Co-cultures: exploring interspecies culture among humans and other animals.

The concept of 'co-culture' is introduced as a novel framework for understanding the mutual cultural evolution between animal species, including, but not only, humans. It explores the dynamics of interspecies interactions, particularly in how different species influence each other's behavioural and cognitive adaptations. Various instances of interspecies cultural exchange are highlighted, such as the acquisition of medicinal plants from animals resulting in a shared medicinal culture, adaptive behaviours of urban wildlife, and cooperative behaviours between animal species. Co-culture challenges the notion of species-specific culture, underscoring the complexity and interconnectedness of human and animal societies, and between animal societies. Further research into co-culture is advocating and emphasising its implications for conservation, urban planning, and a deeper understanding of animal cognition and behaviour.

Deep learning for automatic facial detection and recognition in Japanese macaques: illuminating social networks.

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research has offered new methodological perspectives through the automatisation of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identification done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques' face detector (Faster-RCNN model), reaching an accuracy of 82.2% and (ii) the creation of an individual recogniser for the Kojima Island macaque population (YOLOv8n model), reaching an accuracy of 83%. We also created a Kojima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques.

Effect of a Cat's Permanent Presence on the Health and Social Network of Older Adults With Alzheimer's Disease or Disabilities in a Nursing Home.

Our study analyzes the effects of the permanent presence of cats on the health and social network of residents with pathologies in nursing home. Fifty-three residents, thirty-six caregivers, and four cats in three Alzheimer's Disease units ("ADU") and one Disability unit ("DISU") were observed for 180 hours. Social networks were created via instantaneous sampling of physical proximities and social exchanges between residents, caregivers, and the cats. Our results showed that: (1) the four units behave similarly in the presence or absence of a cat (2) cats are placed at the periphery of the network and interact with residents showing a keen interest in them, and (3) caregivers who are in strong contact with the cat show a greater number of social interactions in their unit. This study, using for the first time a social network approach, opens up a new field of understanding of human-animal relationships in a care dimension.

The power of sound: unravelling how acoustic communication shapes group dynamics.

Acoustic signalling is a key mode of communication owing to its instantaneousness and rapid turnover, its saliency and flexibility and its ability to function strategically in both short- and long-range contexts. Acoustic communication is closely intertwined with both collective behaviour and social network structure, as it can facilitate the coordination of collective decisions and behaviour, and play an important role in establishing, maintaining and modifying social relationships. These research topics have each been studied separately and represent three well-established research areas. Yet, despite the close connection of acoustic communication with collective behaviour and social networks in natural systems, only few studies have focused on their interaction. The aim of this theme issue is therefore to build a foundation for understanding how acoustic communication is linked to collective behaviour, on the one hand, and social network structure on the other, in non-human animals. Through the building of such a foundation, our hope is that new questions in new avenues of research will arise. Understanding the links between acoustic communication and social behaviour seems crucial for gaining a comprehensive understanding of sociality and social evolution. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Individual and ecological heterogeneity promote complex communication in social vertebrate group decisions.

To receive the benefits of social living, individuals must make effective group decisions that enable them to achieve behavioural coordination and maintain cohesion. However, heterogeneity in the physical and social environments surrounding group decision-making contexts can increase the level of difficulty social organisms face in making decisions. Groups that live in variable physical environments (high ecological heterogeneity) can experience barriers to information transfer and increased levels of ecological uncertainty. In addition, in groups with large phenotypic variation (high individual heterogeneity), individuals can have substantial conflicts of interest regarding the timing and nature of activities, making it difficult for them to coordinate their behaviours or reach a consensus. In such cases, active communication can increase individuals' abilities to achieve coordination, such as by facilitating the transfer and aggregation of information about the environment or individual behavioural preferences. Here, we review the role of communication in vertebrate group decision-making and its relationship to heterogeneity in the ecological and social environment surrounding group decision-making contexts. We propose that complex communication has evolved to facilitate decision-making in specific socio-ecological contexts, and we provide a framework for studying this topic and testing related hypotheses as part of future research in this area. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Automatic identification of stone-handling behaviour in Japanese macaques using LabGym artificial intelligence.

The latest advances in artificial intelligence technology have opened doors to the video analysis of complex behaviours. In light of this, ethologists are actively exploring the potential of these innovations to streamline the time-intensive behavioural analysis process using video data. Several tools have been developed for this purpose in primatology in the past decade. Nonetheless, each tool grapples with technical constraints. To address these limitations, we have established a comprehensive protocol designed to harness the capabilities of a cutting-edge artificial intelligence-assisted software, LabGym. The primary objective of this study was to evaluate the suitability of LabGym for the analysis of primate behaviour, focusing on Japanese macaques as our model subjects. First, we developed a model that accurately detects Japanese macaques, allowing us to analyse their actions using LabGym. Our behavioural analysis model succeeded in recognising stone-handling-like behaviours on video. However, the absence of quantitative data within the specified time frame limits the ability of our study to draw definitive conclusions regarding the quality of the behavioural analysis. Nevertheless, to the best of our knowledge, this study represents the first instance of applying the LabGym tool specifically for the analysis of primate behaviours, with our model focusing on the automated recognition and categorisation of specific behaviours in Japanese macaques. It lays the groundwork for future research in this promising field to complexify our model using the latest version of LabGym and associated tools, such as multi-class detection and interactive behaviour analysis.

The role of social attraction and social avoidance in shaping modular networks.

How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.

Fractals and artificial intelligence to decrypt ideography and understand the evolution of language.

Self-sufficient ideographies are rare because they are stifled by the issue of standardization. Similar issues arise with abstract art or drawings created by young children or great apes. We propose that mathematical indices and artificial intelligence can help us decode ideography, and if not to understand its meaning, at least to know that meaning exists.

Editorial: Recent Advances in Animal Cognition and Ethology.

Animal cognition and ethology, the scientific study of animal behaviour, have long captivated the human imagination [...].

Micro urban spaces and mental well-being: Measuring the exposure to urban landscapes along daily mobility paths and their effects on momentary depressive symptomatology among older population.

The urban environment plays an important role for the mental health of residents. Researchers mainly focus on residential neighbourhoods as exposure context, leaving aside the effects of non-residential environments. In order to consider the daily experience of urban spaces, a people-based approach focused on mobility paths is needed. Applying this approach, (1) this study investigated whether individuals' momentary mental well-being is related to the exposure to micro-urban spaces along the daily mobility paths within the two previous hours; (2) it explored whether these associations differ when environmental exposures are defined considering all location points or only outdoor location points; and (3) it examined the associations between the types of activity and mobility and momentary depressive symptomatology. Using a geographically-explicit ecological momentary assessment approach (GEMA), momentary depressive symptomatology of 216 older adults living in the Ile-de-France region was assessed using smartphone surveys, while participants were tracked with a GPS receiver and an accelerometer for seven days. Exposure to multiple elements of the streetscape was computed within a street network buffer of 25 m of each GPS point over the two hours prior to the questionnaire. Mobility and activity type were documented from a GPS-based mobility survey. We estimated Bayesian generalized mixed effect models with random effects at the individual and day levels and took into account time autocorrelation. We also estimated fixed effects. A better momentary mental wellbeing was observed when residents performed leisure activities or were involved in active mobility and when they were exposed to walkable areas (pedestrian dedicated paths, open spaces, parks and green areas), water elements, and commerce, leisure and cultural attractors over the previous two hours. These relationships were stronger when exposures were defined based only on outdoor location points rather than all location points, and when we considered within-individual differences compared to between-individual differences.

Analyzing the use of videoconference by and for older adults in nursing homes: an interdisciplinary approach to learn from the pandemic.

Introduction: During the Covid-19 pandemic and the resulting visitation restrictions, digital tools were used in many nursing homes in France to allow the older adults and their relatives to maintain social contact via videoconferencing. This article adopts an interdisciplinary approach to analyze the processes that affect the use of digital technologies. Methods: Drawing on the concept of "mediation," it seeks to shed light on how individuals embrace these tools in a relational situation. The interviews and observations undertaken among residents, their relatives, professionals, and the management head of seven nursing homes in 2021, make it possible to outline the different forms of practices and uses and to identify the factors leading to the variations observed. Results: While the key objective of these technical and technological tools is to compensate - on a functional level - for the communication problems and the isolation of individuals in order to promote residents' "quality of life" by maintaining "social contact," our study reveals that these tools' uses and practices largely differ. It also shows considerable inequalities in terms of residents' acquisition of subjective feelings of ownership of the tools. These are never attributed to isolated physical, cognitive, psychic, and social difficulties, but are influenced by specific organizational, interactional, and psychic configurations. Some of the structures analyzed revealed situations in which mediation failed, occasionally exposing the risk associated with seeking "ties at all costs," or revealing a disturbing strangeness when residents were placed in front of screens. Some configurations, however, showed that it was possible to set up an intermediate space for the experience to unfold, which in turn opened up a space where individuals, groups, and institutions could experiment, allowing them to develop subjective feelings of ownership of this experience. Discussion: This article discusses how the configurations that failed to promote the mediation process reveal the need to assess the representations of care and assistance in the relationships between older adults, their loved ones, and nursing home professionals. Indeed, in certain situations, the use of videoconferencing, while seeking to produce a positive effect, risks displacing and increasing the effects of the "negative" associated with dependency, which may worsen individuals' difficulties within nursing homes. The risks associated with the failure to take into account residents' requests and consent explain why it is important to discuss how certain uses of digital tools may renew the dilemma between concerns for protection, on the one hand, and respect for autonomy on the other.

Incorporating animal agency into research design could improve behavioral and neuroscience research.

Despite increasing numbers of publications showing that many animals possess the neural substrates involved in emotions and consciousness and exhibit agency in their behavior, many animals are still restrained and forced to take part in applied or fundamental research. However, these restraints and procedures, because they stress animals and limit the expression of adaptive behavior, may result in compromised findings. Researchers should alter their research paradigms to understand the mechanisms and functions of the brain and behavior so that the paradigms incorporate animals' agency. This article discusses how animal agency cannot only be the key to more wide-ranging and improved research in existing domains but can also lead to new research questions about behavior and brain evolution. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Deep learning for studying drawing behavior: A review.

In recent years, computer science has made major advances in understanding drawing behavior. Artificial intelligence, and more precisely deep learning, has displayed unprecedented performance in the automatic recognition and classification of large databases of sketches and drawings collected through touchpad devices. Although deep learning can perform these tasks with high accuracy, the way they are performed by the algorithms remains largely unexplored. Improving the interpretability of deep neural networks is a very active research area, with promising recent advances in understanding human cognition. Deep learning thus offers a powerful framework to study drawing behavior and the underlying cognitive processes, particularly in children and non-human animals, on whom knowledge is incomplete. In this literature review, we first explore the history of deep learning as applied to the study of drawing along with the main discoveries in this area, while proposing open challenges. Second, multiple ideas are discussed to understand the inherent structure of deep learning models. A non-exhaustive list of drawing datasets relevant to deep learning approaches is further provided. Finally, the potential benefits of coupling deep learning with comparative cultural analyses are discussed.

Use of Digital Technologies to Maintain Older Adults' Social Ties During Visitation Restrictions in Long-Term Care Facilities: Scoping Review.

BACKGROUND: Digital technologies were implemented to address the disruption of long-term care facility residents' socialization needs during the COVID-19 pandemic. A literature review regarding this topic is needed to inform public policy, facility managers, family caregivers, and nurses and allied health professionals involved in mediating the use of digital devices for residents' social ties. OBJECTIVE: Our study outlines key concepts, methodologies, results, issues, and gaps in articles published during pandemic-related visitation restrictions. METHODS: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) protocol, a scoping review was conducted by searching 3 database aggregator platforms (EBSCO, ProQuest, and PubMed) for studies published in peer-reviewed journals from early 2020 to the end of June 2021, when the most stringent restrictions were in place. We included qualitative and quantitative studies, reviews, commentaries, viewpoints, and letters to the editors in French or English focusing on digital technologies aiming to support the social contact of residents in long-term care facilities during pandemic-related visitation restrictions. RESULTS: Among 763 screened articles, 29 met our selection criteria. For each study, we characterized the (1) authors, title, and date of the publication; (2) country of the first author; (3) research fields; (4) article type; and (5) type of technology mentioned. The analysis distinguished 3 main themes emerging from the literature: (1) impact and expectations of remote social contact on the physical and mental health and well-being of the residents (n=12), (2) with whom or what the social contact took place (n=17), and (3) limitations and barriers to significant social contact related to digital technologies (n=14). The results first underlined the highly positive impact expected by the authors of the digital technologies on health and quality of life of residents of long-term care facilities. Second, they highlighted the plurality of ties to consider, since social contact takes place not only with family caregivers to maintain contact but also for other purposes (end-of-life videoconferences) and with other types of contact (eg, with staff and robots). Third, they exposed the limitations and barriers to significant contact using digital technologies and outlined the required conditions to enable them. CONCLUSIONS: The review demonstrated the opportunities and risks outlined by the literature about the implementation of digital technologies to support remote social contact. It showed the plurality of ties to consider and revealed the need to evaluate the positive impact of remote contact from the residents' perspectives. Therefore, to go beyond the risk of digital solutionism, there is a need for studies considering the holistic impact on health regarding the implementation of digital technologies, including the meaning residents give to interpersonal exchanges and the organizational constraints. TRIAL REGISTRATION: OSF Registries osf.io/yhpx3; https://osf.io/yhpx3.

Both age and social environment shape the phenotype of ant workers.

Position within the social group has consequences on individual lifespans in diverse taxa. This is especially obvious in eusocial insects, where workers differ in both the tasks they perform and their aging rates. However, in eusocial wasps, bees and ants, the performed task usually depends strongly on age. As such, untangling the effects of social role and age on worker physiology is a key step towards understanding the coevolution of sociality and aging. We performed an experimental protocol that allowed a separate analysis of these two factors using four groups of black garden ant (Lasius niger) workers: young foragers, old foragers, young nest workers, and old nest workers. We highlighted age-related differences in the proteome and metabolome of workers that were primarily related to worker subcaste and only secondarily to age. The relative abundance of proteins and metabolites suggests an improved xenobiotic detoxification, and a fuel metabolism based more on lipid use than carbohydrate use in young ants, regardless of their social role. Regardless of age, proteins related to the digestive function were more abundant in nest workers than in foragers. Old foragers were mostly characterized by weak abundances of molecules with an antibiotic activity or involved in chemical communication. Finally, our results suggest that even in tiny insects, extended lifespan may require to mitigate cancer risks. This is consistent with results found in eusocial rodents and thus opens up the discussion of shared mechanisms among distant taxa and the influence of sociality on life history traits such as longevity.

Management of Social Behaviour of Domestic Yaks in Manang, Nepal: An Etho-Ethnographic Study.

Herdsmen use different techniques, as per varying geographies and cultures, to keep the cohesion within herds and avoid animals getting lost or predated. However, there is no study on the social behaviour of yaks and herdsmen management practices. Therefore, this ethology study was initiated by ethnographic inquiries. In Manang, the success of the shepherd is dictated by his personal attribute of 'Khula man' or open-heartedness. This attribute refers to good intentions and emotions such as empathy, which allow the shepherd to focus more on others than on himself. This cultural way of assessing the skills required to become a successful and knowledgeable shepherd guided us to study the effect of cultural values on the herd's social behaviour. We collected data from two herds living at the same settlement (Yak kharka, 4100 m altitude, Nepal) by equipping them with loggers. One of the herdsmen used the tether rope while the other one did not. Moreover, the Thaku herd had a more proactive shepherd than the Phurba one. In each herd, 17 animals were equipped with one Actigraph wgt3x-BT to measure activity using an accelerometer and spatial associations using a proximity recorder. One of the herds was equipped with GPS (N = 11) as well. Using GPS locations and activity, we showed that the two herds were cohesive and synchronised their activities but the Thaku herd (tether rope herd) was more cohesive than the Phurba herd based on the Actigraph signals. The shepherds also have personal knowledge of the social relationships of individual animals in their herds and use these relationships to keep the group cohesive and to manage cattle well.

Making Drawings Speak Through Mathematical Metrics.

Figurative drawing is a skill that takes time to learn, and it evolves during different childhood phases that begin with scribbling and end with representational drawing. Between these phases, it is difficult to assess when and how children demonstrate intentions and representativeness in their drawings. The marks produced are increasingly goal-oriented and efficient as the child's skills progress from scribbles to figurative drawings. Pre-figurative activities provide an opportunity to focus on drawing processes. We applied fourteen metrics to two different datasets (N = 65 and N = 344) to better understand the intentional and representational processes behind drawing, and combined these metrics using principal component analysis (PCA) in different biologically significant dimensions. Three dimensions were identified: efficiency based on spatial metrics, diversity with color metrics, and temporal sequentiality. The metrics at play in each dimension are similar for both datasets, and PCA explains 77% of the variance in both datasets. Gender had no effect, but age influenced all three dimensions differently. These analyses for instance differentiate scribbles by children from those drawn by adults. The three dimensions highlighted by this study provide a better understanding of the emergence of intentions and representativeness in drawings. We discussed the perspectives of such findings in comparative psychology and evolutionary anthropology.

Draw yourself: How culture influences drawings by children between the ages of two and fifteen.

The place children live strongly influence how they develop their behavior, this is also true for pictorial expression. This study is based on 958 self-portraits drawn by children aged 2-15 years old from 35 countries across 5 continents. A total of 13 variables were extracted of each drawing allowing us to investigate the differences of individuals and environment representations in these drawings. We used a principal component analysis to understand how drawing characteristics can be combined in pictorial concepts. We analyzed the effect of age, gender, socioeconomic, and cultural factors in terms of complexity and inclusion of social (human figures) and physical (element from Nature and man-made elements) environments, their frequencies, size, and proportions of these elements on each drawing. Our results confirm the existence of cultural variations and the influence of age on self-portrait patterns. We also observed an influence of physical and socio-cultural contexts through the level of urbanization and the degree of individualism of the countries, which have affected the complexity, content and representation of human figures in the drawings studied.

A Data-Driven Simulation of the Trophallactic Network and Intranidal Food Flow Dissemination in Ants.

Food sharing can occur in both social and non-social species, but it is crucial in eusocial species, in which only some group members collect food. This food collection and the intranidal (i.e., inside the nest) food distribution through trophallactic (i.e., mouth-to-mouth) exchanges are fundamental in eusocial insects. However, the behavioural rules underlying the regulation and the dynamics of food intake and the resulting networks of exchange are poorly understood. In this study, we provide new insights into the behavioural rules underlying the structure of trophallactic networks and food dissemination dynamics within the colony. We build a simple data-driven model that implements interindividual variability and the division of labour to investigate the processes of food accumulation/dissemination inside the nest, both at the individual and collective levels. We also test the alternative hypotheses (no variability and no division of labour). The division of labour, combined with inter-individual variability, leads to predictions of the food dynamics and exchange networks that run, contrary to the other models. Our results suggest a link between the interindividual heterogeneity of the trophallactic behaviours, the food flow dynamics and the network of trophallactic events. Our results show that a slight level of heterogeneity in the number of trophallactic events is enough to generate the properties of the experimental networks and seems to be crucial for the creation of efficient trophallactic networks. Despite the relative simplicity of the model rules, efficient trophallactic networks may emerge as the networks observed in ants, leading to a better understanding of the evolution of self-organisation in such societies.

Using Artificial Intelligence to Analyze Non-Human Drawings: A First Step with Orangutan Productions.

Drawings have been widely used as a window to the mind; as such, they can reveal some aspects of the cognitive and emotional worlds of other animals that can produce them. The study of non-human drawings, however, is limited by human perception, which can bias the methodology and interpretation of the results. Artificial intelligence can circumvent this issue by allowing automated, objective selection of features used to analyze drawings. In this study, we use artificial intelligence to investigate seasonal variations in drawings made by Molly, a female orangutan who produced more than 1299 drawings between 2006 and 2011 at the Tama Zoological Park in Japan. We train the VGG19 model to first classify the drawings according to the season in which they are produced. The results show that deep learning is able to identify subtle but significant seasonal variations in Molly's drawings, with a classification accuracy of 41.6%. We use VGG19 to investigate the features that influence this seasonal variation. We analyze separate features, both simple and complex, related to color and patterning, and to drawing content and style. Content and style classification show maximum performance for moderately complex, highly complex, and holistic features, respectively. We also show that both color and patterning drive seasonal variation, with the latter being more important than the former. This study demonstrates how deep learning can be used to objectively analyze non-figurative drawings and calls for applications to non-primate species and scribbles made by human toddlers.