Writer's cramp, or focal hand dystonia, is characterized by involuntary coactivation of antagonist or unnecessary muscles while writing or performing other tasks. Although the mechanism underlying this muscle overactivation is unknown, recent studies of changes in cerebral blood flow during writing have demonstrated a reduction in the activation of the primary motor cortex (MC) and hyperactivity of parts of the frontal non-primary motor areas. Therefore, any measures that decrease the activities of non-primary motor areas such as the premotor cortex (PMC) and the supplementary motor area (SMA) might improve dystonic symptoms. To explore this possibility, we studied nine patients with writer's cramp and seven age-matched control subjects, using subthreshold low-frequency (0.2 Hz) repetitive transcranial magnetic stimulation (rTMS), which exerts an inhibitory action on the cortex. Previous studies have demonstrated shortened cortical silent periods in dystonia, suggesting deficient cortical inhibition in the MC. We compared the silent periods and computer-assisted ratings of handwriting before and after rTMS applied to the MC, SMA or PMC. We also used the sham coil for control runs. Stimulation of the PMC but not the MC significantly improved the rating of handwriting (mean tracking error from the target, P = 0.004; pen pressure, P = 0.01) and prolonged the silent period (P = 0.02) in the patient group. rTMS over the other sites or using a sham coil in the patient group or trials in the control group revealed no physiological or clinical changes. This increased susceptibility of the PMC in dystonia suggests that the lack of inhibition in the MC is secondary to the hyperactivity of PMC neurons. Inhibition of the PMC using rTMS could provide a therapeutic measure of writer's cramp.

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Several behavioural studies have shown that the interplay between voice and face information in audiovisual speech perception is not universal. Native English speakers (ESs) are influenced by visual mouth movement to a greater degree than native Japanese speakers (JSs) when listening to speech. However, the biological basis of these group differences is unknown. Here, we demonstrate the time-varying processes of group differences in terms of event-related brain potentials (ERP) and eye gaze for audiovisual and audio-only speech perception. On a behavioural level, while congruent mouth movement shortened the ESs’ response time for speech perception, the opposite effect was observed in JSs. Eye-tracking data revealed a gaze bias to the mouth for the ESs but not the JSs, especially before the audio onset. Additionally, the ERP P2 amplitude indicated that ESs processed multisensory speech more efficiently than auditory-only speech; however, the JSs exhibited the opposite pattern. Taken together, the ESs’ early visual attention to the mouth was likely to promote phonetic anticipation, which was not the case for the JSs. These results clearly indicate the impact of language and/or culture on multisensory speech processing, suggesting that linguistic/cultural experiences lead to the development of unique neural systems for audiovisual speech perception.

Traffic accidents remain one of the most critical issues in many countries. One of the major causes of traffic accidents is drowsiness while driving. Since drowsiness is related to human physiological conditions, drowsiness is hard to prevent. Several studies have been conducted in assessing drowsiness, especially in a driving environment. One of the common methods used is the electroencephalogram (EEG). It is known that drowsiness occurs in the central nervous system; thus, estimating drowsiness using EEG is the promising way to assess drowsiness accurately. In this study, we tried to estimate drowsiness using frequency-domain and time-domain analysis of EEG. To validate the physiological conditions of the subjects, the Karolinska sleepiness scale (KSS), a subject-based assessment of drowsiness condition; and an examiner-based assessment known as facial expression evaluation (FEE) were applied. Three categories were considered; alert (KSS <; 6; FEE <; 1), weak drowsiness (KSS 6-7; FEE 1-2) and strong drowsiness (KSS > 7; FEE > 2). The six parameters (absolute and relative power of alpha, ratio of β/α and (θ+α)/β, and Hjorth activity and mobility parameters) had statistically significant differences between the three drowsiness conditions (P <; 0.001). By using both KSS and FEE, these parameters showed high accuracy in detecting drowsiness (up to 92.9%). Taken together, we suggest that EEG parameters can be used in detecting the three drowsiness conditions in a simulated driving environment.

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