Meditation has been practiced beginning of ancient times, and recently has gained more attention as something that can be utilized by anyone, regardless of their location, age, or gender for health benefits. The present study was aimed to produce some basic data on the effects of short-term meditation, as assessed by measuring brain waves during meditation, on 15 healthy Japanese students. Experiments were conducted with the subjects' eyes closed. After watching a meditation video (of about nine minutes duration), subjects took a three-minute break before practicing voiceless self meditation.Frequency analysis of brain waves of the subjects during the meditation revealed that the strength of α wave tends to increase during the meditation. In addition, the content rate of M1 (a + b) α waves during meditation tended to be higher than during the rest or recovery periods, although this difference was not statistically significant. The content rate of M2 (a + b) α waves during meditation was higher than that during rest, while that for Ύ waves was much lower than that during rest. Relative to that during recovery, the content rate during meditation was significantly lower for M2 α waves but significantly higher for Ύ waves. The α waves showed significantly more intermediate frequencies during M1 and M2 meditation as compared to those during the rest period, but fewer were noted during recovery. The LF/HF values, which reflect sympathetic nerve activity, were significantly higher during both M1 and M2 meditation than during the rest period. However, relative to that during recovery, LF/HF during M2 meditation was significantly lower.One limitation of the present study is that the meditation period was comparatively short. In addition, many of the subjects were also inexperienced in meditation, which may have created more variability in the results. However, the present study clearly demonstrates that repeated practice of meditation may improve subject's attention to task activities as well as the effectiveness of the neural network recruited for impulse control.