Sub-Second Temporal Integration of Vibro-Tactile Stimuli: Intervals between Adjacent, Weak, and Within-Channel Stimuli Are Underestimated

Tactile estimation of sub-second time is essential for correct recognition of sensory inputs and dexterous manipulation of objects. Despite our intuitive understanding that time is robustly estimated in any situation, tactile sub-second time is altered by, for example, body movement, similar to how visual time is modulated by eye movement. The effects of simpler factors, such as stimulus location, intensity, and frequency, have also been reported in temporal tasks in other modalities, but their effects on tactile sub-second interval estimation remain obscure. Here, we were interested in whether a perceived short interval presented by tactile stimuli is altered only by changing stimulus features. The perceived interval between a pair of stimuli presented on the same finger apparently became short relative to that on different fingers; that of a weak-intensity pair relative to that of a pair with stronger intensity was decreased; and that of a pair with the same frequency relative to one with different frequencies was underestimated. These findings can be ascribed to errors in encoding temporal relationships: nearby-space/weak-intensity/similar-frequency stimuli presented within a short time difference are likely to be integrated into a single event and lead to relative time compression

Sense of resistance for a cursor moved by user’s keystrokes

Haptic sensation of a material can be modulated by its visual appearance. A technique that utilizes this visual-haptic interaction is called pseudo-haptic feedback. Conventional studies have investigated pseudo-haptic feedback in situations wherein a user manipulated a virtual object using a computer mouse, a force-feedback device, etc. The present study investigated whether and how it was possible to offer pseudo-haptic feedback to a user who manipulated a virtual object using keystrokes. Participants moved a cursor toward a destination by pressing a key. While the cursor was moving, the cursor was temporarily slowed down on a square area of the screen. The participants' task was to report, on a 5-point scale, how much resistance they felt to the cursor's movement. In addition to the basic speed of the cursor, the ratio of the basic speed to the speed within the square area was varied. In Experiment 1, we found that these two factors interacted significantly with each other, but further analysis showed that the cursor speed within the square area was the most important determinant of perceived resistance. In Experiment 2, consistent with the results of the previous experiment, it was found that the cursor movement outside of the square area was not required to generate the sense of resistance. Counterintuitively, in Experiment 3, the sense of resistance was apparent even without user's keystrokes. We discuss how the sense of resistance for a cursor moved by keystrokes can be triggered visually, but interpreted by the brain as a haptic impression

Tracking changes in touch desire and touch avoidance before and after the COVID-19 outbreak

Touch is essential for social interactions, environmental exploration, and wellbeing. However, human touch behavior has been greatly restricted by COVID-19 prevention measures, and this is expected to impact people’s attitude toward touch. Here we examined the transition of people’s touch desire and touch avoidance before and after the COVID-19 outbreak, using data from millions of public Twitter posts over an eight-year span. We found that people's desire for touching the human body and pet animals increased significantly after the COVID-19 outbreak and remained high afterward. In contrast, the avoidance of touching everyday objects increased immediately after the outbreak but gradually returned to the pre-COVID-19 levels. Our findings highlight the sign of “skin hunger”, a public health crisis due to social distancing, and call attention to the trend that people are becoming less aware of infection control as COVID-19 persists

Apparent time interval of visual stimuli is compressed during fast hand movement.

The influence of body movements on visual time perception is receiving increased attention. Past studies showed apparent expansion of visual time before and after the execution of hand movements and apparent compression of visual time during the execution of eye movements. Here we examined whether the estimation of sub-second time intervals between visual events is expanded, compressed, or unaffected during the execution of hand movements. The results show that hand movements, at least the fast ones, reduced the apparent time interval between visual events. A control experiment indicated that the apparent time compression was not produced by the participants' involuntary eye movements during the hand movements. These results, together with earlier findings, suggest hand movement can change apparent visual time either in a compressive way or in an expansive way, depending on the relative timing between the hand movement and visual stimulus

Schematic illustration of the experimental setup and time course.

<p>(A) Experimental setup. (B) Time course of a stimulus for the experimental conditions.</p

The PSEs and JNDs in the supplementary experiment (n = 3).

<p>Symbols indicate individual data points and error bars denote the 95% confidence interval calculated by bootstrap method [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124901#pone.0124901.ref022" target="_blank">22</a>]. The trials whose RMSE of eye movement exceeded the threshold were excluded from data analysis. The numbers at each data point indicate the rate of the number of sample data used to analyze all sample data (%). 100 (%) means that all 60 sample data were used in data analysis.</p

Psychometric functions for the four conditions obtained for participant T. Y.

<p>Filled circles and solid lines show the raw data and fitted psychometric curves, respectively.</p

The results in the main experiment (n = 7).

<p>(A) The means of the PSEs. Error bars denote the standard errors. (B) The means of the JNDs. Error bars denote the standard errors.</p