Predicting individual traits from unperformed tasks.

Relating individual differences in cognitive traits to brain functional organization is a long-lasting challenge for the neuroscience community. Individual intelligence scores were previously predicted from whole-brain connectivity patterns, extracted from functional magnetic resonance imaging (fMRI) data acquired at rest. Recently, it was shown that task-induced brain activation maps outperform these resting-state connectivity patterns in predicting individual intelligence, suggesting that a cognitively demanding environment improves prediction of cognitive abilities. Here, we use data from the Human Connectome Project to predict task-induced brain activation maps from resting-state fMRI, and proceed to use these predicted activity maps to further predict individual differences in a variety of traits. While models based on original task activation maps remain the most accurate, models based on predicted maps significantly outperformed those based on the resting-state connectome. Thus, we provide a promising approach for the evaluation of measures of human behavior from brain activation maps, that could be used without having participants actually perform the tasks.

Too much is bad: increasing numbers of livestock and conspecifics reduce body mass in an avian scavenger.

Individual traits such as body mass can serve as early warning signals of changes in the fitness prospects of animal populations facing environmental impacts. Here, taking advantage of a 19-yr monitoring, we assessed how individual, population, and environmental factors modulate long-term changes in the body mass of Canarian Egyptian vultures. Individual vulture body mass increased when primary productivity was highly variable, but decreased in years with a high abundance of livestock. We hypothesized that carcasses of wild animals, a natural food resource that can be essential for avian scavengers, could be more abundant in periods of weather instability but depleted when high livestock numbers lead to overgrazing. In addition, increasing vulture population numbers also negatively affect body mass suggesting density-dependent competition for food. Interestingly, the relative strength of individual, population and resource availability factors on body mass changed with age and territorial status, a pattern presumably shaped by differences in competitive abilities and/or age-dependent environmental knowledge and foraging skills. Our study supports that individual plastic traits may be extremely reliable tools to better understand the response of secondary consumers to current and future natural and human-induced environmental changes.

The effect of oxytocin on biological motion perception in dogs (Canis familiaris).

Recent studies have shown that the neuropeptide oxytocin is involved in the regulation of several complex human social behaviours. There is, however, little research on the effect of oxytocin on basic mechanisms underlying human sociality, such as the perception of biological motion. In the present study, we investigated the effect of oxytocin on biological motion perception in dogs (Canis familiaris), a species adapted to the human social environment and thus widely used to model many aspects of human social behaviour. In a within-subjects design, dogs (N = 39), after having received either oxytocin or placebo treatment, were presented with 2D projection of a moving point-light human figure and the inverted and scrambled version of the same movie. Heart rate (HR) and heart rate variability (HRV) were measured as physiological responses, and behavioural response was evaluated by observing dogs' looking time. Subjects were also rated on the personality traits of Neuroticism and Agreeableness by their owners. As expected, placebo-pretreated (control) dogs showed a spontaneous preference for the biological motion pattern; however, there was no such preference after oxytocin pretreatment. Furthermore, following the oxytocin pretreatment female subjects looked more at the moving point-light figure than males. The individual variations along the dimensions of Agreeableness and Neuroticism also modulated dogs' behaviour. Furthermore, HR and HRV measures were affected by oxytocin treatment and in turn played a role in subjects' looking behaviour. We discuss how these findings contribute to our understanding of the neurohormonal regulatory mechanisms of human (and non-human) social skills.

Impact of inter- and intra-specific competition among larvae on larval, adult, and life-table traits of Aedes aegypti and Aedes albopictus females.

Few studies have taken a comprehensive approach of measuring the impact of inter- and intra-specific larval competition on adult mosquito traits. In this study, the impact of competition Aedes aegypti and A. albopictus was quantified over the entire life of a cohort.Competitive treatments affected hatch-to-adult survivorship and development time to adulthood of females for both species, but affected median wing length of females only for A. albopictus. Competitive treatments had no significant effect on the median adult female longevity nor were there any effects on other individual traits related to bloodfeeding and reproductive success.Analysis of life table traits revealed no effect of competitive treatment on net reproductive rate (R0) but there were significant effects on cohort generation time (Tc) and cohort rate of increase (r) for both species.Inter-specific and intra-specific competition among Aedes larvae may produce individual and population-level effects that are manifest in adults; however, benign conditions may enable resulting adults to compensate for some impacts of competition, particularly those affecting blood feeding success, fecundity, and net reproductive rate, R0. The effect of competition, therefore, affects primarily larva - to - adult survivorship and larval development time, which in turn impact the cohort generation time, Tc and ultimately cohort rate of increase, r.The lack of effects of larval rearing environment on adult longevity suggests that effects on vectorial capacity due to longevity may be limited if adults have easy access to sugar and blood meals.

The Dynamic Model of Health Assets: a model development.

AIM: Epidemiological research on resistance and resilience can build on models of health developed in health promotion. Nevertheless, these models need to be adjusted to approaches currently employed in epidemiology; namely, included concepts should be easy to operationalize, and links between them should be simple enough to enable statistical modeling. In addition, these models should include both individual and environmental assets. The objective of this study is to consolidate the current knowledge on health assets, adjust them to epidemiological research needs, and propose a new model of health assets for epidemiological studies on health. DESIGN: The conceptual paper was conducted according to the guidelines for the model development. METHODS: The development of the new model was made from the perspective of salutogenesis - the branch of health promotion studying the origins of health. The analysis of literature on health promotion, public health, and positive psychology was conducted to find the links connecting individual and environmental assets. RESULTS: The newly developed Dynamic Model of Health Assets circularly links individual characteristics, actions, environments, and support. Each preceding component of the model contributes to the following one; each component also independently contributes to resistance and resilience. The new model may guide large-scale epidemiological research on resistance and resilience. The model's components are easy to operationalize; the model allows for constructing multilevel models and accounting for the dynamic nature of the relationships between components. It is also generic enough to be adjusted to studying contributors to resistance and resilience to different specific diseases. CONCLUSION: The new model can guide epidemiological studies on resistance and resilience.

Quantifying the Effects of Motivation on Listening Effort: A Systematic Review and Meta-Analysis.

Motivation influences the amount of listening effort (LE) exerted or experienced under challenging conditions, such as in high-noise environments. This systematic review and meta-analysis is the first to quantify the effects of motivation on LE. The review was pre-registered in PROSPERO, and performed in accordance with PRISMA guidelines. Eligible studies examined the influence of motivation or individual traits (related to motivation) on LE in adults. Motivational factors, coded as independent variables, included financial reward, evaluative threat, perceived competence, feedback, and individual traits. LE outcomes were categorized as subjective, behavioral, or physiological. The quality of evidence was assessed using an adaptation of the Cochrane Collaboration Risk of Bias Tool. Nested random-effects meta-analyses were performed to quantify and compare the influence of motivational factors across LE outcomes. After assessing 3,532 records, 48 studies met the inclusion criteria and 43 were included in the meta-analyses. Risk of bias was high, for example, many studies lacked sample size justification. Motivational factors had a small-to-medium effect (mean Cohen's d = 0.34, range: 0.11-0.72) on LE. When LE outcomes were considered collectively, an external manipulation of motivation (perceived competence) produced a larger mean effect size compared with individual traits. Some combinations of motivational factors and LE outcomes produced more robust effects than others, for example, evaluative threat and subjective LE outcomes. Although wide prediction intervals and high risk of bias mean that significant positive effects cannot be guaranteed, these findings provide useful guidance on the selection of motivational factors and LE outcomes for future research.

The Prediction of Brain Activity from Connectivity: Advances and Applications.

The human brain is composed of multiple, discrete, functionally specialized regions that are interconnected to form large-scale distributed networks. Using advanced brain-imaging methods and machine-learning analytical approaches, recent studies have demonstrated that regional brain activity during the performance of various cognitive tasks can be accurately predicted from patterns of task-independent brain connectivity. In this review article, we first present evidence for the predictability of brain activity from structural connectivity (i.e., white matter connections) and functional connectivity (i.e., temporally synchronized task-free activations). We then discuss the implications of such predictions to clinical populations, such as patients diagnosed with psychiatric disorders or neurologic diseases, and to the study of brain-behavior associations. We conclude that connectivity may serve as an infrastructure that dictates brain activity, and we pinpoint several open questions and directions for future research.

Are You "Gazing" at Me? How Others' Gaze Direction and Facial Expression Influence Gaze Perception and Postural Control.

In everyday life, interactions between humans are generally modulated by the value attributed to the situation, which partly relies on the partner's behavior. A pleasant or cooperating partner may trigger an approach behavior in the observer, while an unpleasant or threatening partner may trigger an avoidance behavior. In this context, the correct interpretation of other's intentions is crucial to achieve satisfying social interactions. Social cues such as gaze direction and facial expression are both fundamental and interrelated. Typically, whenever gaze direction and facial expression of others communicate the same intention, it enhances both the interlocutor's gaze direction and the perception of facial expressions (i.e., shared signal hypothesis). For instance, an angry face with a direct gaze is perceived as more intense since it represents a threat to the observer. In this study, we propose to examine how the combination of others' gaze direction (direct or deviated) and emotional facial expressions (i.e., happiness, fear, anger, sadness, disgust, and neutrality) influence the observer's gaze perception and postural control. Gaze perception was indexed by the cone of direct gaze (CoDG) referring to the width over which an observer feels someone's gaze is directed at them. A wider CoDG indicates that the observer perceived the face as looking at them over a wider range of gaze directions. Conversely, a narrower CoDG indicates a decrease in the range of gaze directions perceived as direct. Postural control was examined through the center of pressure displacements reflecting postural stability and approach-avoidance tendencies. We also investigated how both gaze perception and postural control may vary according to participants' personality traits and emotional states (e.g., openness, anxiety, etc.). Our results confirmed that gaze perception is influenced by emotional faces: a wider CoDGs was observed with angry and disgusted faces while a narrower CoDG was observed for fearful faces. Furthermore, facial expressions combined with gaze direction influence participants' postural stability but not approach-avoidance behaviors. Results are discussed in the light of the approach-avoidance model, by considering how some personality traits modulate the relation between emotion and posture.

Individual differences in light sensitivity affect sleep and circadian rhythms.

Artificial lighting is omnipresent in contemporary society with disruptive consequences for human sleep and circadian rhythms because of overexposure to light, particularly in the evening/night hours. Recent evidence shows large individual variations in circadian photosensitivity, such as melatonin suppression, due to artificial light exposure. Despite the emerging body of research indicating that the effects of light on sleep and circadian rhythms vary dramatically across individuals, recommendations for appropriate light exposure in real-life settings rarely consider such individual effects. This review addresses recently identified links among individual traits, for example, age, sex, chronotype, genetic haplotypes, and the effects of evening/night light on sleep and circadian hallmarks, based on human laboratory and field studies. Target biological mechanisms for individual differences in light sensitivity include differences occurring within the retina and downstream, such as the central circadian clock. This review also highlights that there are wide gaps of uncertainty, despite the growing awareness that individual differences shape the effects of evening/night light on sleep and circadian physiology. These include (1) why do certain individual traits differentially affect the influence of light on sleep and circadian rhythms; (2) what is the translational value of individual differences in light sensitivity in populations typically exposed to light at night, such as night shift workers; and (3) what is the magnitude of individual differences in light sensitivity in population-based studies? Collectively, the current findings provide strong support for considering individual differences when defining optimal lighting specifications, thus allowing for personalized lighting solutions that promote quality of life and health.

A Novel Estimation of Unobserved Pig Growth Traits for the Purposes of Precision Feeding Methods.

Recent technological advances make it possible to deliver feeding strategies that can be tailored to the needs of individual pigs in order to optimise the allocation of nutrient resources and contribute toward reducing excess nutrient excretion. However, these efforts are currently hampered by the challenges associated with: (1) estimation of unobserved traits from the available data on bodyweight and feed consumption; and (2) characterisation of the distributions and correlations of these unobserved traits to generate accurate estimates of individual level variation among pigs. Here, alternative quantitative approaches to these challenges, based on the principles of inverse modelling and separately inferring individual level distributions within a Bayesian context were developed and incorporated in a proposed precision feeding modelling framework. The objectives were to: (i) determine the average and distribution of individual traits characterising growth potential and body composition in an empirical population of growing-finishing barrows and gilts; (ii) simulate the growth and excretion of nitrogen and phosphorus of the average pig offered either a commercial two-phase feeding plan, or a precision feeding plan with daily adjustments; and (iii) simulate the growth and excretion of nitrogen and phosphorus across the pig population under two scenarios: a two-phase feeding plan formulated to meet the nutrient requirements of the average pig or a precision feeding plan with daily adjustments for each and every animal in the population. The distributions of mature bodyweight and ratio of lipid to protein weights at maturity had median (IQR) values of 203 (47.8) kg and 2.23 (0.814) kg/kg, respectively; these estimates were obtained without any prior assumptions concerning correlations between the traits. Overall, it was found that a proposed precision feeding strategy could result in considerable reductions in excretion of nitrogen and phosphorus (average pig: 8.07 and 9.17% reduction, respectively; heterogenous pig population: 22.5 and 22.9% reduction, respectively) during the growing-finishing period from 35 to 120 kg bodyweight. This precision feeding modelling framework is anticipated to be a starting point toward more accurate estimation of individual level nutrient requirements, with the general aim of improving the economic and environmental sustainability of future pig production systems.

Linking individual and population patterns of rocky-shore mussels.

Individual traits and population parameters can be used as proxies of processes taking place within a range of scales, thus improving the way we can evaluate species response to environmental variability. In intertidal rocky shores, patterns at the within-site scale, i.e., between centimeters to hundreds of meters, are important for understanding the population response into these highly variable environments. Here, we studied a rocky-shore mussel population at the within-site spatial scale (1) to test how intertidal height and orientation of the shore affect individual traits and population parameters, (2) to infer the link between individual and population level features, and (3) to explore the upscaling mechanisms driving population structure and processes. We analyzed the patterns of six population parameters: density, biomass, crowding, median individual size, recruitment and mortality rate, and four individual traits: growth rate, spawning phenology, size and condition index. Crowding was defined as the degree of overlapping of individuals within a given area, for which we created a "crowding index". Mussels were studied along the intertidal height gradient in two rocky shores with contrasted orientation at one site over a full year. Our results showed a significant effect of intertidal height and shore orientation on most of individual traits and population parameters studied. In contrast, biomass contained in a full covered surface did not vary in space nor in time. This pattern likely results from relatively constant crowding and a trade-off between median individuals' size and density. We hypothesize that growth, mortality and recruitment rates may all play roles in the stability of the crowding structure of mussel aggregations. Variation in spawning phenology between the two shores in the study site was also observed, suggesting different temporal dynamics of microclimate conditions. Interestingly, despite the different population size distribution between the two shores, our estimates indicate similar potential reproductive output. We hypothesize that the structure of the patches would tend to maintain or carry a maximum of biomass due to trade-offs between density and size while maintaining and maximizing the reproductive output. The patterns of spatial variability of individual traits and population parameters in our study site suggest that heterogeneous within-site conditions influence variation in individual performance and population processes. These results provide insights about the relationship between individual traits and how these relationships make patterns at the population level emerge. They provide baseline information necessary to improve models of metapopulation with spatially explicit processes.

Adverse health outcomes among workers of wood pellet production facilities.

INTRODUCTION: Workers of pellet production facilities (WPPF) are exposed to high concentrations of wood dust and microbial pollutants. Such stimulation may lead to numerous allergic and toxic reactions, infections, and other non-specific syndromes. OBJECTIVE: To check the influence of individual traits of workers and characteristic features / factors of their living and working environments on the probability of adverse outcomes' appearance. MATERIAL AND METHODS: The questionnaire study assessing adverse health effects resulting from individual exposure was conducted among 28 workers of 10 Polish WPPF. The logistic regression (for dichotomous variables) was used to determine the appearance probability (given as odds ratio) of adverse symptoms or diseases. RESULTS AND CONCLUSIONS: WPPF workers may have an increased risk of developing work-related adverse health outcomes. Both the individual traits and environmental exposure factors significantly influence the probability of their occurrence.

The effects of personality and locus of control on trust in humans versus artificial intelligence.

INTRODUCTION: We are increasingly exposed to applications that embed some sort of artificial intelligence (AI) algorithm, and there is a general belief that people trust any AI-based product or service without question. This study investigated the effect of personality characteristics (Big Five Inventory (BFI) traits and locus of control (LOC)) on trust behaviour, and the extent to which people trust the advice from an AI-based algorithm, more than humans, in a decision-making card game. METHOD: One hundred and seventy-one adult volunteers decided whether the final covered card, in a five-card sequence over ten trials, had a higher/lower number than the second-to-last card. They either received no suggestion (control), recommendations from what they were told were previous participants (humans), or an AI-based algorithm (AI). Trust behaviour was measured as response time and concordance (number of participants' responses that were the same as the suggestion), and trust beliefs were measured as self-reported trust ratings. RESULTS: It was found that LOC influences trust concordance and trust ratings, which are correlated. In particular, LOC negatively predicted beyond the BFI dimensions trust concordance. As LOC levels increased, people were less likely to follow suggestions from both humans or AI. Neuroticism negatively predicted trust ratings. Openness predicted reaction time, but only for suggestions from previous participants. However, people chose the AI suggestions more than those from humans, and self-reported that they believed such recommendations more. CONCLUSIONS: The results indicate that LOC accounts for a significant variance for trust concordance and trust ratings, predicting beyond BFI traits, and affects the way people select whom they trust whether humans or AI. These findings also support the AI-based algorithm appreciation.

The nature and nurture of ADHD and its comorbidities: A narrative review on twin studies.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children worldwide, and also the recognition of its persistence into adulthood is increasing. While ADHD in childhood is highly heritable and mostly driven by familial factors, during adulthood it appears to show a lower heritability, even if there is not total agreement on this yet. This disorder often co-occurs with many other conditions, which also vary across the different stages of development, and several studies have used the twin design to investigate these comorbidities, giving valuable insights into the origins of the observed co-occurrence. This review aims to summarize the main results of twin research, according to the following domains: individual traits, cognitive impairment, behavioral manifestations, clinical conditions and psychosocial risk factors. Individual features seem to play a role in this symptomatology and include personality traits such as negative emotionality, personality disorders and temperamental dimensions with a predominance of novelty seeking. At a lower level, ADHD is associated with both functional and anatomic brain characteristics. ADHD is also associated with some forms of cognitive impairment, such as sluggish cognitive tempo, and learning disabilities, with a specific predisposition to reading disability. In addition, ADHD is strongly associated with externalizing disorders such as conduct disorder and oppositional defiant disorder, and some behavioral outcomes, particularly substance use and abuse both in adolescence and adulthood. Moreover, ADHD symptoms often overlap with other psychological disorders, namely affective and internalizing disorders, as well as autism spectrum disorder and autistic-like traits in a wider sense. Notably, a genetic overlap has been found between asthma and ADHD, particularly with respect to hyperactivity/impulsivity dimensions. ADHD also appears to represent a risk factor for disordered eating, and, more specifically, for binge eating and bulimia nervosa. Finally, among psychosocial factors, an association has been proposed between childhood maltreatment and ADHD symptoms.

Tick parasitism in the Mediterranean spur-thighed tortoise in the Maamora forest, Morocco.

Macroparasites in general, and ectoparasites in particular, have the potential to regulate host population dynamics. In this context, this study addresses the tick parasitism traits of the Mediterranean spur-thighed tortoise (Testudo graeca) in the core area of its distribution range (northwestern Morocco, Maamora). It was discovered that 92.5% of the tortoises were parasitized by ticks in spring, with an infestation intensity and an abundance of 6.7 and 6.2 tick/tortoise, respectively. The observed parasitization rates were among the highest reported worldwide for T. graeca, which could relate to density-depended effects driving host-parasite interactions. The main tick species that parasitized the tortoises were Hyalomma aegyptium (95.6% of the ticks and in the 100% of the parasitized tortoises), Hy. marginatum, Hy. excavatum and Hy. scupense. Individual predictors for the tortoises, such as age, sex and the interaction between body condition and sex, were significantly related to tick abundance. Age-related behavioural differences might favour a higher host-tick effective contact in adults than in juveniles. The fact that males are more active in spring - the breeding season - might explain the observed male-bias in tick abundance and may also be responsible for the negative effect of male body condition on tick infestation rate in contrast to females. Given the potential role played by parasites as regards modulating population dynamics, our results suggest that ticks should be taken into account in the conservation and management programmes of this tortoise species.