Temporal Taylor's scaling of facial electromyography and electrodermal activity in the course of emotional stimulation

High frequency psychophysiological data create a challenge for quantitative modeling based on Big Data tools since they reflect the complexity of processes taking place in human body and its responses to external events. Here we present studies of fluctuations in facial electromyography (fEMG) and electrodermal activity (EDA) massive time series and changes of such signals in the course of emotional stimulation. Zygomaticus major (ZYG, "smiling" muscle) activity, corrugator supercilii (COR, "frowning"bmuscle) activity, and phasic skin conductance (PHSC, sweating) levels of 65 participants were recorded during experiments that involved exposure to emotional stimuli (i.e., IAPS images, reading and writing messages on an artificial online discussion board). Temporal Taylor's fluctuations scaling were found when signals for various participants and during various types of emotional events were compared. Values of scaling exponents were close to 1, suggesting an external origin of system dynamics and/or strong interactions between system's basic elements (e.g., muscle fibres). Our statistical analysis shows that the scaling exponents enable identification of high valence and arousal levels in ZYG and COR signals

Opportunities and challenges for using automatic human affect analysis in consumer research

The ability to automatically assess emotional responses via contact-free video recording taps into a rapidly growing market aimed at predicting consumer choices. If consumer attention and engagement are measurable in a reliable and accessible manner, relevant marketing decisions could be informed by objective data. Although significant advances have been made in automatic affect recognition, several practical and theoretical issues remain largely unresolved. These concern the lack of cross-system validation, a historical emphasis of posed over spontaneous expressions, as well as more fundamental issues regarding the weak association between subjective experience and facial expressions. To address these limitations, the present paper argues that extant commercial and free facial expression classifiers should be rigorously validated in cross-system research. Furthermore, academics and practitioners must better leverage fine-grained emotional response dynamics, with stronger emphasis on understanding naturally occurring spontaneous expressions, and in naturalistic choice settings. We posit that applied consumer research might be better situated to examine facial behavior in socio-emotional contexts rather than decontextualized, laboratory studies, and highlight how AHAA can be successfully employed in this context. Also, facial activity should be considered less as a single outcome variable, and more as a starting point for further analyses. Implications of this approach and potential obstacles that need to be overcome are discussed within the context of consumer research

Psychophysiological responses to eye contact with a humanoid robot: Impact of perceived intentionality

Eye contact with a social robot has been shown to elicit similar psychophysiological responses to eye contact with another human. However, it is becoming increasingly clear that the attention- and affect-related psychophysiological responses differentiate between direct (toward the observer) and averted gaze mainly when viewing embodied faces that are capable of social interaction, whereas pictorial or pre-recorded stimuli have no such capability. It has been suggested that genuine eye contact, as indicated by the differential psychophysiological responses to direct and averted gaze, requires a feeling of being watched by another mind. Therefore, we measured event-related potentials (N170 and frontal P300) with EEG, facial electromyography, skin conductance, and heart rate deceleration responses to seeing a humanoid robot's direct versus averted gaze, while manipulating the impression of the robot's intentionality. The results showed that the N170 and the facial zygomatic responses were greater to direct than to averted gaze of the robot, and independent of the robot's intentionality, whereas the frontal P300 responses were more positive to direct than to averted gaze only when the robot appeared intentional. The study provides further evidence that the gaze behavior of a social robot elicits attentional and affective responses and adds that the robot's seemingly autonomous social behavior plays an important role in eliciting higher-level socio-cognitive processing.Peer reviewe

Factors associated with worse lung function in cystic fibrosis patients with persistent staphylococcus aureus

Background Staphylococcus aureus is an important pathogen in cystic fibrosis (CF). However, it is not clear which factors are associated with worse lung function in patients with persistent S. aureus airway cultures. Our main hypothesis was that patients with high S. aureus density in their respiratory specimens would more likely experience worsening of their lung disease than patients with low bacterial loads. Methods Therefore, we conducted an observational prospective longitudinal multi-center study and assessed the association between lung function and S. aureus bacterial density in respiratory samples, co-infection with other CF-pathogens, nasal S. aureus carriage, clinical status, antibiotic therapy, IL-6- and IgG-levels against S. aureus virulence factors. Results 195 patients from 17 centers were followed; each patient had an average of 7 visits. Data were analyzed using descriptive statistics and generalized linear mixed models. Our main hypothesis was only supported for patients providing throat specimens indicating that patients with higher density experienced a steeper lung function decline (p<0.001). Patients with exacerbations (n = 60), S. aureus small-colony variants (SCVs, n = 84) and co-infection with Stenotrophomonas maltophilia (n = 44) had worse lung function (p = 0.0068; p = 0.0011; p = 0.0103). Patients with SCVs were older (p = 0.0066) and more often treated with trimethoprim/sulfamethoxazole (p = 0.0078). IL-6 levels positively correlated with decreased lung function (p<0.001), S. aureus density in sputa (p = 0.0016), SCVs (p = 0.0209), exacerbations (p = 0.0041) and co-infections with S. maltophilia (p = 0.0195) or A. fumigatus (p = 0.0496). Conclusions In CF-patients with chronic S. aureus cultures, independent risk factors for worse lung function are high bacterial density in throat cultures, exacerbations, elevated IL-6 levels, presence of S. aureus SCVs and co-infection with S. maltophilia

The Glycan Shield of HIV Is Predominantly Oligomannose Independently of Production System or Viral Clade

The N-linked oligomannose glycans of HIV gp120 are a target for both microbicide and vaccine design. The extent of cross-clade conservation of HIV oligomannose glycans is therefore a critical consideration for the development of HIV prophylaxes. We measured the oligomannose content of virion-associated gp120 from primary virus from PBMCs for a range of viral isolates and showed cross-clade elevation (62–79%) of these glycans relative to recombinant, monomeric gp120 (∼30%). We also confirmed that pseudoviral production systems can give rise to notably elevated gp120 oligomannose levels (∼98%), compared to gp120 derived from a single-plasmid viral system using the HIVLAI backbone (56%). This study highlights differences in glycosylation between virion-associated and recombinant gp120

CYBEREMOTIONS – Collective Emotions in Cyberspace

AbstractEmotions are an important part of most societal dynamics. As with face to face meetings, Internet exchanges may not only include factual information but may also elicit emotional responses; how participants feel about the subject discussed or other group members. The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. We present results of two years of studies performed in the EU Large Scale Integrating Project CYBEREMOTIONS (Collective emotions in cyberspace) Our goal is to understand the role of collective emotions in creating, forming and breaking-up ICT mediated communities and to prepare the background for the next generation of emotionally-intelligent ICT services. Project results have already attracted a lot of attention from various mass media and research journals including the Science and New Scientist magazines. Nine Project teams are organised in three layers (data, theory and ICT output)

Human and machine validation of 14 databases of dynamic facial expressions

With a shift in interest toward dynamic expressions, numerous corpora of dynamic facial stimuli have been developed over the past two decades. The present research aimed to test existing sets of dynamic facial expressions (published between 2000 and 2015) in a cross-corpus validation effort. For this, 14 dynamic databases were selected that featured facial expressions of the basic six emotions (anger, disgust, fear, happiness, sadness, surprise) in posed or spontaneous form. In Study 1, a subset of stimuli from each database (N = 162) were presented to human observers and machine analysis, yielding considerable variance in emotion recognition performance across the databases. Classification accuracy further varied with perceived intensity and naturalness of the displays, with posed expressions being judged more accurately and as intense, but less natural compared to spontaneous ones. Study 2 aimed for a full validation of the 14 databases by subjecting the entire stimulus set (N = 3812) to machine analysis. A FACS-based Action Unit (AU) analysis revealed that facial AU configurations were more prototypical in posed than spontaneous expressions. The prototypicality of an expression in turn predicted emotion classification accuracy, with higher performance observed for more prototypical facial behavior. Furthermore, technical features of each database (i.e., duration, face box size, head rotation, and motion) had a significant impact on recognition accuracy. Together, the findings suggest that existing databases vary in their ability to signal specific emotions, thereby facing a trade-off between realism and ecological validity on the one end, and expression uniformity and comparability on the other