁄4 .1441). For the 0.1 Hz condition of the enhancing vision group before and after the adaptation, each subject’s sway power was plotted to determine the visually- induced sways and GVS-induced sways (see Figure 11); these data were not normalized by individual averages. For four of the five subjects, contributing weights of vision increased while those of GVS decreased. For the inhibiting GVS adaptation condition, the GVS-induced sway increased particularly at the high frequency (0.3 Hz), while the visually-induced sway slightly decreased (see Figure 12). For the enhancing GVS adaptation condition, the GVS-induced sway slightly increased and the visually-induced sway decreased at the low frequency (see Figure 13). Repeated measures ANOVA for the data from Figure 12 (right) and 13 (right; three ways: two adaptation groups  two modalities  three frequencies) was performed to test the effects of the adaption; however, there were no effects as the individual differences were too large. Next, single-sample t -tests were performed to determine whether the power changes of postural sway were different from zero for each condition. There was a near-significant effect of increased GVS-induced sway at 0.3 Hz by inhibiting GVS adaptation ( p 1⁄4 .054). Paired t -tests were performed to test the difference between GVS-induced sway and visually-induced sway for each frequency condition. For the inhibiting GVS condition, there was a significant effect of the adaptation ( p 1⁄4 .026) at 0.3 Hz where the GVS-induced sway increased signifi- cantly more than the visually-increased sway. For the enhancing GVS condition, there was a near significant effect of the adaptation ( p 1⁄4 .060) at 0.1 Hz, where the GVS-induced sway increased more than the visually- induced sway. For the 0.3 Hz condition of the inhibiting GVS group and the 0.1 Hz condition of the enhancing GVS group before and after the adaptation, each subject’s sway power was plotted to determine ratios of the visually- induced sways and the GVS-induced sways (see Figures 14 and 15, respectively). For five of the seven subjects in the inhibiting GVS group, the contributing weights of GVS increased and those of vision decreased (see Figure 14). For three of the six subjects in the enhancing GVS group, contributing weights of GVS increased and those of vision decreased (see Figure 15). 5.2.2 Phase Delay of Postural Sways. The phases of postural sway at the same frequency of visual or GVS stimuli were calculated, and pretests, posttests, and their difference were plotted in Figures 16, 17, 18, and 19. Postural sway delays to stimulus motions, particularly GVS-induced sways, have a large delay for 30–120 8 (Kitazaki & Kimura, 2008), which may affect the delay of postural sways. Similar ANOVAs (three ways: two adaptation groups [inhibiting/enhancing]  two modalities  three frequencies) were performed for visual adaptations and GVS adaptations. Single-sample t -tests and paired t -tests were also performed, similar to the power/amplitude analysis. There was no effect of adaptation in the inhibiting vision group (see Figure 16). For the enhancing vision group, the delay of visually- induced sway increased at the middle frequency (0.2 Hz; see Figure 17; single-sample t -test, p 1⁄4 .064; paired t test p 1⁄4 .076). However, there was no significant effect of the ANOVA. For the inhibiting GVS group, the delay of visually- induced sways increased at the high frequency (0.3 Hz; see Figure 18; single-sample t -test, p 1⁄4 .079). For the enhancing GVS group, the delay of visually-induced sway decreased at the middle frequency (0.2 Hz; see Figure 19; single-sample t -test, p 1⁄4 .090). For the ...
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... effect of the modality ( p 1⁄4 .0002) and the frequency ( p 1⁄4 .0087), and an interaction between them ( p 1⁄4 .0211). These data were identical to those presented in our previous study (Kitazaki & Kimura, 2008). Participants were randomly divided into four groups prior to pretests: the inhibiting body-movement- yoked vision group (six participants), the enhancing body-movement-yoked vision group (five participants), the inhibiting body-movement-yoked GVS group (seven participants), and the enhancing body-movement-yoked GVS group (six participants). The apparatus was identical to the pretests except that the force plate was excluded. The motion of each participant’s head was monitored by a motion tracker, and visual motion or GVS were continuously manipulated online depending on their motion at 60 Hz. In the enhancing vision adaptation, when the participant inclined rightward, the random dots moved rightward to induce more rightward postural sway (and vice versa). In the inhibiting vision adaptation, when the participant inclined rightward, the random dots moved leftward. For these two conditions, the manipulation of visual motion was the opposite. In the enhancing GVS adaptation, when the participant inclined rightward, the GVS induced a rightward postural sway. In the inhibiting GVS adaptation, when the participant inclined leftward, the GVS induced a rightward postural sway. For these two conditions, the manipulation of GVS was the opposite. Participants were asked to sway their body laterally back and forth with a 30 cm travel distance (15 cm left and right from the center) at 0.2 Hz. To guide this body motion, two vertical bars in red and green were presented on the screen (see Figure 8). The red bar moved left and right with sinusoidal speed modulation at 0.2 Hz. The green bar represented the current (online) position of the participant’s head. We asked participants to move the green bar on the red bar as accurately as possi- ble. Each trial continued for 60 s. Each subject performed 10 trials a day, and continued for 7 days. Thus, every participant performed 70 trials in total. The methods were identical to the pretest. All participants performed the same experiment. 5.2.1 Amplitude of Postural Sways. Identical analyses to those of the pretest were performed. Data were plotted for inhibiting vision (see Figure 9), enhancing vision (see Figures 10 and 11), inhibiting GVS (see Figure 12), and enhancing GVS (see Figures 13 and 14) groups. In Figures 9, 10, 12 and 13, the left graph represents pretest data of the same group subjects, while the center graph represents posttest data. To determine individual changes before and after the adaptation, the difference of the induced postural sway before and after the adaptation was calculated by subtracting the pretest data from the posttest data; these data are plotted in the right-side graph of Figures 9, 10, 12 and 13. There were no effects of the adaptation for the inhibiting vision adaptation condition (see Figure 9), while the visually-induced sway slightly increased and the GVS- induced sway decreased at low frequency (0.1 Hz) for the enhancing vision adaptation condition (see Figure 10). Repeated measures ANOVA for the data from Figure 9 (right) and Figure 10 (right) were performed to examine the effects of the adaptation (three ways: two adaptation groups  two modalities  three frequen- cies). There was a significant three-way interaction between adaptation (inhibiting/enhancing)  modality  frequency ( p 1⁄4 .0491), which supports the observa- tion that the enhancing vision adaptation only decreased GVS-induced sway and increased visually-induced sway at the low frequency. Single-sample t -tests were performed to test whether power changes of postural sways were different from zero for each condition; there was a near-significant effect suggesting that GVS-induced sway was decreased at 0.1 Hz ( p 1⁄4 .079). Next, paired t -tests were performed to test the difference between the GVS- induced sways and the visually-induced sways for each frequency condition; there was only a weak tendency for a difference between GVS- and visually-induced sways with the enhancing vision adaptation at 0.1 Hz ( p 1⁄4 .1441). For the 0.1 Hz condition of the enhancing vision group before and after the adaptation, each subject’s sway power was plotted to determine the visually- induced sways and GVS-induced sways (see Figure 11); these data were not normalized by individual averages. For four of the five subjects, contributing weights of vision increased while those of GVS decreased. For the inhibiting GVS adaptation condition, the GVS-induced sway increased particularly at the high frequency (0.3 Hz), while the visually-induced sway slightly decreased (see Figure 12). For the enhancing GVS adaptation condition, the GVS-induced sway slightly increased and the visually-induced sway decreased at the low frequency (see Figure 13). Repeated measures ANOVA for the data from Figure 12 (right) and 13 (right; three ways: two adaptation groups  two modalities  three frequencies) was performed to test the effects of the adaption; however, there were no effects as the individual differences were too large. Next, single-sample t -tests were performed to determine whether the power changes of postural sway were different from zero for each condition. There was a near-significant effect of increased GVS-induced sway at 0.3 Hz by inhibiting GVS adaptation ( p 1⁄4 .054). Paired t -tests were performed to test the difference between GVS-induced sway and visually-induced sway for each frequency condition. For the inhibiting GVS condition, there was a significant effect of the adaptation ( p 1⁄4 .026) at 0.3 Hz where the GVS-induced sway increased signifi- cantly more than the visually-increased sway. For the enhancing GVS condition, there was a near significant effect of the adaptation ( p 1⁄4 .060) at 0.1 Hz, where the GVS-induced sway increased more than the visually- induced sway. For the 0.3 Hz condition of the inhibiting GVS group and the 0.1 Hz condition of the enhancing GVS group before and after the adaptation, each subject’s sway power was plotted to determine ratios of the visually- induced sways and the GVS-induced sways (see Figures 14 and 15, respectively). For five of the seven subjects in the inhibiting GVS group, the contributing weights of GVS increased and those of vision decreased (see Figure 14). For three of the six subjects in the enhancing GVS group, contributing weights of GVS increased and those of vision decreased (see Figure 15). 5.2.2 Phase Delay of Postural Sways. The phases of postural sway at the same frequency of visual or GVS stimuli were calculated, and pretests, posttests, and their difference were plotted in Figures 16, 17, 18, and 19. Postural sway delays to stimulus motions, particularly GVS-induced sways, have a large delay for 30–120 8 (Kitazaki & Kimura, 2008), which may affect the delay of postural sways. Similar ANOVAs (three ways: two adaptation groups [inhibiting/enhancing]  two modalities  three frequencies) were performed for visual adaptations and GVS adaptations. Single-sample t -tests and paired t -tests were also performed, similar to the power/amplitude analysis. There was no effect of adaptation in the inhibiting vision group (see Figure 16). For the enhancing vision group, the delay of visually- induced sway increased at the middle frequency (0.2 Hz; see Figure 17; single-sample t -test, p 1⁄4 .064; paired t test p 1⁄4 .076). However, there was no significant effect of the ANOVA. For the inhibiting GVS group, the delay of visually- induced sways increased at the high frequency (0.3 Hz; see Figure 18; single-sample t -test, p 1⁄4 .079). For the enhancing GVS group, the delay of visually-induced sway decreased at the middle frequency (0.2 Hz; see Figure 19; single-sample t -test, p 1⁄4 .090). For the ...
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Citations
... Finally, the question of whether the proprioceptive weight remains constant during sway referencing is still open. Indeed, several research papers emphasize the importance of dynamic re-weighting to adapt to the environment have shown changes in sensory weights, such as up-weighting relevant sensory cues and down-weighting irrelevant ones [20,27]. Accordingly, during sway referencing, the weight of the irrelevant signals from the proprioceptive sensors may have been reduced. ...
Postural control characteristics have been proposed as a predictor of Motion Sickness (MS). However, postural adaptation to sensory environment changes may also be critical for MS susceptibility. In order to address this issue, a postural paradigm was used where accurate orientation information from body sensors could be lost and restored, allowing us to infer sensory re-weighting dynamics from postural oscillation spectra in relation to car-sickness susceptibility. Seventy-one participants were standing on a platform (eyes closed) alternating from static phases (proprioceptive and vestibular sensors providing reliable orientation cues) to sway referenced to the ankle-angle phases (proprioceptive sensors providing unreliable orientation cues). The power spectrum density (PSD) on a 10 s sliding window was computed from the antero-posterior displacement of the center of pressure. Energy ratios (ERs) between the high (0.7–1.3 Hz) and low (0.1–0.7 Hz) frequency bands of these PSDs were computed on key time windows. Results showed no difference between MS and non-MS participants following loss of relevant ankle proprioception. However, the reintroduction of reliable ankle signals led, for the non-MS participants, to an increase of the ER originating from a previously up-weighted vestibular information during the sway-referenced situation. This suggests inter-individual differences in re-weighting dynamics in relation to car-sickness susceptibility.
... There is considerable evidence that sensory re-weighting occurs after exposure to conditions where the normal relationships between sensory cues are disrupted experimentally. Kitazaki and Kimura (2010) reported down-weighting of vestibular cues in postural stabilization when the cues were rendered irrelevant for estimating spatial orientation of the body. Others have shown similar effects over a period of weeks (Dilda et al., 2014). ...
Sensory dynamics can be re-shaped by environmental interaction, allowing adaptation to altered or unfamiliar conditions that would otherwise provoke challenges for the central nervous system. One such condition occurs in virtual reality, where sensory conflict is thought to induce cybersickness. Although the sensory re-weighting process is likely to underlie adaptation to cybersickness, evidence of a link between sensory re-weighting dynamics and cybersickness is rare. Here, we characterize the relationship between sensory re-weighting in a balance control task and cybersickness. Participants were exposed to visual oscillation while standing in tandem stance. The sway path length of the center of pressure (COP) was measured and averaged for each level of visual oscillation, and a ratio was computed between high and low oscillation magnitudes to reflect the relative contributions of multiple sensory sources of information concerning balance control. Results showed a significant relationship between the magnitude dependency of sway and common sub-scales of cybersickness: disorientation [r(21) = 0.45, p = 0.028] and oculomotor discomfort [r(21) = 0.45, p = 0.033]. We conclude that participants who reported less cybersickness were better-able to down-weight visual information at high magnitude oscillations, thus demonstrating a lower dependency between sway and visual magnitude. The results confirm the utility of balance control as an indicator of cybersickness, and support the role of multisensory re-weighting in determining an individual's tolerance to VR applications.
... In many situations they provide largely redundant information so that loss of one is not critical. In situations where one sensory channel becomes critical for balance or another become false or unreliable, the CNS might selectively attend or ignore specific channels through a process of "reweighting" [2][3][4][5][6]. Current concepts of motor control are based on forward sensory and motor models [7][8] whereby the CNS responds to the sensed difference between the predicted sensory inflow for an action and the actual sensed inflow. ...
... When applied as a binaural bipolar stimulus it evokes a pattern of afferent firing that signals natural head rotation in roll [12][13]. When the CNS is repeatedly exposed to daily or weekly sessions of pseudorandom or sinusoidal vestibular stimulation, the stimulation initially causes severe postural disturbances, but this effect dissipates and balance returns to baseline levels after 7-8 sessions [2][3]. These results appear to reflect a reweighting of sensory inputs [2][3]. ...
... When the CNS is repeatedly exposed to daily or weekly sessions of pseudorandom or sinusoidal vestibular stimulation, the stimulation initially causes severe postural disturbances, but this effect dissipates and balance returns to baseline levels after 7-8 sessions [2][3]. These results appear to reflect a reweighting of sensory inputs [2][3]. Because vestibulo-ocular reflexes remain affected despite repeated exposure to these same artificial vestibular stimuli, reweighting likely involves slow cerebellar processes rather than actual changes at the level of the vestibular end-organs or reflexes [2]. ...
To determine how the vestibular sense controls balance, we used instantaneous head angular velocity to drive a galvanic vestibular stimulus so that afference would signal that head movement was faster or slower than actual. In effect, this changed vestibular afferent gain. This increased sway 4-fold when subjects (N = 8) stood without vision. However, after a 240 s conditioning period with stable balance achieved through reliable visual or somatosensory cues, sway returned to normal. An equivalent galvanic stimulus unrelated to sway (not driven by head motion) was equally destabilising but in this situation the conditioning period of stable balance did not reduce sway. Reflex muscle responses evoked by an independent, higher bandwidth vestibular stimulus were initially reduced in amplitude by the galvanic stimulus but returned to normal levels after the conditioning period, contrary to predictions that they would decrease after adaptation to increased sensory gain and increase after adaptation to decreased sensory gain. We conclude that an erroneous vestibular signal of head motion during standing has profound effects on balance control. If it is unrelated to current head motion, the CNS has no immediate mechanism of ignoring the vestibular signal to reduce its influence on destabilising balance. This result is inconsistent with sensory reweighting based on disturbances. The increase in sway with increased sensory gain is also inconsistent with a simple feedback model of vestibular reflex action. Thus, we propose that recalibration of a forward sensory model best explains the reinterpretation of an altered reafferent signal of head motion during stable balance.
Background:
The vestibular system encodes head motion in space which is naturally accompanied by other sensory cues. Electrical stimuli, applied across the mastoid processes, selectively activate primary vestibular afferents which has spurred clinical and biomedical applications of electrical vestibular stimulation (EVS). When properly matched to head motion, EVS may also manipulate the closed-loop relationship between actions and vestibular feedback to reveal the mechanisms of sensorimotor recalibration and learning.
New method:
We designed a portable, low-cost real-time EVS system using an Arduino microcontroller programmed through Simulink that provides electrical currents based on head angular motion. We used well-characterized vestibular afferent physiological responses to head angular velocity and electrical current to compute head-motion equivalent of real-time modulatory EVS currents. We also examined if our system induced recalibration of the vestibular system during human balance control.
Results:
Our system operated at 199.9997Hz(±0.005Hz) and delivered head-motion-equivalent electrical currents with ∼10ms delay. The output driving the current stimulator matched the implemented linear model for physiological vestibular afferent dynamics with minimal background noise (<0.2% of ±10V range). Participants recalibrated to the modulated closed-loop vestibular feedback using visual cues during standing balance, replicating earlier findings.
Comparison with existing methods:
EVS is typically used to impose external perturbations that are independent of one's own movement. We provided a solution using open-source hardware to implement a real-time, physiologybased, and task-relevant vestibular modulations using EVS.
Conclusions:
Our portable, low-cost vestibular modulation system will make physiological closed-loop vestibular manipulations more accessible thus encouraging novel investigations and biomedical applications of EVS.
Human perception and action adaptively change depending on everyday experiences of or exposures to sensory information in changing environments. I aimed to know how our perception-action system adapts and changes in modified virtual-reality (VR) environments, and investigated visuo-motor adaptation of position constancy in a VR environment, visual and vestibular postural control after 7-day adaptation to modified sensory stimulation, and learning of event related cortical potential during motor imagery for application to a brain-machine interface. I found that human perception system, perception-action coordination system, and underlying neural system could change to adapt a new environment with considering quantitative sensory-motor relationship, reliability of information, and required learning with real-time feedback. These findings may contribute to develop an adaptive VR system in a future, which can change adaptively and cooperatively with human perceptual adaptation and neural plasticity.
