Social and Emotional Effect on Human Behavior

A key function of morality is to regulate social behavior. Research suggests moral values may be divided into two types: binding values, which govern behavior in groups, and individualizing values, which promote personal rights and freedoms. Because people tend to mentally activate concepts in situations in which they may prove useful, the importance they afford moral values may vary according to whom they are with in the moment. In particular, because binding values help regulate communal behavior, people may afford these values more importance when in the presence of close (versus distant) others. Five studies test and support this hypothesis. First, we use a custom smartphone application to repeatedly record participants’ (n = 1166) current social context and the importance they afforded moral values. Results show people rate moral values as more important when in the presence of close others, and this effect is stronger for binding than individualizing values—an effect that replicates in a large preregistered online sample (n = 2016). A lab study (n = 390) and two preregistered online experiments (n = 580 and n = 752) provide convergent evidence that people afford binding, but not individualizing, values more importance when in the real or imagined presence of close others. Our results suggest people selectively activate different moral values according to the demands of the situation, and show how the mere presence of others can affect moral thinking.

Simple SummaryIt is widely recognized that the assessment of animal welfare should include measures of positive emotional (affective) state. Existing behavioral and physiological indicators of a positive affective state frequently lack sensitivity, objectivity or are unsuitable in a production environment. Therefore, there is a need to develop new approaches to accurately and objectively measure a positive emotional state in animals, including novel molecular markers such a miRNA. These biomarkers must be measurable in the peripheral circulation and provide an accurate account of the physiological and molecular activity in regions of the brain associated with emotional processing. Further, such markers require validation against established behavioral and physiological indices. Here we investigated the efficacy of circulating miRNA as biomarkers of emotional state in the pig.The ability to assess the welfare of animals is dependent on our ability to accurately determine their emotional (affective) state, with particular emphasis being placed on the identification of positive emotions. The challenge remains that current physiological and behavioral indices are either unable to distinguish between positive and negative emotional states, or they are simply not suitable for a production environment. Therefore, the development of novel measures of animal emotion is a necessity. Here we investigated the efficacy of microRNA (miRNA) in the brain and blood as biomarkers of emotional state in the pig. Female Large White × Landrace pigs (n = 24) were selected at weaning and trained to perform a judgment bias test (JBT), before being exposed for 5 weeks to either enriched (n = 12) or barren housing (n = 12) conditions. Pigs were tested on the JBT once prior to treatment, and immediately following treatment. MiRNA and neurotransmitters were analyzed in blood and brain tissue after euthanasia. Treatment had no effect on the outcomes of the JBT. There was also no effect of treatment on miRNA expression in blood or the brain (FDR p > 0.05). However, pigs exposed to enriched housing had elevated dopamine within the striatum compared to pigs in barren housing (p = 0.02). The results imply that either (a) miRNAs are not likely to be valid biomarkers of a positive affective state, at least under the type of conditions employed in this study, or (b) that the study design used to modify affective state was not able to create differential affective states, and therefore establish the validity of miRNA as biomarkers.

Human altruistic behaviors are heterogeneous across both contexts and people, whereas the neural signatures underlying the heterogeneity remain to be elucidated. To address this issue, we examined the neural signatures underlying the context- and person-dependent altruistic punishment, conjoining event-related fMRI with both task-based and resting-state functional connectivity (RSFC). Acting as an impartial third party, participants decided how to punish norm violators either alone or in the presence of putative others. We found that the presence of others decreased altruistic punishment due to diffusion of responsibility. Those behavioral effects paralleled altered neural responses in the dorsal anterior cingulate cortex (dACC) and putamen. Further, we identified modulation of responsibility diffusion on task-based functional connectivity of dACC with the brain regions implicated in reward processing (i.e., posterior cingulate cortex and amygdala/orbital frontal cortex). Finally, the RSFC results revealed that (i) increased intrinsic connectivity strengths of the putamen with temporoparietal junction and dorsolateral PFC were associated with attenuated responsibility diffusion in altruistic punishment and (ii) increased putamen-dorsomedial PFC connectivity strengths were associated with reduced responsibility diffusion in self-reported responsibility. Taken together, our findings elucidate the context- and person-dependent altruistic behaviors as well as associated neural substrates and thus provide a potential neurocognitive mechanism of heterogeneous human altruistic behaviors. Hum Brain Mapp 38:5535-5550, 2017. © 2017 Wiley Periodicals, Inc.

This study aims to analyze the influence of store environment on impulse buying behavior with emotional states as intervening variable using Mehrabian-Russell’s model. The store environment variables in this study include time availability, atmospheric factors, presence of others, and perceived crowdness. Using Mehrabian-Russell’s model, it is hypothesized that emotional state mediates the effects of store environment variables on impulse buying behavior as a dependent variable. The object in this study is Matahari Department Store in Yogyakarta. Sample of 166 respondents were selected by using purposive sampling method. Data were collected by using field survey technique. Normality, validity and reliability tests were conducted to test the quality of research instruments. The data analysis was conducted by using multiple linear regressions to test the research hypothesis. Results showed that atmospheric factors. as predicted, positively affect the emotional states. While perceived crowdness, consistent to the hypothesis, negatively affect the emotional states. The emotional states also positively affects the impulse buying behavior. The hypothesis of time availability and presence of others were not supported in this research. The findings of this research indicate that creating a proper atmospheric factors and creating a convenience store lay out to avoid crowdness are essential to stimulate impulse buying behavior.

Social grouping increases survival in many species, including humans1,2. By contrast, social isolation generates an aversive state (‘loneliness’) that motivates social seeking and heightens social interaction upon reunion3, 4–5. The observed rebound in social interaction triggered by isolation suggests a homeostatic process underlying the control of social need, similar to physiological drives such as hunger, thirst or sleep3,6. In this study, we assessed social responses in several mouse strains, among which FVB/NJ mice emerged as highly, and C57BL/6J mice as moderately, sensitive to social isolation. Using both strains, we uncovered two previously uncharacterized neuronal populations in the hypothalamic preoptic nucleus that are activated during either social isolation or social rebound and orchestrate the behaviour display of social need and social satiety, respectively. We identified direct connectivity between these two populations and with brain areas associated with social behaviour, emotional state, reward and physiological needs and showed that mice require touch to assess the presence of others and fulfil their social need. These data show a brain-wide neural system underlying social homeostasis and provide significant mechanistic insights into the nature and function of circuits controlling instinctive social need and for the understanding of healthy and diseased brain states associated with social context.

Food caching animals depend on their caches at times of low food availability. Because stored food is susceptible to being stolen or degraded, many species employ cache protection strategies such as ceasing caching in the presence of others or avoiding storing perishable items for long periods. Several species frequently recover their caches and recache, which may reduce pilferage or degradation of cached items. We studied the food handling decisions of Florida scrub-jays (Aphelocoma coerulescens) after cache recovery to determine the roles that social and ecological environments play in post-recovery decisions. Instead of reducing recaching in the presence of others, recovering jays flew away from the recovery site, allowing them to eat or recache a recovered item regardless of the social context. Microhabitat type and soil moisture of the recovery sites had a significant influence on whether recoveries were eaten or recached; most items that were recached had been recovered from bare sand sites or sites with low soil moisture. Taken together, our results suggest that food store management of Florida scrub-jays are unaffected by the social context, but are strongly affected by the habitat conditions that influence the quality of caches.

Commitment is a paradoxical feature of human behavior, often seen as both an irrational bias and a virtue for achieving goals. This study investigates its social roots, revealing how social contexts shape the strength, content, and timing of self-commitment, even in individual tasks. Through a series of game-like experiments, participants pursued one of two equally desirable goals via sequential actions under varied social conditions: alone in a private room (Experiment 1), alongside an optimal reinforcement learning (RL) agent (Experiment 2) or another human (Experiment 3) on a shared display, or alone with a mere passive observer present (Experiment 4). Our results demonstrate that (1) all social contexts consistently heightened self-commitment, underscoring its sensitivity to the public nature of tasks; (2) in parallel-play settings (Experiments 2 and 3), participants spontaneously inferred others' intentions and avoided selecting the same goal, despite instructions that such avoidance was unnecessary, suggesting that theory-of-mind (ToM) inference of another agent is spontaneously evoked to bias goal selection; and (3) Bayesian ToM modeling indicated that participants delayed revealing their intentions in parallel-play settings but not in the mere-presence condition, implying that spontaneous bargaining with a potential partner, rather than mere social presence, prompts more cautious commitment formation. These findings illuminate that, even in individual tasks, self-commitment is deeply intertwined with social context, influencing how people manage their goals and interactions with others.

Association between affect and cannabis use varies by social context

Simple SummaryEmotions or affective states recognition in farm animals is an underexplored research domain. Despite significant advances in animal welfare research, animal affective state computing through the development and application of devices and platforms that can not only recognize but interpret and process the emotions, are in a nascent stage. The analysis and measurement of unique behavioural, physical, and biological characteristics offered by biometric sensor technologies and the affiliated complex and large data sets, opens the pathway for novel and realistic identification of individual animals amongst a herd or a flock. By capitalizing on the immense potential of biometric sensors, artificial intelligence enabled big data methods offer substantial advancement of animal welfare standards and meet the urgent needs of caretakers to respond effectively to maintain the wellbeing of their animals.Farm animals, numbering over 70 billion worldwide, are increasingly managed in large-scale, intensive farms. With both public awareness and scientific evidence growing that farm animals experience suffering, as well as affective states such as fear, frustration and distress, there is an urgent need to develop efficient and accurate methods for monitoring their welfare. At present, there are not scientifically validated ‘benchmarks’ for quantifying transient emotional (affective) states in farm animals, and no established measures of good welfare, only indicators of poor welfare, such as injury, pain and fear. Conventional approaches to monitoring livestock welfare are time-consuming, interrupt farming processes and involve subjective judgments. Biometric sensor data enabled by artificial intelligence is an emerging smart solution to unobtrusively monitoring livestock, but its potential for quantifying affective states and ground-breaking solutions in their application are yet to be realized. This review provides innovative methods for collecting big data on farm animal emotions, which can be used to train artificial intelligence models to classify, quantify and predict affective states in individual pigs and cows. Extending this to the group level, social network analysis can be applied to model emotional dynamics and contagion among animals. Finally, ‘digital twins’ of animals capable of simulating and predicting their affective states and behaviour in real time are a near-term possibility.

Monitoring Affective Trajectories during Complex Learning Sidney D’Mello (sdmello@memphis.edu) Department of Computer Science, University of Memphis Memphis, TN 38152 USA Roger S. Taylor (rstaylor@memphis.edu) Institute for Intelligent Systems, University of Memphis Memphis, TN 38152 USA Art Graesser (a-graesser@memphis.edu) Department of Psychology, University of Memphis Memphis, TN 38152 USA A series of studies have recently explored the affective states that occur during complex learning. Studies by Graesser and his colleagues have collected online measures of affect, such as observations by trained judges and emote- aloud protocols, as well as offline judgments of emotions by multiple judges (Craig, et al., 2004; D’Mello et al., 2006; Graesser et al., 2006). These studies have revealed that the basic emotions identified by Ekman and Friesen (1978), namely anger, fear, sadness, joy, disgust, and surprise, typically do not play a significant role in learning (see also Kort Reilly, & Picard, 2001). Instead they documented a set of affective states that typically do play a significant role in learning, at least in the case of college students learning about computer literacy with an intelligent tutoring system. These affective states were boredom, flow (engagement, Csikszentmihalyi, 1990), confusion, and frustration. They also monitored the affective states of delight and surprise, which occurred less frequently. While some of these affective states might be viewed as purely cognitive in nature, our position is that they should be classified as affective states (or emotions) because these states are accompanied by significant changes in physiological arousal compared with a “neutral” state of no apparent emotion or feeling (Barrett, 2006; Meyer & Turner, in press; Stein & Hernandez, in press). Furthermore, affective-cognitive composites are particularly relevant to higher-order learning. The aforementioned set of affective states can be situated within a broader perspective of emotion, in particular Russell’s (2003) Core Affect framework. This perspective holds that an affective state is composed of two integrated components: valence (pleasure to displeasure) and arousal (activation to deactivation). These components can be depicted graphically with valence represented on the X-axis and arousal on the Y-axis. Moving from left to right along the X-axis (valence) would correspond to increasing feelings of pleasure. Moving upward along the Y-axis (arousal) would correspond to increasing feelings of activation and energy (see Figure 1). The affective states of boredom, flow, confusion, and frustration will be the primary focus of this paper. These affective states have been previously correlated with learning Abstract This study investigated the transitions between affective states (i.e., boredom, flow, confusion, frustration, delight, and surprise) during learning while college students were tutored in computer literacy by AutoTutor, an automated tutoring system with natural language dialogue. Videos of participants’ faces and the interaction histories were recorded and then played back for the participants to judge their own affective states. We developed a metric to measure the relative likelihood of transitioning from an affective state at time t i to a subsequent affective state at time t i+1 . Several significant trajectories between affective states were identified. Instructional implications are discussed in the context of an expanded version of a cognitive disequilibrium model. Keywords: Affective states; emotions; affect trajectories, affect sequencing; emotion dynamics; AutoTutor; learning; instruction. Introduction There is ample empirical evidence in the psychological literature that emotions (or affective states) are systematically influenced by the knowledge and goals of the learner, and vice versa (Mandler, 1984; Ortony, Clore, & Collins, 1988; Russell, 2003; Stein & Levine, 1991). As individuals interact in the social and physical world, they attempt to assimilate new information with existing knowledge schemas. When new or discrepant information is detected, a mismatch between input and knowledge occurs. Attention shifts to discrepant information, the autonomic nervous system increases in arousal, and the new information may modify the individual’s goals and knowledge. The learner experiences a variety of possible emotions, depending on the context, the amount of change, and whether important goals are blocked. However, this type of affective arousal that accompanies learning is still not well understood. For example, researchers have yet to narrow down the emotions that accompany deep level learning of conceptual material. The consequential impact of the emotions on knowledge acquisition and transfer is still not well understood.

PurposeDespite current advances in the domain, little is known about the dynamic nature of the value construct, specifically the manner in which value perceptions change over time during the higher education consumption experience. This paper aims to examine the impact that emotions (affective states) and knowledge (cognitive influences) have on changes to the give and get dimensions of value, the respective impact of these on satisfaction, and the latter's influence on intention to recommend.Design/methodology/approachThe study was conducted in the UK education domain. Data were collected through a matched sample of 66 students at two points in time (at the start of the course and half way through) during a one‐year postgraduate course. The PLS approach to structural equation modelling was employed to examine the relationships between the focal constructs.FindingsThe results indicate differential impact of knowledge and emotions on the value dimensions at the two time points. Emotions are more dominant at time 1, while at time 2 the impact of emotions and knowledge on the value dimensions is comparable. There is significant increase from time 1 to 2 in six of the examined relationships while the reverse is found for only one relationship. The influence of satisfaction on intention to recommend increases significantly from time 1 to 2.Originality/valueTo the knowledge of the authors, this research represents the first examination of value's temporal nature, in which the results provide empirical support for value as a dynamic phenomenon that is differentially influenced by cognitive and affective variables.

Human behavior is influenced by the presence of others, which scientists also call ‘the audience effect’. The use of social control to produce more cooperative behaviors may positively influence road use and safety. This study uses an online questionnaire to test how eyes images affect the behavior of pedestrians when crossing a road. Different eyes images of men, women and a child with different facial expressions -neutral, friendly and angry- were presented to participants who were asked what they would feel by looking at these images before crossing a signalized road. Participants completed a questionnaire of 20 questions about pedestrian behaviors (PBQ). The questionnaire was received by 1,447 French participants, 610 of whom answered the entire questionnaire. Seventy-one percent of participants were women, and the mean age was 35 ± 14 years. Eye images give individuals the feeling they are being observed at 33%, feared at 5% and surprised at 26%, and thus seem to indicate mixed results about avoiding crossing at the red light. The expressions shown in the eyes are also an important factor: feelings of being observed increased by about 10-15% whilst feelings of being scared or inhibited increased by about 5% as the expression changed from neutral to friendly to angry. No link was found between the results of our questionnaire and those of the Pedestrian Behavior Questionnaire (PBQ). This study shows that the use of eye images could reduce illegal crossings by pedestrians, and is thus of key interest as a practical road safety tool. However, the effect is limited and how to increase this nudge effect needs further consideration.

Human behaviour is not only influenced by the physical presence of others, but also implied social presence. This study examines the impact of awareness of being eye-tracked on eye movement behaviour in a laboratory setting. During a classic yes/no face recognition task, participants were made to believe that their eye movements were recorded (or not recorded) by eye trackers. Their looking patterns with and without the awareness of being eye-tracked were compared while perceiving social (faces, faces-and-bodies) and non-social (inanimate objects) video stimuli. Area-of-interest (AOI) analysis revealed that misinformed participants (who were not aware that their eye movements were being recorded) looked more at the body (chest and waist) compared to informed participants (who believed they were being eye-tracked), whereas informed participants fixated longer on the mouth and shorter on the eyes of female models than misinformed participants did. These findings highlight the potential impact of an awareness of being eye tracked on one’s eye movement pattern when perceiving a social stimulus. We conclude that even within laboratory settings an eye tracker may function as an implied social presence that leads individuals to modify their eye movement behaviour according to socially-derived inhibitory norms.

While many studies focus on segmental variation in Parkinsonian speech, little is known about prosodic modulations reflecting the ability to adapt to communicative demands in people with Parkinson's disease (PwPD). This type of prosodic modulation is important for social interaction, and it involves modifications in speech melody (intonational level) and articulation of consonants and vowels (segmental level). The present study investigates phonetic cues of prosodic modulations with respect to different focus structures in mild dysarthric PwPD as a function of levodopa. Acoustic and kinematic speech parameters of 25 PwPD were assessed in two motor conditions. Speech production data from PwPD were collected before (medication-OFF) and after levodopa intake (medication-ON) by means of 3-D electromagnetic articulography. On the acoustic level, intensity, pitch, and syllable durations were analyzed. On the kinematic level, movement duration and amplitude were investigated. Spatio-temporal modulations of speech parameters were examined and compared across three different prosodic focus structures (out-of-focus, broad focus, contrastive focus) to display varying speech demands. Overall, levodopa had beneficial effects on motor performance, speech loudness, and pitch modulation. Acoustic syllable durations and kinematic movement durations did not change, revealing no systematic effects of motor status on the temporal domain. In contrast, there were spatial modulations of the oral articulators: tongue tip movements were smaller and lower lip movements were larger in amplitude under levodopa, reflecting a more agile and efficient articulatory movement under levodopa. Thus, respiratory-phonatory functions and consonant production improved, while syllable duration and tongue body kinematics did not change. Interestingly, prominence marking strategies were comparable between the medication conditions under investigation, and in fact, appear to be preserved in mild dysarthric PwPD.

Emotion in action: When emotions meet motor circuits