Hippocampal representation during collective spatial behaviour in bats.

Social animals live and move through spaces shaped by the presence, motion and sensory cues of multiple other individuals1-6. Neural activity in the hippocampus is known to reflect spatial behaviour7-9 yet its study is lacking in such dynamic group settings, which are ubiquitous in natural environments. Here we studied hippocampal activity in groups of bats engaged in collective spatial behaviour. We find that, under spontaneous conditions, a robust spatial structure emerges at the group level whereby behaviour is anchored to specific locations, movement patterns and individual social preferences. Using wireless electrophysiological recordings from both stationary and flying bats, we find that many hippocampal neurons are tuned to key features of group dynamics. These include the presence or absence of a conspecific, but not typically of an object, at landing sites, shared spatial locations, individual identities and sensory signals that are broadcasted in the group setting. Finally, using wireless calcium imaging, we find that social responses are anatomically distributed and robustly represented at the population level. Combined, our findings reveal that hippocampal activity contains a rich representation of naturally emerging spatial behaviours in animal groups that could in turn support the complex feat of collective behaviour.

Collective behavior from surprise minimization.

Collective motion is ubiquitous in nature; groups of animals, such as fish, birds, and ungulates appear to move as a whole, exhibiting a rich behavioral repertoire that ranges from directed movement to milling to disordered swarming. Typically, such macroscopic patterns arise from decentralized, local interactions among constituent components (e.g., individual fish in a school). Preeminent models of this process describe individuals as self-propelled particles, subject to self-generated motion and "social forces" such as short-range repulsion and long-range attraction or alignment. However, organisms are not particles; they are probabilistic decision-makers. Here, we introduce an approach to modeling collective behavior based on active inference. This cognitive framework casts behavior as the consequence of a single imperative: to minimize surprise. We demonstrate that many empirically observed collective phenomena, including cohesion, milling, and directed motion, emerge naturally when considering behavior as driven by active Bayesian inference-without explicitly building behavioral rules or goals into individual agents. Furthermore, we show that active inference can recover and generalize the classical notion of social forces as agents attempt to suppress prediction errors that conflict with their expectations. By exploring the parameter space of the belief-based model, we reveal nontrivial relationships between the individual beliefs and group properties like polarization and the tendency to visit different collective states. We also explore how individual beliefs about uncertainty determine collective decision-making accuracy. Finally, we show how agents can update their generative model over time, resulting in groups that are collectively more sensitive to external fluctuations and encode information more robustly.

The impact of threshold decision mechanisms of collective behavior on disease spread.

Humans are a hyper-social species, which greatly impacts the spread of infectious diseases. How do social dynamics impact epidemiology and what are the implications for public health policy? Here, we develop a model of disease transmission that incorporates social dynamics and a behavior that reduces the spread of disease, a voluntary nonpharmaceutical intervention (NPI). We use a "tipping-point" dynamic, previously used in the sociological literature, where individuals adopt a behavior given a sufficient prevalence of the behavior in the population. The thresholds at which individuals adopt the NPI behavior are modulated by the perceived risk of infection, i.e., the disease prevalence and transmission rate, costs to adopt the NPI behavior, and the behavior of others. Social conformity creates a type of "stickiness" whereby individuals are resistant to changing their behavior due to the population's inertia. In this model, we observe a nonmonotonicity in the attack rate as a function of various biological and social parameters such as the transmission rate, efficacy of the NPI, costs of the NPI, weight of social consequences of shirking the social norm, and the degree of heterogeneity in the population. We also observe that the attack rate can be highly sensitive to these parameters due to abrupt shifts in the collective behavior of the population. These results highlight the complex interplay between the dynamics of epidemics and norm-driven collective behaviors.

Kin-recognition and predation shape collective behaviors in the cannibalistic nematode Pristionchus pacificus.

Kin-recognition is observed across diverse species forming an important behavioral adaptation influencing organismal interactions. In many species, the molecular mechanisms involved are difficult to characterize, but in the nematode Pristionchus pacificus molecular components regulating its kin-recognition system have been identified. These determine its predatory behaviors towards other con-specifics which prevents the killing and cannibalization of kin. Importantly, their impact on other interactions including collective behaviors is unknown. Here, we explored a high altitude adapted clade of this species which aggregates abundantly under laboratory conditions, to investigate the influence of the kin-recognition system on their group behaviours. By utilizing pairwise aggregation assays between distinct strains of P. pacificus with differing degrees of genetic relatedness, we observe aggregation between kin but not distantly related strains. In assays between distantly related strains, the aggregation ratio is frequently reduced. Furthermore, abolishing predation behaviors through CRISPR/Cas9 induced mutations in Ppa-nhr-40 result in rival strains successfully aggregating together. Finally, as Caenorhabditis elegans are found naturally occurring with P. pacificus, we also explored aggregation events between these species. Here, aggregates were dominated by P. pacificus with the presence of only a small number of predators proving sufficient to disrupt C. elegans aggregation dynamics. Thus, aggregating strains of P. pacificus preferentially group with kin, revealing competition and nepotism as previously unknown components influencing collective behaviors in nematodes.

When do stereotypes undermine indirect reciprocity?

Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.

How local partisan context conditions prosocial behaviors: Mask wearing during COVID-19.

Does local partisan context influence the adoption of prosocial behavior? Using a nationwide survey of 60,000 adults and geographic data on over 180 million registered voters, we investigate whether neighborhood partisan composition affects a publicly observable and politicized behavior: wearing a mask. We find that Republicans are less likely to wear masks in public as the share of Republicans in their zip codes increases. Democratic mask wearing, however, is unaffected by local partisan context. Consequently, the partisan gap in mask wearing is largest in Republican neighborhoods, and less apparent in Democratic areas. These effects are distinct from other contextual effects such as variations in neighborhood race, income, or education. In contrast, partisan context has significantly reduced influence on unobservable public health recommendations like COVID-19 vaccination and no influence on nonpoliticized behaviors like flu vaccination, suggesting that differences in mask wearing reflect the publicly observable and politicized nature of the behavior instead of underlying differences in dispositions toward medical care.

Functional duality in group criticality via ambiguous interactions.

Critical phenomena are wildly observed in living systems. If the system is at criticality, it can quickly transfer information and achieve optimal response to external stimuli. Especially, animal collective behavior has numerous critical properties, which are related to other research regions, such as the brain system. Although the critical phenomena influencing collective behavior have been extensively studied, two important aspects require clarification. First, these critical phenomena never occur on a single scale but are instead nested from the micro- to macro-levels (e.g., from a Lévy walk to scale-free correlation). Second, the functional role of group criticality is unclear. To elucidate these aspects, the ambiguous interaction model is constructed in this study; this model has a common framework and is a natural extension of previous representative models (such as the Boids and Vicsek models). We demonstrate that our model can explain the nested criticality of collective behavior across several scales (considering scale-free correlation, super diffusion, Lévy walks, and 1/f fluctuation for relative velocities). Our model can also explain the relationship between scale-free correlation and group turns. To examine this relation, we propose a new method, applying partial information decomposition (PID) to two scale-free induced subgroups. Using PID, we construct information flows between two scale-free induced subgroups and find that coupling of the group morphology (i.e., the velocity distributions) and its fluctuation power (i.e., the fluctuation distributions) likely enable rapid group turning. Thus, the flock morphology may help its internal fluctuation convert to dynamic behavior. Our result sheds new light on the role of group morphology, which is relatively unheeded, retaining the importance of fluctuation dynamics in group criticality.

Description of the Collective Behavior in Competition of Young Soccer Players Under-16 (U-16), Under-17 (U-17), Under-19 (U-19), and Under-23 (U-23), Considering the Areas of the Pitch and Phases of the Game.

ABSTRACT: Nieto, S, Echeazarra, I, Errekagorri, I, and Castellano, J. Description of the collective behavior in competition of young soccer players under-16 (U-16), under-17 (U-17), under-19 (U-19), and under-23 (U-23), considering the areas of the pitch and phases of the game. J Strength Cond Res 38(4): 714-723, 2024-The objective was to employ an integrated observational-notational record to describe collective behavior (CB) in competition matches of young soccer players from 4 teams, U-16, U-17, U-19, and U-23, playing for a professional soccer club academy. A total of 1,481 possessions were registered. Collective behavior, captured by GPS devices, was described with the variables: depth, surface area, stretch index, length, and width. In addition, from the notational analysis, the behavior depending on the area of the field (Z1, Z2, Z3, and Z4) and ball possession (POS), nonball possession (nPOS), and set pieces phases were contextualized. A 2-tailed analysis of variance was applied to compare the CB of the teams. Results show that: (a) in all ages/categories, CB varied significantly in and without the possession of the ball and was conditioned by the area of the pitch where the ball was; (b) CB showed higher values with the ball and greater variability without it; and (c) depending on the age, CB presented differences with larger effect sizes in depth and length, in and without the possession of the ball, in Z1 and Z2. Integrating positional data to the moment of play and areas of the field could help a more accurate analysis of the competition to better understand the CB evolution of young soccer players.

Experimental evidence suggests intergroup relations are, by default, neutral rather than aggressive.

The target article offers a game-theoretical analysis of primitive intergroup aggression (i.e., raiding) and discusses difficulties in achieving peace. We argue the analysis does not capture the actual strategy space, missing out "do-nothing." Experimental evidence robustly shows people prefer doing nothing against out-group members over cooperating with/attacking them. Thus, the target article overestimates the likelihood of intergroup aggression.

Use of nominal group technique methods in the virtual setting: A reflective account and recommendations for practice.

Nominal group technique methods involve the use of structured activities within groups comprised of purposefully selected stakeholders (nominal groups), with the broad aim of achieving a level of consensus and prioritising information. In this paper, we will report how we facilitated nominal groups, using Microsoft Teams, to prioritise content for a theory-based behaviour change intervention to improve responses to clinically deteriorating patients. Our methods incorporated development and piloting of research materials, facilitation of online nominal groups with different stakeholders, and a structured approach to ranking behaviour change strategies. Practical suggestions are offered based on our experience of using this method in a virtual context.

Collective behavior in relation with changing environments: Dynamics, modularity, and agency.

Collective behavior operates without central control, using local interactions among participants to adjust to changing conditions. Many natural systems operate collectively, and by specifying what objectives are met by the system, the idea of agency helps to describe how collective behavior is embedded in the conditions it deals with. Ant colonies function collectively, and the enormous diversity of more than 15K species of ants, in different habitats, provides opportunities to look for general ecological patterns in how collective behavior operates. The foraging behavior of harvester ants in the desert regulates activity to manage water loss, while the trail networks of turtle ants in the canopy tropical forest respond to rapidly changing resources and vegetation. These examples illustrate some broad correspondences in natural systems between the dynamics of collective behavior and the dynamics of the surroundings. To outline how interactions among participants, acting in relation with changing surroundings, achieve collective outcomes, I focus on three aspects of collective behavior: the rate at which interactions adjust to conditions, the feedback regime that stimulates and inhibits activity, and the modularity of the network of interactions. To characterize the dynamics of the surroundings, I consider gradients in stability, energy flow, and the distribution of resources and demands. I then propose some hypotheses that link how collective behavior operates with changing environments.

Increasing resolution in stress neurobiology: from single cells to complex group behaviors.

Stress can have severe psychological and physiological consequences. Thus, inappropriate regulation of the stress response is linked to the etiology of mood and anxiety disorders. The generation and implementation of preclinical animal models represent valuable tools to explore and characterize the mechanisms underlying the pathophysiology of stress-related psychiatric disorders and the development of novel pharmacological strategies. In this commentary, we discuss the strengths and limitations of state-of-the-art molecular and computational advances employed in stress neurobiology research, with a focus on the ever-increasing spatiotemporal resolution in cell biology and behavioral science. Finally, we share our perspective on future directions in the fields of preclinical and human stress research.

Dynamics and risk sharing in groups of selfish individuals.

Understanding why animals organize in collective states is a central question of current research in, e.g., biology, physics, and psychology. More than 50 years ago, W.D. Hamilton postulated that the formation of animal herds may simply result from the individual's selfish motivation to minimize their predation risk. The latter is quantified by the domain of danger (DOD) which is given by the Voronoi area around each individual. In fact, simulations show that individuals aiming to reduce their DODs form compact groups similar to what is observed in many living systems. However, despite the apparent simplicity of this problem, it is not clear what motional strategy is required to find an optimal solution. Here, we use the framework of Multi Agent Reinforcement Learning (MARL) which gives the unbiased and optimal strategy of individuals to solve the selfish herd problem. We demonstrate that the motivation of individuals to reduce their predation risk naturally leads to pronounced collective behaviors including the formation of cohesive swirls. We reveal a previously unexplored rather complex intra-group motion which eventually leads to a evenly shared predation risk amongst selfish individuals.

Self-organization of collective escape in pigeon flocks.

Bird flocks under predation demonstrate complex patterns of collective escape. These patterns may emerge by self-organization from local interactions among group-members. Computational models have been shown to be valuable for identifying what behavioral rules may govern such interactions among individuals during collective motion. However, our knowledge of such rules for collective escape is limited by the lack of quantitative data on bird flocks under predation in the field. In the present study, we analyze the first GPS trajectories of pigeons in airborne flocks attacked by a robotic falcon in order to build a species-specific model of collective escape. We use our model to examine a recently identified distance-dependent pattern of collective behavior: the closer the prey is to the predator, the higher the frequency with which flock members turn away from it. We first extract from the empirical data of pigeon flocks the characteristics of their shape and internal structure (bearing angle and distance to nearest neighbors). Combining these with information on their coordination from the literature, we build an agent-based model adjusted to pigeons' collective escape. We show that the pattern of turning away from the predator with increased frequency when the predator is closer arises without prey prioritizing escape when the predator is near. Instead, it emerges through self-organization from a behavioral rule to avoid the predator independently of their distance to it. During this self-organization process, we show how flock members increase their consensus over which direction to escape and turn collectively as the predator gets closer. Our results suggest that coordination among flock members, combined with simple escape rules, reduces the cognitive costs of tracking the predator while flocking. Such escape rules that are independent of the distance to the predator can now be investigated in other species. Our study showcases the important role of computational models in the interpretation of empirical findings of collective behavior.

Dynamical behavior mechanism in the network of interaction between group behavior and virus propagation.

This paper introduces a complex network of interaction between human behavior and virus transmission, in which group synchronous behavior influences cure rates. The study examines the influence of individual group behavior on virus transmission, the reciprocal influence of virus transmission on individual group behavior, and the effects of evolving network structures on cluster synchronization. It also analyzes the conditions necessary for virus extinction or the occurrence of a pandemic, as well as the conditions for achieving individual group synchronization. The paper provides discriminant conditions to distinguish between aggregation behavior and virus extinction. The proposed model effectively captures the phenomenon of resurgence observed in many viruses. The conclusions drawn are rigorously validated through simulations conducted under various conditions, confirming the validity and reliability of the findings.

Recovery of dynamical similarity from lossy representations of collective behavior of midge swarms.

Understanding emergent collective phenomena in biological systems is a complex challenge due to the high dimensionality of state variables and the inability to directly probe agent-based interaction rules. Therefore, if one wants to model a system for which the underpinnings of the collective process are unknown, common approaches such as using mathematical models to validate experimental data may be misguided. Even more so, if one lacks the ability to experimentally measure all the salient state variables that drive the collective phenomena, a modeling approach may not correctly capture the behavior. This problem motivates the need for model-free methods to characterize or classify observed behavior to glean biological insights for meaningful models. Furthermore, such methods must be robust to low dimensional or lossy data, which are often the only feasible measurements for large collectives. In this paper, we show that a model-free and unsupervised clustering of high dimensional swarming behavior in midges (Chironomus riparius), based on dynamical similarity, can be performed using only two-dimensional video data where the animals are not individually tracked. Moreover, the results of the classification are physically meaningful. This work demonstrates that low dimensional video data of collective motion experiments can be equivalently characterized, which has the potential for wide applications to data describing animal group motion acquired in both the laboratory and the field.

Effects of engaging in mass participation sporting events on physical activity behaviour,: a systematic review.

Mass participation sports event (MPSE)s have been identified as a potential referral pathway for engaging inactive patients in regular physical activity. This study aimed to review evidence of physical activity behaviour and associated health-related outcomes of engaging in MPSEs among the general population. A systematic review was performed of quantitative studies that examined the relationship between MPSEs and physical activity behaviour or secondary outcomes (e.g. physical activity motivation or confidence, physical or mental health) or any intervention to maintain physical activity following MPSEs. Search methods included searching five electronic databases and checking reference lists. Methodological quality was assessed using the Mixed Methods Appraisal Tool. A total of 2079 papers were identified, 142 were independently assessed for eligibility and 39 were included. Data from prospective cohort studies suggested that levels of physical activity achieved in training for MPSEs tended to drop in the months after, but increases were reported in some studies of novice participants. Interventions involving health promotion materials provided post-event led to small increases in physical activity. Perceived benefits of participating in MPSEs included physical and mental health, fitness, self-efficacy and social connections. Existing evidence suggests that MPSEs can act as a motivator to initiate exercise in preparation for the event, but there is limited evidence on how best to sustain physical activity post-event. Given the short duration of most studies, longer prospective analyses are needed to delineate patterns of habitual and event-related activity and account for seasonal effects.

Mass participation sporting events can be attractive to low-active participants as well as regular exercisers, with a notable proportion identified as low active (one-fifth). Overall levels of physical activity tend to decline after event completion, suggesting that training in preparation for events was not maintained. There is some evidence of increased exercise post-event reported among novice participants, though evidence is limited on effective ways to sustain exercise after event completion. Regularly held events such as parkrun or booster interventions following events helped maintain exercise levels over 12 months.

Phenomenon of Nightclub Shots: Mass Psychogenic Disease?

BACKGROUND: This article examines the possibility that the "nightclub shots" epidemic is a "mass psychogenic disease" phenomenon, by comparing the various cases of "mass sociogenic diseases" reported in the literature. We carried out a literature review on PubMed. The keywords used were "mass hysteria", "mass sociogenic disease", "mass psychogenic disease" and "epidemic of multiple unexplained symptoms". RESULTS: Our review of the literature revealed several elements common to the various "mass hysterias" we identified. These phenomena generally appear in a climate of anxiety specific to the era in which they occur, in this case the fear of bioterrorism in the 21st century. Symptoms are generally benign and transient, appearing and resolving easily without the identification of an organic cause. They usually occur in a small group of individuals, and more frequently in young people and women. The media can exacerbate the phenomenon. CONCLUSION: The phenomenon of epidemics of nightclub shots seems to fit into the common framework of "mass psychogenic diseases" identified in the literature. This diagnosis could therefore be evoked, in the absence of any other objective somatic explanation.

Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model.

BACKGROUND: Every year, volunteers of the Belgian Red Cross provide onsite medical care at more than 8000 mass gathering events and other manifestations. Today standardized planning tools for optimal preventive medical resource use during these events are lacking. This study aimed to develop and validate a prediction model of patient presentation rate (PPR) and transfer to hospital rate (TTHR) at mass gatherings in Belgium. METHODS: More than 200,000 medical interventions from 2006 to 2018 were pooled in a database. We used a subset of 28 different mass gatherings (194 unique events) to develop a nonlinear prediction model. Using regression trees, we identified potential predictors for PPR and TTHR at these mass gatherings. The additional effect of ambient temperature was studied by linear regression analysis. Finally, we validated the prediction models using two other subsets of the database. RESULTS: The regression tree for PPR consisted of 7 splits, with mass gathering category as the most important predictor variable. Other predictor variables were attendance, number of days, and age class. Ambient temperature was positively associated with PPR at outdoor events in summer. Calibration of the model revealed an R2 of 0.68 (95% confidence interval 0.60-0.75). For TTHR, the most determining predictor variables were mass gathering category and predicted PPR (R2 = 0.48). External validation indicated limited predictive value for other events (R2 = 0.02 for PPR; R2 = 0.03 for TTHR). CONCLUSIONS: Our nonlinear model performed well in predicting PPR at the events used to build the model on, but had poor predictive value for other mass gatherings. The mass gathering categories "outdoor music" and "sports event" warrant further splitting in subcategories, and variables such as attendance, temperature and resource deployment need to be better recorded in the future to optimize prediction of medical usage rates, and hence, of resources needed for onsite emergency medical care.