Search

The worldwide outbreak of the COVID-19 virus puts the work and social life of citizens around the globe to a halt. During this time of crisis, digital media such as smartphones are a window to the world. Based on the mobileDNA data of 2778 Flemish adults, this report reveals that smartphones are key instruments to keep informed, stay in touch with loved ones and participate in the public sphere.

Social group influence plays an important role in societally relevant phenomena such as rioting and mass panic. One way through which groups influence individuals is by directing their gaze. Evidence that gaze following increases with group size has typically been explained in terms of strategic processes. Here, we instead tested the role of sensorimotor processes. In an ecologically valid virtual reality task, we found that participants were more likely to follow the gaze of a group when more people looked, even though they knew the group provided no relevant information. Interestingly, participants also sometimes changed their mind after starting to follow the gaze of the group, indicating that automatic imitation can be overruled by strategic processes. Our results suggest that social group influence is best explained by a two-step model in which bottom-up imitative processes first elicit a reflexive tendency to imitate, before top-down strategic processes determine whether to execute or inhibit this reflex. These results provide a deeper understanding of how group dynamics steer behavior.

How can we provide a positive user experience in our future smart spaces, given the strong growth of smart devices, each demanding attention with their own visual, auditory and tactile interactions? We will define a framework that is able to map the user experience journey in which all possible interactions between the user the products and the smart environment are measured in detail. In order to achieve this, we will create a Unity workspace to simulate smart environments by combining spatial audio, virtual reality and tactile interactions. In this workspace we will explore psychophysiological markers of the user’s personal experience of these interactions (blink rate, skin conductance and heart rate) and assess the practical feasibility for user evaluation. Furthermore we will setup a protocol to capture all relevant interactions that occur in the context of a smart environment based on our HCCI (Human Computer Context Interaction) framework. This will be implemented via a Proof of Concept based on the smart kitchen environment.

As it is adaptive to accurately detect and localize bodily threats, it has been proposed that the brain prioritizes somatosensory input at body locations where pain is expected. To test this proposition, the detection of tactile changes on a body location was investigated to assess whether detection was facilitated by threat of pain. Healthy participants (N = 47) indicated whether two consecutive patterns of three tactile stimuli were the same or not. Stimuli could be administered at eight possible locations. In half of the trials, the same pattern was presented twice. In the other half, one stimulus location was different between the two displays. To induce bodily threat, a painful stimulus was occasionally administered to the non-dominant lower arm. Mean accuracy of tactile change detection as a function of location was analyzed using repeated-measures analysis of variance (ANOVA). Tactile changes on the threatened arm (i.e., when a tactile stimulus emerged at or disappeared from that arm), both at the exact pain location (lower arm) and at the other location (upper arm), were better detected than tactile changes on other limbs.