Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development.

Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.

Avoiding costly mistakes in groups: The evolution of error management in collective decision making.

Individuals continuously have to balance the error costs of alternative decisions. A wealth of research has studied how single individuals navigate this, showing that individuals develop response biases to avoid the more costly error. We, however, know little about the dynamics in groups facing asymmetrical error costs and when social influence amplifies either safe or risky behavior. Here, we investigate this by modeling the decision process and information flow with a drift-diffusion model extended to the social domain. In the model individuals first gather independent personal information; they then enter a social phase in which they can either decide early based on personal information, or wait for additional social information. We combined the model with an evolutionary algorithm to derive adaptive behavior. We find that under asymmetric costs, individuals in large cooperative groups do not develop response biases because such biases amplify at the collective level, triggering false information cascades. Selfish individuals, however, undermine the group's performance for their own benefit by developing higher response biases and waiting for more information. Our results have implications for our understanding of the social dynamics in groups facing asymmetrical errors costs, such as animal groups evading predation or police officers holding a suspect at gunpoint.

Social interaction can select for reduced ability.

Animals, including humans, differ in a wide range of physical and cognitive abilities ranging from measures of running speed and physical strength to learning ability and intelligence. We consider the evolution of ability when individuals interact pairwise over their contribution to a common good. In this interaction, the contribution of each is assumed to be the best given their own ability and the contribution of their partner. Since there is a tendency for individuals to partially compensate for a low contribution by their partner, low-ability individuals can do well. As a consequence, for benefit and cost structures for which individuals have a strong response to partner's contribution, there can be selection for reduced ability. Furthermore, there can be disruptive selection on ability, leading to a bimodal distribution of ability under some modes of inheritance.

Boosting medical diagnostics by pooling independent judgments.

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors' diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches.

The making of winners (and losers): how early dominance interactions determine adult social structure in a clonal fish.

Across a wide range of animal taxa, winners of previous fights are more likely to keep winning future contests, just as losers are more likely to keep losing. At present, such winner and loser effects are considered to be fairly transient. However, repeated experiences with winning and/or losing might increase the persistence of these effects, generating long-lasting consequences for social structure. To test this, we exposed genetically identical individuals of a clonal fish, the Amazon molly (Poecilia formosa), to repeated winning and/or losing dominance interactions during the first two months of their life. We subsequently investigated whether these experiences affected the fish's ability to achieve dominance in a hierarchy five months later after sexual maturity, a major life-history transition. Individuals that had only winning interactions early in life consistently ranked at the top of the hierarchy. Interestingly, individuals with only losing experience tended to achieve the middle dominance rank, whereas individuals with both winning and losing experiences generally ended up at the bottom of the hierarchy. In addition to demonstrating that early social interactions can have dramatic and long-lasting consequences for adult social behaviour and social structure, our work also shows that higher cumulative winning experience early in life can counterintuitively give rise to lower social rank later in life.

Sexual conflict over parental care promotes the evolution of sex differences in care and the ability to care.

Strong asymmetries in parental care, with one sex providing more care than the other, are widespread across the animal kingdom. At present, two factors are thought to ultimately cause sex differences in care: certainty of parentage and sexual selection. By contrast, we here show that the coevolution of care and the ability to care can result in strong asymmetries in both the ability to care and the level of care, even in the absence of these factors. While the coevolution of care and the ability to care does not predict which sex evolves to care more than the other, once other factors give rise to even the slightest differences in the cost and benefits of care between the sexes (e.g. differences in certainty in parentage), a clear directionality emerges; the sex with the lower cost or higher benefit of care evolves both to be more able to care and to provide much higher levels of care than the other sex. Our findings suggest that the coevolution of levels of care and the ability to care may be a key factor underlying the evolution of sex differences in care.

Limited clinical benefit for surveillance PET-CT scanning in patients with histologically transformed lymphoma in complete metabolic remission following primary therapy.

The optimum follow-up of patients with transformed indolent lymphoma (TrIL) is not well defined. We sought to determine the utility of surveillance positron emission tomography-computed tomography (PET-CT) in patients with TrIL achieving complete metabolic remission (CMR) after primary therapy. We performed a retrospective analysis of patients with TrIL treated at Peter MacCallum Cancer Centre between 2002 and 2012 who achieved CMR after primary therapy who had ≥1 subsequent surveillance PET-CT. Of 55 patients with TrIL, 37 (67 %) received autologous stem cell transplantation as consolidation following chemoimmunotherapy. After a median follow-up of 34 (range 3-101) months, the actuarial 3-year progression-free (PFS) and overall survival (OS) were 77 % (95 %CI 62-86 %) and 88 % (75-94 %), respectively. Of 180 surveillance PET-CT scans, there were 153 true negatives, 4 false positives, 1 false negative, 7 indeterminate and 15 true positives. Considering indeterminate scans as false positives, the specificity of PET-CT for detecting relapse was 94 %, sensitivity was 83 %, positive predictive value was 63 % and negative predictive value was 98 %. All seven subclinical (PET detected) relapses were of low-grade histology; in contrast, all nine relapses with diffuse large B cell lymphoma (DLBCL) were symptomatic. In our cohort of patients with TrIL achieving CMR, PET-CT detected subclinical low-grade relapses but all DLBCL relapses were accompanied by clinical symptoms. Thus, surveillance imaging of patients with TrIL achieving CMR is of limited clinical benefit. PET-CT should be reserved for evaluation of clinically suspected relapse.

A phase III randomized trial of high-dose CEOP + filgrastim versus standard-dose CEOP in patients with non-Hodgkin lymphoma: 10-year follow-up data: Australasian Leukaemia and Lymphoma Group (ALLG) NHL07 trial.

Increasing dose intensity (DI) of chemotherapy for patients with aggressive non-Hodgkin lymphoma (NHL) may improve outcomes at the cost of increased toxicity. This issue was addressed in a randomized trial aiming to double the DI of myelosuppressive drugs. Between 1994 and 1999, 250 patients with previously untreated aggressive NHL were randomized to treatment with six cycles of 3-weekly standard (s) or intensive (i) chemotherapy: s-CEOP-cyclophosphamide 750, epirubicin 75, vincristine 1.4 mg/m(2) all on day 1, and prednisolone 100 mg days 1-5; i-CEOP-cyclophosphamide 1,500, epirubicin 150, vincristine 1.4 mg/m(2) all on day 1, and prednisolone 100 mg days 1-5. Primary endpoint was 5-year overall survival (OS). Relative to s-CEOP patients, i-CEOP patients achieved a 78% increase in the DI of cyclophosphamide and epirubicin. Despite this, there was no significant difference in any outcome: 5-year OS (56.7% i-CEOP; 55.1% s-CEOP; P = 0.80), 5-year progression free survival (PFS; 41% i-CEOP; 43% s-CEOP; P = 0.73), 5-year time to progression (TTP; 44% i-CEOP; 47% s-CEOP; P = 0.72), or complete remission (CR) + unconfirmed CR (CRu) rates (53% i-CEOP; 59% s-CEOP; P = 0.64). Long-term follow up at 10 years also showed no significant differences in OS, PFS, or TTP. The i-CEOP arm had higher rates of febrile neutropenia (70 vs. 26%), hospitalisations, blood product utilisation, haematological and gastrointestinal toxicities, and lower quality of life scores during treatment, although without significant differences 6-month later. In the treatment of aggressive NHL in the prerituximab era, increasing DI did not result in improved outcomes, while at the same time lead to increased toxicity.

Accurate decisions in an uncertain world: collective cognition increases true positives while decreasing false positives.

In a wide range of contexts, including predator avoidance, medical decision-making and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives; conversely, decreased false positives are associated with decreased true positives. We use an integrated theoretical and experimental approach to show that a group of decision-makers can overcome this basic limitation. Using a mathematical model, we show that a simple quorum decision rule enables individuals in groups to simultaneously increase true positives and decrease false positives. The results from a predator-detection experiment that we performed with humans are in line with these predictions: (i) after observing the choices of the other group members, individuals both increase true positives and decrease false positives, (ii) this effect gets stronger as group size increases, (iii) individuals use a quorum threshold set between the average true- and false-positive rates of the other group members, and (iv) individuals adjust their quorum adaptively to the performance of the group. Our results have broad implications for our understanding of the ecology and evolution of group-living animals and lend themselves for applications in the human domain such as the design of improved screening methods in medical, forensic, security and business applications.

Life-history trade-offs favour the evolution of animal personalities.

In recent years evidence has been accumulating that personalities are not only found in humans but also in a wide range of other animal species. Individuals differ consistently in their behavioural tendencies and the behaviour in one context is correlated with the behaviour in multiple other contexts. From an adaptive perspective, the evolution of animal personalities is still a mystery, because a more flexible structure of behaviour should provide a selective advantage. Accordingly, many researchers view personalities as resulting from constraints imposed by the architecture of behaviour (but see ref. 12). In contrast, we show here that animal personalities can be given an adaptive explanation. Our argument is based on the insight that the trade-off between current and future reproduction often results in polymorphic populations in which some individuals put more emphasis on future fitness returns than others. Life-history theory predicts that such differences in fitness expectations should result in systematic differences in risk-taking behaviour. Individuals with high future expectations (who have much to lose) should be more risk-averse than individuals with low expectations. This applies to all kinds of risky situations, so individuals should consistently differ in their behaviour. By means of an evolutionary model we demonstrate that this basic principle results in the evolution of animal personalities. It simultaneously explains the coexistence of behavioural types, the consistency of behaviour through time and the structure of behavioural correlations across contexts. Moreover, it explains the common finding that explorative behaviour and risk-related traits like boldness and aggressiveness are common characteristics of animal personalities.

Reproductive individuality of clonal fish raised in near-identical environments and its link to early-life behavioral individuality.

Recent studies have documented among-individual phenotypic variation that emerges in the absence of apparent genetic and environmental differences, but it remains an open question whether such seemingly stochastic variation has fitness consequences. We perform a life-history experiment with naturally clonal fish, separated directly after birth into near-identical (i.e., highly standardized) environments, quantifying 2522 offspring from 152 broods over 280 days. We find that (i) individuals differ consistently in the size of offspring and broods produced over consecutive broods, (ii) these differences are observed even when controlling for trade-offs between brood size, offspring size and reproductive onset, indicating individual differences in life-history productivity and (iii) early-life behavioral individuality in activity and feeding patterns, with among-individual differences in feeding being predictive of growth, and consequently offspring size. Thus, our study provides experimental evidence that even when minimizing genetic and environmental differences, systematic individual differences in life-history measures and ultimately fitness can emerge.

On the evolution of personalities via frequency-dependent selection.

Personality differences can be found in a wide range of species across the animal kingdom, but why natural selection gave rise to such differences remains an open question. Frequency-dependent selection is a potent mechanism explaining variation; it does not explain, however, the other two key features associated with personalities, consistency and correlations. Using the hawk-dove game and a frequency-dependent foraging game as examples, we here show that this changes fundamentally whenever one takes into account the physiological architecture underlying behavior (e.g., metabolism). We find that the inclusion of physiology changes the evolutionary predictions concerning consistency and correlations: while selection gives rise to inconsistent individuals and stochastically fluctuating behavioral correlations in scenarios that neglect physiology, we find high levels of behavioral consistency and tight and stable trait correlations in scenarios that incorporate physiology. The coevolution of behavioral and physiological traits also gives rise to adaptive physiological differences that are systematically associated with behavioral differences. As well as providing a framework for understanding behavioral consistency and behavioral correlations, our work thus also provides an explanation for systematic physiological differences within populations, a phenomenon that appears to exist in a wide range of species but that, up to now, has been poorly understood.

Emergence of central nervous system myeloma in the era of novel agents.

Although multiple myeloma (MM) remains an incurable disease, considerable improvements in survival have been made with the introduction of autologous stem cell transplantation and new drugs. Central nervous system (CNS) MM is a rare complication associated with poor survival. Historically, CNS disease developed early in the course of MM; however recently, patients often present with CNS disease following multiple lines of therapy. It is hypothesized that exposure to novel agents (thalidomide, lenalidomide and bortezomib) changes the natural history of MM, increasing the lifetime risk of CNS disease. We analysed the baseline characteristics, treatment and outcome data of patients who presented with CNS MM at Peter MacCallum Cancer Centre between 2001 and 2010. Seven patients were identified, from 2005 onwards. All patients were Durie-Salmon stage IIIA or IIIB and International Staging System Scores I to III at baseline. All had received at least three lines of therapy, including high-dose chemotherapy with autologous stem cell transplantation and a novel agent, prior to developing CNS MM. Median time from diagnosis to CNS disease was 24 months (range 10-42). All patients died after developing CNS disease with median survival post-CNS disease of 2 months (range 1-23). The incidence of CNS MM is increasing, and time to development of CNS manifestations is prolonging, associated with increased use of high-dose chemotherapy and novel agents. Whether this is due to improved overall survival or specific characteristics of these therapies is not clear. Despite the availability of novel agents, survival after CNS MM remains poor.

Developmental feedbacks and the emergence of individuality.

Behavioural individuality is a hallmark of animal life, with major consequences for fitness, ecology, and evolution. One of the most widely invoked explanations for this variation is that feedback loops between an animal's behaviour and its state (e.g. physiology, informational state, social rank, etc.) trigger and shape the development of individuality. Despite their often-cited importance, however, little is known about the ultimate causes of such feedbacks. Expanding on a previously employed model of adaptive behavioural development under uncertainty, we find that (i) behaviour-state feedbacks emerge as a direct consequence of adaptive behavioural development in particular selective environments and (ii) that the sign of these feedbacks, and thus the consequences for the development of behavioural individuality, can be directly predicted by the shape of the fitness function, with increasing fitness benefits giving rise to positive feedbacks and trait divergence and decreasing fitness benefits leading to negative feedbacks and trait convergence. Our findings provide a testable explanatory framework for the emergence of developmental feedbacks driving individuality and suggest that such feedbacks and their associated patterns of behavioural diversity are a direct consequence of adaptive behavioural development in particular selective environments.

The emergence and development of behavioral individuality in clonal fish.

Behavioral individuality is a ubiquitous phenomenon in animal populations, yet the origins and developmental trajectories of individuality, especially very early in life, are still a black box. Using a high-resolution tracking system, we mapped the behavioral trajectories of genetically identical fish (Poecilia formosa), separated immediately after birth into identical environments, over the first 10 weeks of their life at 3 s resolution. We find that (i) strong behavioral individuality is present at the very first day after birth, (ii) behavioral differences at day 1 of life predict behavior up to at least 10 weeks later, and (iii) patterns of individuality strengthen gradually over developmental time. Our results establish a null model for how behavioral individuality can develop in the absence of genetic and environmental variation and provide experimental evidence that later-in-life individuality can be strongly shaped by factors pre-dating birth like maternal provisioning, epigenetics and pre-birth developmental stochasticity.

On the coevolution of social responsiveness and behavioural consistency.

Recent research focuses on animal personalities, that is individual differences in behaviour that are consistent across contexts and over time. From an adaptive perspective, such limited behavioural plasticity is surprising, since a more flexible structure of behaviour should provide a selective advantage. Here, we argue that consistency can be advantageous because it makes individuals predictable. Predictability, however, can only be advantageous if at least some individuals in the population respond to individual differences. Consequently, the evolution of consistency and responsiveness are mutually dependent. We present a general analysis of this coevolutionary feedback for scenarios that can be represented as matrix games with two pure strategies (e.g. hawk-dove game, snowdrift game). We first show that responsive strategies are favoured whenever some individual differences are present in the population (e.g. due to mutation and drift). We then show that the presence of responsive individuals can trigger a coevolutionary process between responsiveness and consistency that gives rise to populations in which responsive individuals coexist with unresponsive individuals who show high levels of adaptive consistency in their behaviour. Next to providing an adaptive explanation for consistency, our results also link two key features associated with personalities, individual differences in responsiveness and behavioural consistency.

Evolutionary emergence of responsive and unresponsive personalities.

In many animal species, individuals differ consistently in suites of correlated behaviors, comparable with human personalities. Increasing evidence suggests that one of the fundamental factors structuring personality differences is the responsiveness of individuals to environmental stimuli. Whereas some individuals tend to be highly responsive to such stimuli, others are unresponsive and show routine-like behaviors. Much research has focused on the proximate causes of these differences but little is known about their evolutionary origin. Here, we provide an evolutionary explanation. We develop a simple but general evolutionary model that is based on two key ingredients. First, the benefits of responsiveness are frequency-dependent; that is, being responsive is advantageous when rare but disadvantageous when common. This explains why responsive and unresponsive individuals can coexist within a population. Second, positive-feedback mechanisms reduce the costs of responsiveness; that is, responsiveness is less costly for individuals that have been responsive before. This explains why individuals differ consistently in their responsiveness, across contexts and over time. As a result, natural selection gives rise to stable individual differences in responsiveness. Whereas some individuals respond to environmental stimuli in all kinds of contexts, others consistently neglect such stimuli. Interestingly, such differences induce correlations among all kinds of other traits (e.g., boldness and aggressiveness), thus providing an explanation for environment-specific behavioral syndromes.

Pooling decisions decreases variation in response bias and accuracy.

Decision makers in contexts as diverse as medical, judicial, and political decision making are known to differ substantially in response bias and accuracy, and these differences are a major factor undermining the reliability and fairness of the respective decision systems. Using theoretical modeling and empirical testing across five domains, we show that collective systems based on pooling decisions robustly overcome this important but as of now unresolved problem of experts' heterogeneity. In breast and skin cancer diagnostics and fingerprint analysis, we find that pooling the decisions of five experts reduces the variation in sensitivity among decision makers by 52%, 54%, and 41%, respectively. Similar reductions are achieved for specificity and response bias, and in other domains. Thus, although outcomes in individual decision systems are highly variable and at the mercy of individual decision makers, collective systems based on pooling decrease this variation, thereby promoting reliability, fairness, and possibly even trust.