Time-dilation and time-contraction in an anisochronous and anisometric visual scenery

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Genetic algorithms reveal profound individual differences in emotion recognition.

Emotional communication relies on a mutual understanding, between expresser and viewer, of facial configurations that broadcast specific emotions. However, we do not know whether people share a common understanding of how emotional states map onto facial expressions. This is because expressions exist in a high-dimensional space too large to explore in conventional experimental paradigms. Here, we address this by adapting genetic algorithms and combining them with photorealistic three-dimensional avatars to efficiently explore the high-dimensional expression space. A total of 336 people used these tools to generate facial expressions that represent happiness, fear, sadness, and anger. We found substantial variability in the expressions generated via our procedure, suggesting that different people associate different facial expressions to the same emotional state. We then examined whether variability in the facial expressions created could account for differences in performance on standard emotion recognition tasks by asking people to categorize different test expressions. We found that emotion categorization performance was explained by the extent to which test expressions matched the expressions generated by each individual. Our findings reveal the breadth of variability in people's representations of facial emotions, even among typical adult populations. This has profound implications for the interpretation of responses to emotional stimuli, which may reflect individual differences in the emotional category people attribute to a particular facial expression, rather than differences in the brain mechanisms that produce emotional responses

Genetic algorithms reveal identity independent representation of emotional expressions.

People readily and automatically process facial emotion and identity, and it has been reported that these cues are processed both dependently and independently. However, this question of identity independent encoding of emotions has only been examined using posed, often exaggerated expressions of emotion, that do not account for the substantial individual differences in emotion recognition. In this study, we ask whether people's unique beliefs of how emotions should be reflected in facial expressions depend on the identity of the face. To do this, we employed a genetic algorithm where participants created facial expressions to represent different emotions. Participants generated facial expressions of anger, fear, happiness, and sadness, on two different identities. Facial features were controlled by manipulating a set of weights, allowing us to probe the exact positions of faces in high-dimensional expression space. We found that participants created facial expressions belonging to each identity in a similar space that was unique to the participant, for angry, fearful, and happy expressions, but not sad. However, using a machine learning algorithm that examined the positions of faces in expression space, we also found systematic differences between the two identities' expressions across participants. This suggests that participants' beliefs of how an emotion should be reflected in a facial expression are unique to them and identity independent, although there are also some systematic differences in the facial expressions between two identities that are common across all individuals. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Social synchronization of brain activity increases during eye-contact

Humans make eye-contact to extract information about other people’s mental states, recruiting dedicated brain networks that process information about the self and others. Recent studies show that eye-contact increases the synchronization between two brains but do not consider its effects on activity within single brains. Here we investigate how eye-contact affects the frequency and direction of the synchronization within and between two brains and the corresponding network characteristics. We also evaluate the functional relevance of eye-contact networks by comparing inter- and intra-brain networks of friends vs. strangers and the direction of synchronization between leaders and followers. We show that eye-contact increases higher inter- and intra-brain synchronization in the gamma frequency band. Network analysis reveals that some brain areas serve as hubs linking within- and between-brain networks. During eye-contact, friends show higher inter-brain synchronization than strangers. Dyads with clear leader/follower roles demonstrate higher synchronization from leader to follower in the alpha frequency band. Importantly, eye-contact affects synchronization between brains more than within brains, demonstrating that eye-contact is an inherently social signal. Future work should elucidate the causal mechanisms behind eye-contact induced synchronization

Social synchronization of brain activity increases during eye-contact

Copyright © The Author(s) 2022. Humans make eye-contact to extract information about other people’s mental states, recruiting dedicated brain networks that process information about the self and others. Recent studies show that eye-contact increases the synchronization between two brains but do not consider its effects on activity within single brains. Here we investigate how eye-contact affects the frequency and direction of the synchronization within and between two brains and the corresponding network characteristics. We also evaluate the functional relevance of eye-contact networks by comparing inter- and intra-brain networks of friends vs. strangers and the direction of synchronization between leaders and followers. We show that eye-contact increases higher inter- and intra-brain synchronization in the gamma frequency band. Network analysis reveals that some brain areas serve as hubs linking within- and between-brain networks. During eye-contact, friends show higher inter-brain synchronization than strangers. Dyads with clear leader/follower roles demonstrate higher synchronization from leader to follower in the alpha frequency band. Importantly, eye-contact affects synchronization between brains more than within brains, demonstrating that eye-contact is an inherently social signal. Future work should elucidate the causal mechanisms behind eye-contact induced synchronization.BIAL Foundation (No. 138/18); Leverhulme Trust Research Fellowship

Personality Traits Do Not Predict How We Look at Faces

While personality has typically been considered to influence gaze behaviour, literature relating to the topic is mixed. Previously, we found no evidence of self-reported personality traits on preferred gaze duration between a participant and a person looking at them via a video. In this study, 77 of the original participants answered an in-depth follow-up survey containing a more comprehensive assessment of personality traits (Big Five Inventory) than was initially used, to check whether earlier findings were caused by the personality measure being too coarse. In addition to preferred mutual gaze duration, we also examined two other factors linked to personality traits: number of blinks and total fixation duration in the eye region of observed faces. No significant correlations were found between any of these measures and participant personality traits. We suggest that effects previously reported in the literature may stem from contextual differences or modulation of arousal

Assumptions about the positioning of virtual stimuli affect gaze direction estimates during Augmented Reality based interactions

We investigated gaze direction determination in dyadic interactions mediated by an Augmented Reality (AR) head-mounted-display. With AR, virtual content is overlaid on top of the real-world scene, offering unique data visualization and interaction opportunities. A drawback of AR however is related to uncertainty regarding the AR user’s focus of attention in social-collaborative settings: an AR user looking in our direction might either be paying attention to us or to augmentations positioned somewhere in between. In two psychophysical experiments, we assessed what impact assumptions concerning the positioning of virtual content attended by an AR user have on other people’s sensitivity to their gaze direction. In the first experiment we found that gaze discrimination was better when the participant was aware that the AR user was focusing on stimuli positioned on their depth plane as opposed to being positioned halfway between the AR user and the participant. In the second experiment, we found that this modulatory effect was explained by participants’ assumptions concerning which plane the AR user was focusing on, irrespective of these being correct. We discuss the significance of AR reduced gaze determination in social-collaborative settings as well as theoretical implications regarding the impact of this technology on social behaviour

The geometrical nature of optical resonances : from a sphere to fused dimer nanoparticles

We study the electromagnetic response of smooth gold nanoparticles with shapes varying from a single sphere to two ellipsoids joined smoothly at their vertices. We show that the plasmonic resonance visible in the extinction and absorption cross sections shifts to longer wavelengths and eventually disappears as the mid-plane waist of the composite particle becomes narrower. This process corresponds to an increase of the numbers of internal and scattering modes that are mainly confined to the surface and coupled to the incident field. These modes strongly affect the near field, and therefore are of great importance in surface spectroscopy, but are almost undetectable in the far field

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