Pain E-motion Faces Database (PEMF): Pain-related micro-clips for emotion research

The Empathy for Pain Stimuli System (EPSS): Development and preliminary validation

We present the Empathy for Pain Stimuli System (EPSS): a large-scale database of stimuli for studying people's empathy for pain. The EPSS comprises five sub-databases. First, the Empathy for Limb Pain Picture Database (EPSS-Limb) provides 68 painful and 68 non-painful limb pictures, exhibiting people's limbs in painful and non-painful situations, respectively. Second, the Empathy for Face Pain Picture Database (EPSS-Face) provides 80 painful and 80 non-painful pictures of people's faces being penetrated by a syringe or touched by a Q-tip. Third, the Empathy for Voice Pain Database (EPSS-Voice) provides 30 painful and 30 non-painful voices exhibiting either short vocal cries of pain or neutral interjections. Fourth, the Empathy for Action Pain Video Database (EPSS-Action_Video) provides 239 painful and 239 non-painful videos of whole-body actions. Finally, the Empathy for Action Pain Picture Database (EPSS-Action_Picture) provides 239 painful and 239 non-painful pictures of whole-body actions. To validate the stimuli in the EPSS, participants evaluated the stimuli using four different scales, rating pain intensity, affective valence, arousal, and dominance. The EPSS is available to download for free at https://osf.io/muyah/?view_only=33ecf6c574cc4e2bbbaee775b299c6c1 .

Development of the RIKEN database for dynamic facial expressions with multiple angles

The development of facial expressions with sensing information is progressing in multidisciplinary fields, such as psychology, affective computing, and cognitive science. Previous facial datasets have not simultaneously dealt with multiple theoretical views of emotion, individualized context, or multi-angle/depth information. We developed a new facial database (RIKEN facial expression database) that includes multiple theoretical views of emotions and expressers' individualized events with multi-angle and depth information. The RIKEN facial expression database contains recordings of 48 Japanese participants captured using ten Kinect cameras at 25 events. This study identified several valence-related facial patterns and found them consistent with previous research investigating the coherence between facial movements and internal states. This database represents an advancement in developing a new sensing system, conducting psychological experiments, and understanding the complexity of emotional events.

Neural mechanisms underlying attentional bias modification in fibromyalgia patients: a double-blind ERP study

There is a growing interest in the potential benefits of attentional bias modification (ABM) training in chronic pain patients. However, studies examining the effectiveness of ABM programs in fibromyalgia patients have demonstrated inconclusive effects on both behavioral indices and clinical symptoms. Additionally, underlying neural dynamics of ABM effects could yield new insights but remain yet unexplored. Current study, therefore, aims to investigate the effects of ABM training on known neural electrophysiological indicators of attentional bias to pain (P2, N2a). Thirty-two fibromyalgia patients were enrolled and randomly assigned to an ABM training (N = 16) or control (N = 16) condition (2 weeks duration). Within the ABM training condition participants performed five sessions consisting of a modified version of the dot-probe task in which patients were trained to avoid facial pain expressions, whereas in the control group participants performed five sessions consisting of a standard version of the dot-probe task. Potential ABM training effects were evaluated by comparing a single pre- and post-treatment session, in which event-related potentials (ERPs) were recorded in response to both facial expressions and target stimuli. Furthermore, patients filled out a series of self-report questionnaires assessing anxiety, depression, pain-related worrying, fear of pain, fatigue and pain status. After training, results indicated an overall reduction of the amplitude of the P2 component followed by an enhancement of N2a amplitude for the ABM condition compared to control condition. In addition, scores on anxiety and depression decreased in patients assigned to the training condition. However, we found no effects derived from the training on pain-related and fatigue status. Present study offers new insights related to the possible neural mechanisms underlying the effect of ABM training in fibromyalgia. Clinical trial (TRN: NCT05905159) retrospectively registered (30/05/2023).

Should I trust you? Investigating trustworthiness judgements of painful facial expressions

Past research indicates that patients' reports of pain are often met with skepticism and that observers tend to underestimate patients' pain. The mechanisms behind these biases are not yet fully understood. One relevant domain of inquiry is the interaction between the emotional valence of a stranger's expression and the onlooker's trustworthiness judgment. The emotion overgeneralization hypothesis posits that when facial cues of valence are clear, individuals displaying negative expressions (e.g., disgust) are perceived as less trustworthy than those showing positive facial expressions (e.g., happiness). Accordingly, we hypothesized that facial expressions of pain (like disgust) would be judged more untrustworthy than facial expressions of happiness. In two separate studies, we measured trustworthiness judgments of four different facial expressions (i.e., neutral, happiness, pain, and disgust), displayed by both computer-generated and real faces, via both explicit self-reported ratings (Study 1) and implicit motor trajectories in a trustworthiness categorization task (Study 2). Ratings and categorization findings partly support our hypotheses. Our results reveal for the first time that when judging strangers' facial expressions, both negative expressions were perceived as more untrustworthy than happy expressions. They also indicate that facial expressions of pain are perceived as untrustworthy as disgust expressions, at least for computer-generated faces. These findings are relevant to the clinical setting because they highlight how overgeneralization of emotional facial expressions may subtend an early perceptual bias exerted by the patient's emotional facial cues onto the clinician's cognitive appraisal process.