MS-related Spectral Changes

Figures 3-4 A-C reveal that the alpha power increases with the MS-level, especially

in the parietal lobe. This result is consistent with the results of a gravitational

experiment that was conducted by Cheron et al. (2006), who determined that 10Hz

oscillations in the parieto-occipital and sensorimotor areas increased as gravity was

removed. They also suggested that since the parietal lobe is situated at a transition

between the somatosensory and the motor cortex, it may therefore be involved in the

integration of spatial representation, which requires body sensation information from

vestibular inputs.

In the right and left motor areas, the increases in the theta band power are greater

than those in the delta, alpha and beta bands (Figs. 3-4 A and C). Such theta power

increases have also been recorded in numerous studies of motion-induced

motion-sickness. However, the brain areas that have been associated with the theta

power increases are not completely consistent. Wu (1992) reported theta power

increases in the frontal and central areas in a parallel swing study. Significant

MS-related theta power increases have been induced in the frontal areas using a

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rotating chair (Wood et al., 1991; Wood et al., 1994). However, Chelen et al. (1993)

reported theta power increases in the temporo-frontal in a cross-coupled angular

stimulation experiment.

The theta power increases can be referred to sensorimotor integration, which were

demonstrated in a way-finding VR experiment by Caplan et al. (2003). They found

theta oscillations in the peri-Rolandic regions and the temporal lobes were related to

(1) movement (both virtual and real), (2) updating the motor plan according to the

information collected from a multi-modal somatosensory system, and (3) coordinating

with the internal map during navigation. However, in the experiment in this study, the

subjects were instructed to report their motion-sickness levels using a joystick only.

The subjects had to report no further navigation information (such as number and

degree of turns and related information). Although the real turns may unavoidably

influence navigation function of the subjects, their effect should be relatively limited.

Moreover, the possibility of motion-induced theta power changes was eliminated by

removing the EEG power changes that were related to the baseline under the two

experimental conditions - baseline straight-road and baseline curve-road conditions.

Consequently, the theta power increases found in the two motor areas were caused

mainly by the integration of the multi-modal somatosensory information, which may

be essential to the motor planning of bodily movement in response to the motion of

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the platform during cruising on the curved road. Additionally, Caplan et al. (2003)

claimed that the effect of the theta power increase was asymmetric across the left and

right hemispheres. The power increase is more pronounced in the right hemisphere

than in the left. The results herein were consistent with their findings (Figs. 3-2B and

D). Bland & Oddie (2001) also developed the sensorimotor integration hypothesis,

according to which theta oscillations act to coordinate activity in various brain regions

to update motor plans in response to somatosensory inputs. Jensen (2001)

demonstrated that theta oscillations act as carrier waves for information transfer

between any pair of regions via synchronized oscillations at the same frequency.

In the occipital midline component cluster (Fig. 3-4E), component spectra

monotonically increased with the MS level in all frequency bands (delta, theta, alpha

and beta). Such a broadband power increase may indicate that motion-sickness can

strengthen the underlying brain processes, perhaps because of the difficulty of the task

during motion-sickness. This result may also indirectly demonstrate conflicts within

multi-modal somatosensory systems as they sense the environment around the subject,

causing the related brain circuits to work harder than at the baseline (no motion-sick

condition). According to the results of the correlation analysis (Fig. 3-5A), in the

occipital midline cluster, the EEG power responses in the occipital midline were more

highly correlated to subjective sickness-levels than in other brain areas, suggesting

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that activations in the occipital midline may be useful in determining the stages of

motion-sickness.

Although determinations by various studies of the brain regions that are involved in

motion-sickness remain inconclusive, many studies have presented delta power

increases. For example, an increase in delta-band power was observed at C3 and C4 in

an optokinetic rotating drum experiment (Hu et al., 1999) and in the frontal and

temporal areas in an object-finding VR experiment (Kim et al., 2005). A delta power

increase at Fz and Cz was also found in a VR-based car-driving experiment conducted

by Min et al. (2004). Furthermore, a delta power increase has also been reported in a

motion-induced motion-sickness study using cross-coupled angular stimulation

(Chelen et al., 1993). In that study, the delta power increase was detected over the

occipital, the occipital midline, and the right motor IC clusters (Fig. 3-4 C, D, and E),

mainly during the curved-road section (Fig. 3-3). This change in EEG power may be

treated as a stress component caused by the motion-sickness or violent movement of

the motion platform, as suggested by Chen et al. (1989).

The resultant spectral changes might be due to a confounding effect of moving a

joystick and motion sickness. However, the joystick movements were very sparse as

the subjects did not need to move the joystick unless they felt the level of motion

sickness has been changed. Previous studies (Huang et al., 2007; Huang et al., 2008)

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showed that the spectral changes following finger/hand movements in the sustained

attention tasks were usually transient (a quick spectral suppression followed by an

equal-amplitude rebound within 2-4 seconds). Furthermore, these spectral

perturbations would be the same regardless if the subject reported an increase or a

decrease in the sickness-level. Thus, the joystick movements would not have biased

the spectral correlates toward to a spectral increase or decrease systematically when

the correlation between the time course of component spectra and the subjective

sickness level was calculated in a much longer (smoothed) time scale.