In this study, we attempted to observe changes in cognitive characteristics according to 3 intensity changes (Level 1: 0.25 gravity, Level 2: 0.38 gravity, Level 3: 1.3 gravity) at 8 vibration frequencies (10, 50, 100, 150, 200, 225, 250, 300 Hz). The subjects were twelve male (22.1 ± 0.6 years old) and twelve female (21.5 ± 0.8 years old) healthy, right-handed adults with normal cognitive abilities. An experimental trial consisted of a stimulation phase (0.1 sec) in which a vibration stimulus was presented and a rest phase (6 sec) in which no vibration stimulus was presented. A selected stimulus was presented on the first knuckle of the right index finger 5 times (trials). Cognitive characteristics scores according to changes in intensity at each frequency were sampled using a subjective assessment sheet consisting of eighteen items (“ticklish,” “shivery,” “push,” “convex,” “thick,” “numb,” “slow,” “fast,” “shallow,” “strike,” “weak,” “strong,” “dense,” “blunt,” “heavy,” “light,” “stab”, “no stimulus”). To identify the cognitive characteristics according to intensity changes by frequency, the 3 intensities were designated as variables, and a curve estimation regression analysis was performed. At 10 Hz, cognitive characteristics of ’blunt’ increased with the intensity, and ’weak’ decreased. In 100 and 225 Hz, increase or decrease in intensity led to opposite cognitive characteristics (‘weak-strong’ in 100 and 225 Hz, ‘light-heavy’ in 225 Hz). In 100 and 225 Hz, as the intensity increased, expressions on the sense of surface such as ’blunt’ were superior, and the shape of an object (thick) and dynamics (push) differed with the change in intensity. In addition, in 225 Hz, decrease in intensity led to increase in cognitive characteristics such as ’light’ and 'shallow. ’Fast’ was unique in that it only appeared as the intensity increased at 300 Hz.

This study aimed to determine the effects of the binaural beat (BB) on brainwave induction using an inaudible baseline frequency outside the audible frequency range. Experiments were conducted on 18 subjects (11 males [mean age: 25.7 ± 1.6 years] and 7 females [mean age: 24.0 ± 0.6 years]). A BB stimulation of 10 Hz was exerted by presenting frequencies of 18,000 Hz and 18,010 Hz to the left and right ears, respectively. A power spectrum analysis was performed to estimate the mean of the absolute power of the alpha frequency range (8–13 Hz). The variation in the mean alpha power during the rest and stimulation phases in each brain area was compared using the Wilcoxon signed-rank test. Compared to the rest phase, the stimulation phase with BB showed an increasing trend in the mean alpha power across all 5 brain areas. Notably, a significant increase was found in the frontal, central, and temporal areas. This is a significant study in that it determines the effects of only BB without the influence of auditory perception, which has been overlooked in previous studies.

This study investigates somatosensory evoked potential (SEP) patterns in the C3 somatosensory area with varying frequency and intensity of vibrotactile stimuli. The study subjects included 13 men ([Formula: see text] years) and seven women ([Formula: see text] years) who were right-handed and had normal cognitive function. The participants were subjected to three intensity levels (0.25, 0.38 and 1.3[Formula: see text]g) and eight frequencies (10, 50, 100, 150, 200, 225, 250 and 300[Formula: see text]Hz) of vibrotactile stimuli on the distal phalanx of their right index finger. The peak values of SEP patterns generated in response to high-frequency vibrotactile stimuli were greater than those generated because of low-frequency flutter. Moreover, the peak values increased as the stimulus intensity increased from 1[Formula: see text]g to 3[Formula: see text]g. In these results, the maximum and minimum peak, and peak to peak values of SEP pattern in the C3 somatosensory area increased with an increase in the stimulation intensity and frequency of the vibrotactile stimuli. Data on the SEP patterns generated in response to various frequencies and intensities of somatosensory stimuli and the development of relevant databases will elucidate the various clinical applications and applicable domains where SEP assessment can be beneficial.

This study aims to use functional magnetic resonance imaging (fMRI) to assess the effective connectivity between the regions of the brain activated when driving and performing a secondary task (addition task). The subjects used an MR-compatible driving simulator ㅊ to manipulate the driving wheel with both hands and control the pedals (accelerator and brake) with their right foot as if they were driving in an actual environment. Effective connectivity analysis was performed for three regions of the right and the left hemispheres with the highest z-scores, and six of the regions of the entire brain (right and left hemisphere) activated during driving by dynamic causal modeling (DCM). In the right hemisphere, a motor control pathway related to movement control for driving performance was discovered; in the left hemisphere, the pathways in the regions related to movement control for driving performance, starting with the region associated with the secondary task, were discovered. In the whole brain, connectivity was discovered in each of the right and left hemispheres. The motor network of declarative memory, which is the connectivity of the right thalamus, left lingual gyrus, and right precentral gyrus, was worth noting. These results seem meaningful, as they demonstrate the connectivity associated with the control of voluntary movement related to memory from human experience, although limited to driving tasks.

No abstract