Background: Age-related changes affect driving ability, including the smoothness of driving. This operation requires the use of both allocentric strategies (based on world-centered representations) and egocentric strategies (based on self-centered representations); however, with age, a greater preference for egocentric strategies is evident when driving. Furthermore, an age-related decline occurs in both driving ability and spatial navigation. We therefore assessed the relationship between spatial navigation and driving smoothness and tested whether a driving simulator can be used to evaluate smooth lane changes in older drivers. Methods: A total of 34 healthy older drivers (mean age: 68.2 ± 5.4 years old) and 20 younger drivers (mean age = 20.2 ± 5.4 years old) participated in this study. The smoothness of driving was assessed using a driving simulator and spatial navigation was assessed using the Card-Placing Test-A/B. We also assessed visual perception and general intellectual function using standard neuropsychological tests. Results: Older drivers had significantly worse spatial navigation and exhibited less smooth driving than younger drivers. Furthermore, we found a negative correlation between the smoothness of driving and spatial navigation within both groups. These results suggest that the deterioration in spatial navigation in older people may underlie the observed decrease in driving smoothness, and that spatial navigation and smooth driving deteriorate with age. Conclusions: Considering these results, we found a significant correlation in the older group between the smoothness of vehicle movement and spatial navigation, in the smoothness of vehicle movement between the young and old groups. The smoothness values, which indices thoroughly derived from the driving simulator are indeed showing some evidence in ego/allocentric cognitions, which may change by age. The driving simulator could aid the development of intervention programs or assessment measures for drivers with a decreased function.

In the present study, we investigated the motor control of reaching finger movement interfered by the inhibitory intention triggered by the stop-signal. In the experiment, the subject started the reaching movement of the index finger with the go-signal of a green LED and stopped the ongoing movement with the stop-signal of a red LED. The stop-signal delay (SSD) was set at 0, 100, 200, 300 and 400 ms. The movement trajectory was measured during the task. The index finger was able to stop prior to the target point when SSD was less than 400 ms, whereas not when SSD was 400 ms. We also measured electroencephalogram (EEG) during the task. A negative peak around the stop-signal response time (SSRT) and a positive peak around 400-600 ms of the event-related potentials (ERPs) were observed at Fz and Cz. These results indicate that these components of the ERPs were associated with the stop-signal task in the human reaching movement.

It is hypothesized that suitable forces and postures of digits for holding an object are planned simultaneously based on the same motor criterion, using an internal representation of the object. To demonstrate the computational potential of this hypothesis, a neural network model for learning and planning forces and postures of digits in object holding tasks is proposed. Integrating visual 2D images of 9 objects that are different in size and orientation with forces and postures of digits, the neural network internally represents the size and the orientation of the objects and memorizes 5 motor patterns per object. Moreover, the neural network restores forces and postures in natural holding tasks according to the same motor strategy in which a norm of forces of digits is minimized. These results support the computational plausibility of our hypothesis.

Background/Objectives: People often engage in small, repetitive movements—or “fidgeting”—while listening. This behavior has traditionally been regarded as a sign of inattention. However, recent perspectives suggest that these movements may support engagement and arousal regulation. Yet, little is known about how different types of fidgeting affect the allocation of cognitive resources during auditory processing. This study examined whether hand and leg fidgeting influence pupil-linked arousal and auditory task performance. Methods: Young, healthy adults aged 18–26 years completed four auditory processing tasks while performing either hand fidgeting (manipulating a small fidget toy) or leg fidgeting (very light ergometer pedaling). A control group did not fidget. Pupil-linked arousal was assessed using changes in pupil diameter, and listening performance was evaluated across tasks of varying difficulty. Results: Both forms of fidgeting caused pupil dilation compared to the control group, particularly in the case of Hand Fidgeting during the listening task with speech in noise and the fast speech task. Despite these physiological changes, there were no measurable differences in auditory task performance across conditions. Conclusions: Fidgeting modulates pupil-linked arousal without impairing auditory processing in young, healthy adults. Hand fidgeting may help sustain engagement during demanding listening tasks. However, because the fidgeting was intentional and task performance approached ceiling or floor levels, these findings should be interpreted as preliminary. Future studies should examine whether fidgeting supports arousal maintenance or listening performance in individuals with attentional vulnerabilities or auditory processing difficulties.