Selective social interactions and speed-induced leadership in schooling fish.

Animals moving together in groups are believed to interact among each other with effective social forces, such as attraction, repulsion, and alignment. Such forces can be inferred using "force maps," i.e., by analyzing the dependency of the acceleration of a focal individual on relevant variables. Here, we introduce a force map technique suitable for the analysis of the alignment forces experienced by individuals. After validating it using an agent-based model, we apply the force map to experimental data of schooling fish. We observe signatures of an effective alignment force with faster neighbors and an unexpected antialignment with slower neighbors. Instead of an explicit antialignment behavior, we suggest that the observed pattern is the result of a selective attention mechanism, where fish pay less attention to slower neighbors. This mechanism implies the existence of temporal leadership interactions based on relative speeds between neighbors. We present support for this hypothesis both from agent-based modeling as well as from exploring leader-follower relationships in the experimental data.

Individualized social niches in animals: Theoretical clarifications and processes of niche change.

What are social niches, and how do they arise and change? Our first goal in the present article is to clarify the concept of an individualized social niche and to distinguish it from related concepts, such as a social environment and a social role. We argue that focal individuals are integral parts of individualized social niches and that social interactions with conspecifics are further core elements of social niches. Our second goal in the present article is to characterize three types of processes-social niche construction, conformance, and choice (social NC3 processes)-that explain how individualized social niches originate and change. Our approach brings together studies of behavior, ecology, and evolution and integrates social niches into the broader concept of an individualized ecological niche. We show how clarifying the concept of a social niche and recognizing the differences between the three social NC3 processes enhance and stimulate empirical research.

Considering the 'With Whom': Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions.

Experience sampling studies often aim to capture social interactions. A central methodological question in such studies is whether to use event- or signal-contingent sampling. The little existing research on this issue has not taken into account that social interactions occur with unique interaction partners (e.g., Anna or Tom). We analyze one week of social interaction data of 286 students from the University of Pittsburgh (60.8% male, mean age 19.2 years), taking into account the unique interaction partners of each student. Specifically, we investigate the differences between event- and signal contingent sampling in (1) the total number of unique interaction partners captured, as well as (2) the kinds of relationships, and (3) the quality of social interactions with these captured interaction partners. Apart from a larger quantity of interactions and unique interaction partners in the event-contingent sampling design, our analyses indicate subtle differences between the two designs when aiming to assess social interactions with more distant interaction partners, such as coworkers or strangers. Most importantly, in our analyses, specific interaction partners and social roles explained a considerable amount of variance in the quality of social interactions (up to 20.5%), suggesting that future research would benefit greatly from considering "with whom" individuals interact.

The Impact of Screen Time on Sleep Patterns in School-Aged Children: A Cross-Sectional Analysis.

BACKGROUND: In a world filled with technology, there's concern about the impact of screen time on children and teenagers. A recent study of 11,875 children aged nine to 10 in the US explored how screen time affects mental health, behaviour, school performance, sleep, and friendships. The results indicate that more screen time is mildly linked to worse mental health, more behaviour problems, lower academic performance, and poorer sleep, but slightly better peer relationships. However, these connections were weak, with socioeconomic status (SES) having a stronger influence on these outcomes. The study doesn't prove that screen time causes these issues, suggesting that increased screen time might not be directly harmful to children in this age group. The research adds to the understanding of how screen time impacts children's well-being and highlights the importance of promoting healthy habits. Our study aims to add to this literature by examining how screen time impacts sleep quality, dream recall, and academic performance in school-aged children. Understanding the potential consequences of screen time is crucial for promoting healthy habits and ensuring the overall well-being of children. Our research seeks to provide further insights into the relationship between screen time and key aspects of children's lives as its prevalence continues to rise. METHODS: The research incorporates a cohort of 1000 school-aged children, bifurcated evenly into two categories based on their daily screen exposure: a low screen time group (less than one hour daily, n = 500) and a high screen time group (over three hours daily, n = 500). The study probes into the correlation between screen time and various health parameters, such as sleep patterns, dream recall, and academic prowess. RESULTS: The analysis showed that children with low screen time had better sleep efficiency (90% vs. 75%), more frequent dream recall (70% vs. 30%), fewer nocturnal awakenings (0.5 vs. 1.5 times weekly), less daytime sleepiness (20% vs. 60%), and higher physical activity levels (60 vs. 30 minutes per day) compared to those with high screen time. They also had less weekend sleep variability (1.2 hours) and a lower risk of circadian rhythm disturbances (20% increased risk in the high screen time group). Additionally, a screen-free bedroom was more common in the low screen time group (85% vs. 30%), and parental involvement in sleep routines was higher (90% vs. 40%). Academically, the low screen time group achieved higher grades ('A' to 'A+' vs. 'B'), and they had more face-to-face social interactions (two vs. one hour per day). CONCLUSION: Escalating screen time is correlated with detrimental impacts on sleep efficiency, dream recall, physical activity, circadian rhythms, and academic performance in school-aged children. Fostering a screen-free bedroom environment and augmenting parental involvement in sleep routines may alleviate these adverse effects.

Understanding the Interplay of Religion, Social Relationships, and Depressive Symptoms in Later Life: An Analysis of Dynamics in Individual and Dyadic Contexts.

This study examined how religious participation at the individual level and the dyadic religious similarity at the couple level influenced depressive symptoms via social relationships among older Korean couples aged 65 and above. The sample included 1,191 couples from the seventh assessment of the Korean Longitudinal Study of Ageing. The findings indicated that older adults who participated in religious activities more frequently showed lower levels of depressive symptoms through increased social interactions and marital satisfaction. Additionally, older couples with similar religious backgrounds showed higher levels of marital satisfaction than those without similar religious backgrounds, subsequently leading to lower levels of depressive symptoms. Overall, the associations between religion and depressive symptoms were similar for both genders. The findings provided insights into potential mechanisms leading to later-life depressive symptoms at both the individual and couple levels in terms of religion and social relationships and informed practical implications for older couples' marital relationships.

Natural parasites in conjunction with behavioral and color traits explain male agonistic behaviors in a lizard.

Male competition conforms to a cost-benefit model, because while aggression may increase reproductive prospects, it can also increase the risk of injury. We hypothesize that an additional cost in aggressive males would be an increase in parasite load associated with a high energy investment into sexual competition. Some of these infections, in turn, may downmodulate the level of host aggression via energetic trade-offs. We staged dyadic male contests in the lab to investigate the relationships of multiple parasites with the agonistic behavior of lizard hosts, Sceloporus occidentalis. We also included both color and behavioral traits from opponents in the analyses because (1) color patches of lizards may serve as intraspecific signals used by conspecifics to assess the quality of opponents, and (2) contests between male lizards fit classical models of escalated aggression, where lizards increase aggression displays in response to an opponent's behavior. The results conform to our hypothesis because male lizards displayed more pushups when they had more ticks. Moreover, some parasites may modulate the levels of aggression because lizards infected by hematic coccidians performed fewer pushups. Interestingly, lizards also displayed fewer pushups when both the chroma and size of the opponent's blue patch were greater. The results thus also supported the role of the blue patch of S. occidentalis as a sexual armament, because it contributed to the deterrence of aggression from opponent lizards. We revealed that natural parasitic infections in lizard hosts can contribute to their agonistic behavior. We encourage future studies to account for parasites in behavioral tests with lizards.

Predicting the long-term collective behaviour of fish pairs with deep learning.

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social interactions in the fish species Hemigrammus rhodostomus. We compare the results of our deep learning approach with experiments and with the results of a state-of-the-art analytical model. To that end, we propose a systematic methodology to assess the faithfulness of a collective motion model, exploiting a set of stringent individual and collective spatio-temporal observables. We demonstrate that machine learning (ML) models of social interactions can directly compete with their analytical counterparts in reproducing subtle experimental observables. Moreover, this work emphasizes the need for consistent validation across different timescales, and identifies key design aspects that enable our deep learning approach to capture both short- and long-term dynamics. We also show that our approach can be extended to larger groups without any retraining, and to other fish species, while retaining the same architecture of the deep learning network. Finally, we discuss the added value of ML in the context of the study of collective motion in animal groups and its potential as a complementary approach to analytical models.

Circadian Corticosterone Profile in Laying Hens (Gallus gallus domesticus).

Measurement of blood corticosterone concentrations has been established as an indicator for assessment of acute distress. Therefore, knowledge on physiological fluctuations is required, but previous studies allow little conclusion on daily fluctuations in domestic chickens (Gallus gallus domesticus). To verify the presence of a circadian corticosterone rhythm in socialized chickens, blood samples were taken at four-hour intervals from 12 laying hens kept in groups of four over three days, each. Prior to experiments, hens were adapted to repeated handling for stress reduction. Corticosterone concentration was determined using radioimmunoassay. Blood sampling time and duration were recorded, and audio and video recordings were analyzed to assess the impact of behavior on corticosterone concentrations. Despite individual fluctuations, most hens showed a circadian course with two peaks per day. Statistics revealed a significant peak during the day (between 12:00 p.m. and 04:00 p.m.) and a tendency for a second peak at night (12:00 a.m.). The daily corticosterone peak was not explained by daytime social stress and needs to be seen as an endophenotype. The role of nightly corticosterone production has to be investigated in further studies. There might be a relation between corticosterone and reproduction since the only hen not showing peaks was not laying eggs.

Patterns in Temporal Networks with Higher-Order Egocentric Structures.

The analysis of complex and time-evolving interactions, such as those within social dynamics, represents a current challenge in the science of complex systems. Temporal networks stand as a suitable tool for schematizing such systems, encoding all the interactions appearing between pairs of individuals in discrete time. Over the years, network science has developed many measures to analyze and compare temporal networks. Some of them imply a decomposition of the network into small pieces of interactions; i.e., only involving a few nodes for a short time range. Along this line, a possible way to decompose a network is to assume an egocentric perspective; i.e., to consider for each node the time evolution of its neighborhood. This was proposed by Longa et al. by defining the "egocentric temporal neighborhood", which has proven to be a useful tool for characterizing temporal networks relative to social interactions. However, this definition neglects group interactions (quite common in social domains), as they are always decomposed into pairwise connections. A more general framework that also allows considering larger interactions is represented by higher-order networks. Here, we generalize the description of social interactions to hypergraphs. Consequently, we generalize their decomposition into "hyper egocentric temporal neighborhoods". This enables the analysis of social interactions, facilitating comparisons between different datasets or nodes within a dataset, while considering the intrinsic complexity presented by higher-order interactions. Even if we limit the order of interactions to the second order (triplets of nodes), our results reveal the importance of a higher-order representation.In fact, our analyses show that second-order structures are responsible for the majority of the variability at all scales: between datasets, amongst nodes, and over time.

Direct reciprocity and reputation shape trust decisions similarly in blind and sighted individuals.

This study addresses the effects of blindness on trust. Using an auditory version of the multi-round Trust Game, we investigated the effect of reputation and reciprocity on trust decisions in early blind and sighted participants. During each round of the game, participants were endowed with a sum of money and had to decide how much they wanted to invest in their partners, who were manipulated as a function of their good or bad reputation and individualistic or cooperative behavior. The data showed that negative first impression about the partner (bad reputation and/or selfish behavior) impacted more blind participants than sighted ones. However, following repeated interactions with the partners, the overall mean investment aligned between the blind and sighted groups. We interpret these findings as suggesting that blindness may guide participants to a more cautionary behavior when dealing with partners with negative initial characteristics.

Within- and between-person associations between social interactions and loneliness: students' experiences during the COVID-19 pandemic.

The COVID-19 pandemic introduced many restrictions to in-person interactions, and remote social interactions may be especially important for managing loneliness when such restrictions are in place. However, it is unclear how social interactions are related to loneliness when in-person interactions are limited. Data were collected between February 2021 and March 2022 from a sample of 581 university students. Participants reported their loneliness and participation in positive in-person or remote social interactions each day for 14 days. Results from dynamic structural equation models showed that participants felt less lonely than they usually felt on the days they engaged in positive remote interactions at the within-person level. Moreover, participants generally felt less lonely when engaging more frequently in remote interactions, but only when in-person interactions were restricted (between-person level). Some of these results varied by changing COVID-19 restrictions. Finally, for participants who felt lonelier in general, the effect of positive in-person and remote interactions on loneliness was less strong. These findings suggest that social interactions may buffer loneliness but are not as impactful for those who experience greater loneliness.

Interpersonal motor synchrony in autism: a systematic review and meta-analysis.

Introduction: Interpersonal motor synchrony (IMS) is the spontaneous, voluntary, or instructed coordination of movements between interacting partners. Throughout the life cycle, it shapes social exchanges and interplays with intra- and inter-individual characteristics that may diverge in Autism Spectrum Disorder (ASD). Here we perform a systematic review and meta-analysis to summarize the extant literature and quantify the evidence about reduced IMS in dyads including at least one participant with a diagnosis of ASD. Methods: Empirical evidence from sixteen experimental studies was systematically reviewed, encompassing spontaneous and instructed paradigms as well as a paucity of measures used to assess IMS. Of these, thirteen studies (n = 512 dyads) contributed measures of IMS with an in situ neurotypical partner (TD) for ASD and control groups, which could be used for meta-analyses. Results: Reduced synchronization in ASD-TD dyads emerged from both the systematic review and meta-analyses, although both small and large effect sizes (i.e., Hedge's g) in favor of the control group are consistent with the data (Hedge's g = .85, p < 0.001, 95% CI[.35, 1.35], 95% PI[-.89, 2.60]). Discussion: Uncertainty is discussed relative to the type of task, measures, and age range considered in each study. We further discuss that sharing similar experiences of the world might help to synchronize with one another. Future studies should not only assess whether reduced IMS is consistently observed in ASD-TD dyads and how this shapes social exchanges, but also explore whether and how ASD-ASD dyads synchronize during interpersonal exchanges.

To avoid or not to avoid: impact of self-compassion on safety behaviors in social situations.

BACKGROUND/OBJECTIVES: Safety behaviors are commonly used to decrease anxiety in social settings but maintain anxiety. Self-compassion has been shown to reduce anxiety and rumination, but the impact on safety behaviors has not been examined. For the present studies, it was hypothesized that inducing self-compassion would lead to lower safety behaviors compared to controls. METHODS: In Study 1 (N = 390), participants with elevated social anxiety recalled a distressing social situation, were randomly assigned to a self-compassionate (n = 186) or control (n = 204) writing exercise, and then reported predicted self-compassion and safety behaviors for a future situation. In Study 2 (N = 114), the impact of self-compassionate (n = 56) or control writing (n = 58) on safety behaviors was investigated during a Zoom interaction. RESULTS/CONCLUSIONS: In Study 1, as hypothesized, the self-compassion condition reported fewer expected avoidance behaviors compared to controls. In Study 2, state self-compassion and safety behaviors did not differ between conditions. In both studies, distress significantly mediated the relationship between condition and safety behaviors, such that the self-compassion condition reported significantly lower distress, which was associated with lower safety behaviors. Future research can examine whether reduced distress and safety behaviors allow for greater social connection.

Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks.

Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. Digital phenotyping is a commonly used technology to assess a person's social behavior objectively. The experience sampling method (ESM) can capture the subjective perception of specific interactions. Lastly, egocentric networks are often used to measure specific relationship characteristics. These different methods capture different aspects of the social context over different time scales that are related to well-being, and combining them may be necessary to improve the prediction of well-being. Yet, they have rarely been combined in previous research. To address this gap, our study investigates the predictive accuracy of mood based on the social context. We collected intensive within-person data from multiple passive and self-report sources over a 28-day period in a student sample (Participants: N = 11, ESM measures: N = 1313). We trained individualized random forest machine learning models, using different predictors included in each model summarized over different time scales. Our findings revealed that even when combining social interactions data using different methods, predictive accuracy of mood remained low. The average coefficient of determination over all participants was 0.06 for positive and negative affect and ranged from - 0.08 to 0.3, indicating a large amount of variance across people. Furthermore, the optimal set of predictors varied across participants; however, predicting mood using all predictors generally yielded the best predictions. While combining different predictors improved predictive accuracy of mood for most participants, our study highlights the need for further work using larger and more diverse samples to enhance the clinical utility of these predictive modeling approaches.

The role of visual and auditory information in social event segmentation.

Humans organise their social worlds into social and nonsocial events. Social event segmentation refers to the ability to parse the environmental content into social and nonsocial events or units. Here, we investigated the role that perceptual information from visual and auditory modalities, in isolation and in conjunction, played in social event segmentation. Participants viewed a video clip depicting an interaction between two actors and marked the boundaries of social and nonsocial events. Depending on the condition, the clip at first contained only auditory or only visual information. Then, the clip was shown containing both auditory and visual information. Higher overall group consensus and response consistency in parsing the clip was found for social segmentation and when both auditory and visual information was available. Presenting the clip in the visual domain only benefitted group agreement in social segmentation while the inclusion of auditory information (under the audiovisual condition) also improved response consistency in nonsocial segmentation. Thus, social segmentation utilises information from the visual modality, with the auditory cues contributing under ambiguous or uncertain conditions and during segmentation of nonsocial content.

Everyday discrimination, emotion, and daily interactions during adolescence.

The present study examined whether everyday discrimination relates to the frequency of adolescents' positive and negative daily social interactions and whether these associations are driven by anger and positive emotion. Adolescents (N = 334) participated in a three-wave longitudinal study, in which they completed surveys regarding everyday discrimination, anger, and positive emotion, as well as 15 daily reports of conflict and getting along with friends and family. Higher everyday discrimination was related to more daily conflicts and fewer experiences of getting along with other people. Longitudinal models also provided preliminary evidence that everyday discrimination was associated with daily conflicts 4 years later indirectly through anger. Overall, results suggest everyday discrimination relates to adolescents' daily experiences, potentially through differences in emotion.

Involuntary social isolation and alcohol consumption: an ecological momentary assessment in Germany amid the COVID-19 pandemic.

AIMS: Alcohol consumption often occurs in a social setting, which was affected by social distancing measures amid the coronavirus disease-2019 (COVID-19) pandemic. In this study, we examine how involuntary social isolation (i.e. comparing a no-lockdown stage with a lockdown stage) affects the association between loneliness, social activities, and drinking behavior. METHOD: We performed an ecological momentary assessment eight times per day for 7 days amid the COVID-19 pandemic in Germany. We recruited 280 participants and assessed their trait loneliness, daily state loneliness, social activities, and drinking behaviors. RESULTS: We found that a lockdown condition moderates the association between trait and daily state loneliness and alcohol consumption. During a lockdown stage, trait loneliness was positively associated, whereas state loneliness was negatively associated with alcohol consumption. During a no-lockdown stage, trait and state loneliness were both negatively associated with alcohol consumption. For both no-lockdown and lockdown stages, duration of social interaction, male gender, and weekends was positively associated with alcohol consumption. CONCLUSION: Our study suggests that an involuntary social isolation condition (i.e. a lockdown stage) changes how trait loneliness is associated with alcohol consumption.

Human talkers change their voices to elicit specific trait percepts.

The voice is a variable and dynamic social tool with functional relevance for self-presentation, for example, during a job interview or courtship. Talkers adjust their voices flexibly to their situational or social environment. Here, we investigated how effectively intentional voice modulations can evoke trait impressions in listeners (Experiment 1), whether these trait impressions are recognizable (Experiment 2), and whether they meaningfully influence social interactions (Experiment 3). We recorded 40 healthy adult speakers' whilst speaking neutrally and whilst producing vocal expressions of six social traits (e.g., likeability, confidence). Multivariate ratings of 40 listeners showed that vocal modulations amplified specific trait percepts (Experiments 1 and 2), which could be explained by two principal components relating to perceived affiliation and competence. Moreover, vocal modulations increased the likelihood of listeners choosing the voice to be suitable for corresponding social goals (i.e., a confident rather than likeable voice to negotiate a promotion, Experiment 3). These results indicate that talkers modulate their voice along a common trait space for social navigation. Moreover, beyond reactive voice changes, vocal behaviour can be strategically used by talkers to communicate subtle information about themselves to listeners. These findings advance our understanding of non-verbal vocal behaviour for social communication.

Aggravation of cognitive impairments in the valproic acid-induced animal model of autism in BALB/c mice infected with Toxoplasma gondii.

PURPOSE: Toxoplasmosis is a disease caused by infection with a type of coccidial protozoan parasite called Toxoplasma gondii. The relationship between toxoplasmosis and cognitive disorders in neurodegenerative diseases has been proven. There is also evidence that children born to Toxoplasma-infected mothers are more likely to develop autism. METHODS: In the present study, Toxoplasma-infected pregnant BALB/c mice were given valproic acid to induce autism in their male offspring, and their social behaviors, learning, and memory were examined. Chronic toxoplasmosis was established in BALB/c mice by intraperitoneal injection of cyst form of T. gondii. To induce autism, 600 mg/kg of valproic acid was injected intraperitoneally into mice on the 12.5th day of pregnancy. The behavioral experiments, such as social interaction, novel object recognition, and passive avoidance tasks, were performed on male offspring at 50 days. RESULTS: Toxoplasma and valproic acid during the embryonic period caused social communication deficits and disrupted recognition memory and avoidance memory in offspring. Our findings showed that administering valproic acid to Toxoplasma-infected mothers exacerbates cognitive disorders in their offspring.