The off-line effect of affective touch on multisensory integration and tactile perceptual accuracy during the somatic signal detection task

Affective touch refers to the emotional and motivational facets of tactile sensation and has been linked to the activation of a specialised system of mechanosensory afferents (the CT system), that respond optimally to slow caress-like touch. Affective touch has been shown to play an important role in the building of the bodily self: the multisensory integrated global awareness of one’s own body. Here we investigated the effects of affective touch on subsequent tactile awareness and multisensory integration using the Somatic Signal Detection Task (SSDT). During the SSDT, participants were required to detect near-threshold tactile stimulation on their cheek, in the presence/absence of a concomitant light. Participants repeated the SSDT twice, before and after receiving a touch manipulation. Participants were divided into two groups: one received affective touch (CT optimal; n = 32), and the second received non-affective touch (non-CT optimal; n = 34). Levels of arousal (skin conductance levels, SCLs) and mood changes after the touch manipulation were also measured. Affective touch led to an increase in tactile accuracy, as indicated by less false reports of touch and a trend towards higher tactile sensitivity during the subsequent SSDT. Conversely, non-affective touch was found to induce a partial decrease in the correct detection of touch possibly due to a desensitization of skin mechanoreceptors. Both affective and non-affective touch induced a more positive mood and higher SCLs in participants. The increase in SCLs was greater after affective touch. We conclude that receiving affective touch enhances the sense of bodily self therefore increasing perceptual accuracy and awareness. Higher SCLs are suggested to be a possible mediator linking affective touch to a greater tactile accuracy. Clinical implications are discussed.

Measuring the Efficiency of Automation-Aided Performance in a Simulated Baggage Screening Task

Objective The present study replicated and extended prior findings of suboptimal automation use in a signal detection task, benchmarking automation-aided performance to the predictions of several statistical models of collaborative decision making. Background Though automated decision aids can assist human operators to perform complex tasks, operators often use the aids suboptimally, achieving performance lower than statistically ideal. Method Participants performed a simulated security screening task requiring them to judge whether a target (a knife) was present or absent in a series of colored X-ray images of passenger baggage. They completed the task both with and without assistance from a 93%-reliable automated decision aid that provided a binary text diagnosis. A series of three experiments varied task characteristics including the timing of the aid’s judgment relative to the raw stimuli, target certainty, and target prevalence. Results and Conclusion Automation-aided performance fell closest to the predictions of the most suboptimal model under consideration, one which assumes the participant defers to the aid’s diagnosis with a probability of 50%. Performance was similar across experiments. Application Results suggest that human operators’ performance when undertaking a naturalistic search task falls far short of optimal and far lower than prior findings using an abstract signal detection task.

Visibility of an in-ground signal when texting while walking

An increase in pedestrian accidents associated with smartphone use has been one of the main issues in road traffic safety research and administration. Recently, traffic lights and safety signs embedded in the ground have been introduced, but without sufficient scientific consideration. A laboratory experiment evaluated the visibility of an in-ground signal while varying its contrast and position. Twenty-three participants performed a signal detection task when conducting texting while walking on a treadmill. The signals were displayed randomly onto the ground one at a time at three different positions with three different contrasts levels and moved towards a participant. In results, the approaching signals were detected 1.7 m ~ 2.9 m in front of participants, and there were significant differences in the visibility between contrast levels and positions (p<.01). The findings suggest the importance of proper contrast level and placement when installing in- ground signals for improving their visibility by smartphone users.

Neural divergence and convergence for attention to and detection of interoceptive and somatosensory stimuli

Body awareness is constructed by signals originating from within and outside the body. How do these apparently divergent signals converge? We developed a signal detection task to study the neural convergence and divergence of interoceptive and somatosensory signals. Participants focused on either cardiac or tactile events and reported their presence or absence. Beyond some evidence of divergence, we observed a robust overlap in the pattern of activation evoked across both conditions in frontal areas including the insular cortex, as well as parietal and occipital areas, and for both attention and detection of these signals. Psycho-physiological interaction analysis revealed that right insular cortex connectivity was modulated by the conscious detection of cardiac compared to somatosensory sensations, with greater connectivity to occipito-parietal regions when attending to cardiac signals. Our findings speak in favour of the inherent convergence of bodily-related signals and move beyond the apparent antagonism between exteroception and interoception.

Impact of COVID-19 exposure on punishment responsiveness

We investigate whether COVID-19 exposure changes participants’ threat-detection threshold. Sensitivity to threat was measured in a signal detection task among 397 British adults who also reported how much vulnerable they felt to infectious disease. Participants’ data were then matched to the number of confirmed COVID-19 collected from the NHS database. We found that participants who perceive themselves as more likely to catch infectious diseases displayed a higher negativity bias in response to increased COVID-19 cases. In addition, we found a significant effect of education on participants’ punishment responsiveness in response to COVID-19 exposure. A second wave of data collection is planned exactly two weeks after the first one. The goal of this second wave is to replicate the findings and document the impact of increasing COVID-19 cases and deaths on people’s psychology.

Collaborative Metacognition in Signal Detection Decision Making

When individuals work together to make decisions in a signal detection task, they typically achieve greater sensitivity as a group than they could each achieve on their own. The present experiments investigate whether metacognitive, or Type 2, signal detection judgements would show a similar pattern of collaborative benefit. Thirty-two participants in Experiment 1 and sixty participants in Experiment 2 completed a signal detection task individually and in groups, and measures of Type 1 and Type 2 sensitivity were calculated from participants’ confidence judgments. Bayesian parameter estimates suggested that regardless of whether teams are given feedback on their performance (Experiment 1) or receive no feedback (Experiment 2), no credible differences were observed in metacognitive efficiency between the teams and the better members, nor between the teams and the worse members. These findings suggest that teams may self-assess their performance by deferring metacognitive judgments to the most metacognitively sensitive individual within the team, even without trial-by-trial feedback, rather than integrating their judgments and achieving increased metacognitive awareness of their own performance.