Information flow through threespine stickleback networks without social transmission

Social networks can result in directed social transmission of learned information, thus influencing how innovations spread through populations. Here we presented shoals of threespine sticklebacks (Gasterosteous aculeatus) with two identical foraging tasks and applied network-based diffusion analysis (NBDA) to determine whether the order in which individuals in a social group contacted and solved the tasks was affected by the group's network structure. We found strong evidence for a social effect on discovery of the foraging tasks with individuals tending to discover a task sooner when others in their group had previously done so, and with the spread of discovery of the foraging tasks influenced by groups' social networks. However, the same patterns of association did not reliably predict spread of solution to the tasks, suggesting that social interactions affected the time at which the tasks were discovered, but not the latency to its solution following discovery. The present analysis, one of the first applications of NBDA to a natural animal system, illustrates how NBDA can lead to insight into the mechanisms supporting behaviour acquisition that more conventional statistical approaches might miss. Importantly, we provide the first compelling evidence that the spread of novel behaviours can result from social learning in the absence of social transmission, a phenomenon that we refer to as an untransmitted social effect on learning.     

Social Network Analysis Shows Direct Evidence for Social Transmission of Tool Use in Wild Chimpanzees

Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition—that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, “moss-sponging” and “leaf-sponge re-use,” in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most “cultural” of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.     

Humans copy rapidly increasing choices in a multiarmed bandit problem

Conformist social learning, the tendency to acquire the most common trait in a group, allows individuals to rapidly acquire established beneficial traits from a multitude of options. However, conformist strategies hinder acquisition of novel advantageous behavior patterns, because such innovations are by definition uncommon. This raises the possibility that proxy cues of the success of novel traits may be utilized to identify and acquire advantageous innovations and disregard failing options. We show that humans use changes in trait frequency over time as such a cue in an economic game. Participants played a three-alternative forced choice game (i.e., a multi-armed bandit), using social information to attempt to locate a high reward that could change location. Participants viewed temporal changes in how many players chose each option in two successive rounds. Participants supplemented conformist strategies with a “copy-increasing-traits” strategy. That is, regardless of the traits absolute population frequencies, participants' choices were guided by changes in trait frequencies. Thus, humans can detect advantageous innovations by monitoring how many individuals adopt these over time, adopting traits increasing in frequency, and abandoning traits decreasing in frequency. Copying rapidly increasing traits allows identification and acquisition of advantageous innovations, and is thus potentially key in facilitating their early diffusion and cultural evolution.     

Social learning in animals: comparative analysis of different forms and levels

Social learning as one of the key concepts of cognitive ecology includes different forms of behavioural displays from relatively simple, such as "social release" and "stimulus enhancement" up to "teaching" and "cultural transmission" in animal communities. Rapid development of this fields resulted in some contradictions in methods and terminology. In this review different forms and levels of social learning are analyzed. Ecological aspects of social learning are connected with diet shaping, fear of predators and mate choice. The first aspect is the most studied but still discussible. Social learning being an intricate component of feeding behaviour matches with innate behaviour, imprinting as well as early associative learning. Investigation of cognitive aspects of social learning going back to Thorndike's crucial question "Do apes ape?" are now developing into series of questions including even: "Do ants ape?". Elaboration of universal methods of comparative studying of social learning such as "artificial fruit" and "two ways/one outcome" has essentially enlightened these questions and made comparative analysis possible. Large continuum of displays of cognitive skills in social learning has been revealed in non-primate species. One of the discussible issues in the role of social learning is distribution of innovations. Many authors have investigated this intriguing aspect of animal behaviour in different ways, such as long field observations as well as laboratory experiments based on "artificial innovators" that is specimens specially taught by experimentalists. Many impressive results were obtained; in particular it turned out in contradiction with some mathematical models that individuals in groups are rather different in their psychophysiological predisposition to innovative behaviour. Role of teaching in such different forms of behaviour as shaping of species-specific behavioural patterns and spread of innovations is considered. Although the majority of animals in wild populations are not good teachers and pupils, some cultural aspects of behaviour were recently revealed, mostly in primates. At the same time some classical results concerning cultural transmission of new patterns (for example, bottle-opening in tits) were experimentally revised. Many problems still remain unsolved, in particular, how spread of innovations may favour prosperity of populations; to what degree behavioural peculiarities of local groups may be determined by processes of social learning; which internal and external factors and under what circumstances invest into social learning in natural environment.     

Cultural Transmission and the Diffusion of Innovations: Adoption Dynamics Indicate That Biased Cultural Transmission Is the Predominate Force in Behavioral Change

In challenging the pervasive model of individual actors as cost-benefit analysts who adapt their behavior by learning from the environment, this article analyzes the temporal dynamics of both environmental (individual) learning and biased cultural transmission processes by comparing these dynamics with the robust "5-shaped" curves that emerge from the diffusion of innovations literature. The analysis shows three things: (1) that environmental learning alone never produces the 5-shaped adoption dynamics typically observed in the spread of novel practices, ideas, and technologies; (2) that biased cultural transmission always produces the S-shaped temporal dynamics; and (3) that a combination of environmental learning and biased cultural transmission can generate 5-dynamics but only when biased cultural transmission is the predominate force in the spread of new behaviors. These findings suggest that biased cultural transmission processes are much more important to understanding the diffusion of innovations and sociocultural evolution than is often assumed by most theorists. [ diffusion of innovations, cultural transmission, learning, cultural evolution ]     

Innovation in the collective brain

Innovation is often assumed to be the work of a talented few, whose products are passed on to the masses. Here, we argue that innovations are instead an emergent property of our species'' cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains. We outline how many human brains, which evolved primarily for the acquisition of culture, together beget a collective brain. Within these collective brains, the three main sources of innovation are serendipity, recombination and incremental improvement. We argue that rates of innovation are heavily influenced by (i) sociality, (ii) transmission fidelity, and (iii) cultural variance. We discuss some of the forces that affect these factors. These factors can also shape each other. For example, we provide preliminary evidence that transmission efficiency is affected by sociality—languages with more speakers are more efficient. We argue that collective brains can make each of their constituent cultural brains more innovative. This perspective sheds light on traits, such as IQ, that have been implicated in innovation. A collective brain perspective can help us understand otherwise puzzling findings in the IQ literature, including group differences, heritability differences and the dramatic increase in IQ test scores over time.     

A novel feeding behaviour in wild redfronted lemurs (Eulemur rufifrons): depletion of spider nests

Reports on behavioural innovations in wild primate populations as well as on their transmission are rare. Here, we report observations suggesting that redfronted lemurs (Eulemur rufifrons) invent new behaviours in the wild. We observed a novel feeding behaviour in redfronted lemurs in Kirindy Forest, western Madagascar. The feeding behaviour consisted of depletion of nests of a social spider species (Stegodyphus sp.). The behaviour was observed in only one out of four study groups, although spider nests were present in the home ranges of all four groups. The behaviour was exhibited in three different years (2009, 2011, 2012) and appears to be re-invented from time to time. Interestingly, in 2011 this behaviour was shown by four individuals and probably spread within the group. This feeding behaviour has only been observed between the middle of June and early August (i.e. the early dry season), and nests were found to be empty later on, suggesting that these nests are available as a food source only seasonally. Our observation contributes a rare case of behavioural innovations in a wild primate population.     

Animal learning as a source of developmental bias

As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path‐dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution.     

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data

Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional manual gating utilized to identify new cell populations has been inadequate, inefficient, unreliable, and difficult to use, and no algorithms to identify both calibration and new cell populations has been well established. A deep learning with graphic cluster (DGCyTOF) visualization is developed as a new integrated embedding visualization approach in identifying canonical and new cell types. The DGCyTOF combines deep-learning classification and hierarchical stable-clustering methods to sequentially build a tri-layer construct for known cell types and the identification of new cell types. First, deep classification learning is constructed to distinguish calibration cell populations from all cells by softmax classification assignment under a probability threshold, and graph embedding clustering is then used to identify new cell populations sequentially. In the middle of two-layer, cell labels are automatically adjusted between new and unknown cell populations via a feedback loop using an iteration calibration system to reduce the rate of error in the identification of cell types, and a 3-dimensional (3D) visualization platform is finally developed to display the cell clusters with all cell-population types annotated. Utilizing two benchmark CyTOF databases comprising up to 43 million cells, we compared accuracy and speed in the identification of cell types among DGCyTOF, DeepCyTOF, and other technologies including dimension reduction with clustering, including Principal Component Analysis (PCA), Factor Analysis (FA), Independent Component Analysis (ICA), Isometric Feature Mapping (Isomap), t-distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) with k-means clustering and Gaussian mixture clustering. We observed the DGCyTOF represents a robust complete learning system with high accuracy, speed and visualization by eight measurement criteria. The DGCyTOF displayed F-scores of 0.9921 for CyTOF1 and 0.9992 for CyTOF2 datasets, whereas those scores were only 0.507 and 0.529 for the t-SNE+k-means; 0.565 and 0.59, for UMAP+ k-means. Comparison of DGCyTOF with t-SNE and UMAP visualization in accuracy demonstrated its approximately 35% superiority in predicting cell types. In addition, observation of cell-population distribution was more intuitive in the 3D visualization in DGCyTOF than t-SNE and UMAP visualization. The DGCyTOF model can automatically assign known labels to single cells with high accuracy using deep-learning classification assembling with traditional graph-clustering and dimension-reduction strategies. Guided by a calibration system, the model seeks optimal accuracy balance among calibration cell populations and unknown cell types, yielding a complete and robust learning system that is highly accurate in the identification of cell populations compared to results using other methods in the analysis of single-cell CyTOF data. Application of the DGCyTOF method to identify cell populations could be extended to the analysis of single-cell RNASeq data and other omics data.     

Individual acquisition of “stick pounding” behavior by naïve chimpanzees

Many studies investigating culture in nonhuman animals tend to focus on the inferred need of social learning mechanisms that transmit the form of a behavior to explain the population differences observed in wild animal behavioral repertoires. This research focus often results in studies overlooking the possibility of individuals being able to develop behavioral forms without requiring social learning. The disregard of individual learning abilities is most clearly observed in the nonhuman great ape literature, where there is a persistent claim that chimpanzee behaviors, in particular, require various forms of social learning mechanisms. These special social learning abilities have been argued to explain the acquisition of the relatively large behavioral repertoires observed across chimpanzee populations. However, current evidence suggests that although low‐fidelity social learning plays a role in harmonizing and stabilizing the frequency of behaviors within chimpanzee populations, some (if not all) of the forms that chimpanzee behaviors take may develop independently of social learning. If so, they would be latent solutions—behavioral forms that can (re‐)emerge even in the absence of observational opportunities, via individual (re)innovations. Through a combination of individual and low‐fidelity social learning, the population‐wide patterns of behaviors observed in great ape species are then established and stably maintained. This is the Zone of Latent Solutions (ZLS) hypothesis. The current study experimentally tested the ZLS hypothesis for pestle pounding, a wild chimpanzee behavior. We tested the reinnovation of this behavior in semi‐wild chimpanzees at Chimfunshi Wildlife Orphanage in Zambia, Africa, (N = 90, tested in four social groups). Crucially, all subjects were naïve to stick pounding before testing. Three out of the four tested groups reinnovated stick pounding—clearly demonstrating that this behavioral form does not require social learning. These findings provide support for the ZLS hypothesis alongside further evidence for the individual learning abilities of chimpanzees.     

Detecting social learning using networks: a users guide

Controversy over claims of cultures in nonhuman primates and other animals has led to a call for quantitative methods that are able to infer social learning from freely interacting groups of animals. Network-based diffusion analysis (NBDA) is such a method that infers social transmission of a behavioral trait when the pattern of acquisition follows the social network. As, relative to other animals, primates may be unusual in their heavy reliance on social learning, with learning frequently directed along pathways of association; in this study, we draw attention to the significance of this method for primatologists. We provide a "users guide" to NBDA methodology, discussing the choice of NBDA model and social network, and suggest model selection procedures. We also present the results of simulations that suggest that NBDA works well even when the assumptions of the underlying model are violated.     

Social learning improves survivorship at a life-history transition

During settlement, one of the main threats faced by individuals relates to their ability to detect and avoid predators. Information on predator identities can be gained either through direct experience or from the observation and/or interaction with others, a process known as social learning. In this form of predator recognition, less experienced individuals learn from experienced members within the social group, without having to directly interact with a predator. In this study, we examined the role of social learning in predator recognition in relation to the survival benefits for the damselfish, Pomacentrus wardi, during their settlement transition. Specifically, our experiments aimed to determine if P. wardi are capable of transmitting the recognition of the odour of a predator, Pseudochromis fuscus, to conspecifics. The experiment also examined whether there was a difference in the rate of survival between individuals that directly learnt the predator odour and those which acquired the information through social learning compared to naïve individuals. Results show that naïve P. wardi are able to learn a predator’s identity from experienced individuals via social learning. Furthermore, survival between individuals that directly learnt the predator’s identity and those that learnt through social learning did not significantly differ, with fish from both treatments surviving at least five times better than controls. These results demonstrate that experience may play a vital role in determining the outcome of predator–prey interactions, highlighting that social learning improves the ability of prey to avoid and/or escape predation at a life-history transition.     

Identifying Social Learning in Animal Populations: A New ‘Option-Bias’ Method

Background

Studies of natural animal populations reveal widespread evidence for the diffusion of novel behaviour patterns, and for intra- and inter-population variation in behaviour. However, claims that these are manifestations of animal ‘culture’ remain controversial because alternative explanations to social learning remain difficult to refute. This inability to identify social learning in social settings has also contributed to the failure to test evolutionary hypotheses concerning the social learning strategies that animals deploy.

Methodology/Principal Findings

We present a solution to this problem, in the form of a new means of identifying social learning in animal populations. The method is based on the well-established premise of social learning research, that - when ecological and genetic differences are accounted for - social learning will generate greater homogeneity in behaviour between animals than expected in its absence. Our procedure compares the observed level of homogeneity to a sampling distribution generated utilizing randomization and other procedures, allowing claims of social learning to be evaluated according to consensual standards. We illustrate the method on data from groups of monkeys provided with novel two-option extractive foraging tasks, demonstrating that social learning can indeed be distinguished from unlearned processes and asocial learning, and revealing that the monkeys only employed social learning for the more difficult tasks. The method is further validated against published datasets and through simulation, and exhibits higher statistical power than conventional inferential statistics.

Conclusions/Significance

The method is potentially a significant technological development, which could prove of considerable value in assessing the validity of claims for culturally transmitted behaviour in animal groups. It will also be of value in enabling investigation of the social learning strategies deployed in captive and natural animal populations.     

Task-Based Core-Periphery Organization of Human Brain Dynamics

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain''s putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior.     

Differences in Rice stripe virus transmission abilities of Laodelphax striatellus (Homoptera: Delphacidae) from four geographical populations

The small brown planthopper, Laodelphax striatellus (Fallén), can transfer Rice stripe virus (RSV) to host plants, which then develop rice stripe disease. Between vectors, there are two paths for RSV transmission. In current study, we examined the horizontal, vertical and compound transmission rates (horizontal and vertical transmissions together) by L. striatellus from one non-epidemic area (Fuyang in Zhejiang province) and three epidemic areas (Yizheng and Peixian in Jiangsu province, and Donggang in Liaoning province). RSV acquisition rates for naïve L. striatellus from the four populations were not significantly different. RSV transmission rate to healthy rice plants by viruliferous L. striatellus from Fuyang population was relatively lower than those of the other three populations. For example, RSV transmission rate in Fuyang population decreased by 1 fold compared to that in Peixian population when the transmission times were 48 and 72 h. It indicated that horizontal transmission ability of Fuyang population was lower. Vertical transmission rate and the compound transmission abilities of infective L. striatellus in the first generation did not differ significantly among the four populations. However, the ratio of RSV-positive offspring of an infective mother in the fourth generation of Fuyang population (84.3 ± 2.4%) was lowest, and decreased by 10% compared to that of Peixian population. It meant that compound transmission ability of Fuyang population was significantly lower than the other three populations. The reason for the difference in transmission abilities of L. striatellus from different populations was discussed.     

The Influence of Social Structure,Habitat, and Host Traits on the Transmission of Escherichia coli in Wild Elephants

Social structure is proposed to influence the transmission of both directly and environmentally transmitted infectious agents. However in natural populations, many other factors also influence transmission, including variation in individual susceptibility and aspects of the environment that promote or inhibit exposure to infection. We used a population genetic approach to investigate the effects of social structure, environment, and host traits on the transmission of Escherichia coli infecting two populations of wild elephants: one in Amboseli National Park and another in Samburu National Reserve, Kenya. If E. coli transmission is strongly influenced by elephant social structure, E. coli infecting elephants from the same social group should be genetically more similar than E. coli sampled from members of different social groups. However, we found no support for this prediction. Instead, E. coli was panmictic across social groups, and transmission patterns were largely dominated by habitat and host traits. For instance, habitat overlap between elephant social groups predicted E. coli genetic similarity, but only in the relatively drier habitat of Samburu, and not in Amboseli, where the habitat contains large, permanent swamps. In terms of host traits, adult males were infected with more diverse haplotypes, and males were slightly more likely to harbor strains with higher pathogenic potential, as compared to adult females. In addition, elephants from similar birth cohorts were infected with genetically more similar E. coli than elephants more disparate in age. This age-structured transmission may be driven by temporal shifts in genetic structure of E. coli in the environment and the effects of age on bacterial colonization. Together, our results support the idea that, in elephants, social structure often will not exhibit strong effects on the transmission of generalist, fecal-oral transmitted bacteria. We discuss our results in the context of social, environmental, and host-related factors that influence transmission patterns.     

Social learning of fear and safety is determined by the demonstrator's racial group

Social learning offers an efficient route through which humans and other animals learn about potential dangers in the environment. Such learning inherently relies on the transmission of social information and should imply selectivity in what to learn from whom. Here, we conducted two observational learning experiments to assess how humans learn about danger and safety from members (‘demonstrators'') of an other social group than their own. We show that both fear and safety learning from a racial in-group demonstrator was more potent than learning from a racial out-group demonstrator.     

The invasion by the Yellow-legged hornet: A systematic review

The Yellow-legged hornet (Vespa velutina nigrithorax), native to regions of Southeast Asia, was accidentally introduced in Europe, South Korea, and Japan, where is has often become invasive. Due to its potential negative impacts at ecologic, economic and social levels, this hornet was included in the “Union list” of the EU legislation for invasive alien species. This means that measures are urgently needed to prevent further introductions, as well as to early-detect and control spread to avoid new populations. In this study we aim to identify the main reported drivers of distribution, ecological preferences, impacts, and methods for preventing introduction, controlling, and managing this invasive species. The supporting information was obtained from a comprehensive literature search. Then, a literature review was performed to classify the records gathered and to extract the relevant information following an adapted Drivers-Pressures-State-Impacts-Responses framework. The achieved results show a growing interest of researchers on V. velutina nigrithorax through time due to its quick spread and impacts on new ecosystems. They also revealed that there is much information on the State of invasions, whereas more knowledge is needed regarding the Drivers of those invasions. Biological traits such as life history traits, morphology, and the sting venom properties are some of the most studied topics regarding V. velutina nigrithorax. In the future, research should focus on the topics that lack information, analyse other Response solutions that meet the intended measures by the EU legislation, and use new methodology to study the impacts caused by this invader under new perspectives.