Long-term repeatability of cognitive performance.

Measures of cognitive performance, derived from psychometric tasks, have yielded important insights into the factors governing cognitive variation. However, concerns remain over the robustness of these measures, which may be susceptible to non-cognitive factors such as motivation and persistence. Efforts to quantify short-term repeatability of cognitive performance have gone some way to address this, but crucially the long-term repeatability of cognitive performance has been largely overlooked. Quantifying the long-term repeatability of cognitive performance provides the opportunity to determine the stability of cognitive phenotypes and the potential for selection to act on them. To this end, we quantified long-term repeatability of cognitive performance in wild Australian magpies over a three-year period. Cognitive performance was repeatable in two out of four cognitive tasks-associative learning and reversal-learning performance was repeatable, but spatial memory and inhibitory control performance, although trending toward significance, was not. Measures of general cognitive performance, obtained from principal components analyses carried out on each cognitive test battery, were highly repeatable. Together, these findings provide evidence that at least some cognitive phenotypes are stable, which in turn has important implications for our understanding of cognitive evolution.

Herbivory on the pedunculate oak along an urbanization gradient in Europe: Effects of impervious surface, local tree cover, and insect feeding guild.

Urbanization is an important driver of the diversity and abundance of tree-associated insect herbivores, but its consequences for insect herbivory are poorly understood. A likely source of variability among studies is the insufficient consideration of intra-urban variability in forest cover. With the help of citizen scientists, we investigated the independent and interactive effects of local canopy cover and percentage of impervious surface on insect herbivory in the pedunculate oak (Quercus robur L.) throughout most of its geographic range in Europe. We found that the damage caused by chewing insect herbivores as well as the incidence of leaf-mining and gall-inducing herbivores consistently decreased with increasing impervious surface around focal oaks. Herbivory by chewing herbivores increased with increasing forest cover, regardless of impervious surface. In contrast, an increase in local canopy cover buffered the negative effect of impervious surface on leaf miners and strengthened its effect on gall inducers. These results show that-just like in non-urban areas-plant-herbivore interactions in cities are structured by a complex set of interacting factors. This highlights that local habitat characteristics within cities have the potential to attenuate or modify the effect of impervious surfaces on biotic interactions.

Schoolchildren cooperate more successfully with non-kin than with siblings.

Cooperation plays a key role in the development of advanced societies and can be stabilized through shared genes (kinship) or reciprocation. In humans, cooperation among kin occurs more readily than cooperation among non-kin. In many organisms, cooperation can shift with age (e.g. helpers at the nest); however, little is known about developmental shifts between kin and non-kin cooperation in humans. Using a cooperative game, we show that 3- to 10-year-old French schoolchildren cooperated less successfully with siblings than with non-kin children, whether or not non-kin partners were friends. Furthermore, children with larger social networks cooperated better and the perception of friendship among non-friends improved after cooperating. These results contrast with the well-established preference for kin cooperation among adults and indicate that non-kin cooperation in humans might serve to forge and extend non-kin social relationships during middle childhood and create opportunities for future collaboration beyond kin. Our results suggest that the current view of cooperation in humans may only apply to adults and that future studies should focus on how and why cooperation with different classes of partners might change during development in humans across cultures as well as other long-lived organisms.

Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub.

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.

Contrasting the seasonal and elevational prevalence of generalist avian haemosporidia in co-occurring host species.

Understanding the ecology and evolution of parasites is contingent on identifying the selection pressures they face across their infection landscape. Such a task is made challenging by the fact that these pressures will likely vary across time and space, as a result of seasonal and geographical differences in host susceptibility or transmission opportunities. Avian haemosporidian blood parasites are capable of infecting multiple co-occurring hosts within their ranges, yet whether their distribution across time and space varies similarly in their different host species remains unclear. Here, we applied a new PCR method to detect avian haemosporidia (genera Haemoproteus, Leucocytozoon, and Plasmodium) and to determine parasite prevalence in two closely related and co-occurring host species, blue tits (Cyanistes caeruleus, N = 529) and great tits (Parus major, N = 443). Our samples were collected between autumn and spring, along an elevational gradient in the French Pyrenees and over a three-year period. Most parasites were found to infect both host species, and while these generalist parasites displayed similar elevational patterns of prevalence in the two host species, this was not always the case for seasonal prevalence patterns. For example, Leucocytozoon group A parasites showed inverse seasonal prevalence when comparing between the two host species, being highest in winter and spring in blue tits but higher in autumn in great tits. While Plasmodium relictum prevalence was overall lower in spring relative to winter or autumn in both species, spring prevalence was also lower in blue tits than in great tits. Together, these results reveal how generalist parasites can exhibit host-specific epidemiology, which is likely to complicate predictions of host-parasite co-evolution.

How Can We Study the Evolution of Animal Minds?

During the last 50 years, comparative cognition and neurosciences have improved our understanding of animal minds while evolutionary ecology has revealed how selection acts on traits through evolutionary time. We describe how cognition can be subject to natural selection like any other biological trait and how this evolutionary approach can be used to understand the evolution of animal cognition. We recount how comparative and fitness methods have been used to understand the evolution of cognition and outline how these approaches could extend our understanding of cognition. The fitness approach, in particular, offers unprecedented opportunities to study the evolutionary mechanisms responsible for variation in cognition within species and could allow us to investigate both proximate (i.e., neural and developmental) and ultimate (i.e., ecological and evolutionary) underpinnings of animal cognition together. We highlight recent studies that have successfully shown that cognitive traits can be under selection, in particular by linking individual variation in cognition to fitness. To bridge the gap between cognitive variation and fitness consequences and to better understand why and how selection can occur on cognition, we end this review by proposing a more integrative approach to study contemporary selection on cognitive traits combining socio-ecological data, minimally invasive neuroscience methods and measurement of ecologically relevant behaviors linked to fitness. Our overall goal in this review is to build a bridge between cognitive neuroscientists and evolutionary biologists, illustrate how their research could be complementary, and encourage evolutionary ecologists to include explicit attention to cognitive processes in their studies of behavior.

Fast ventral stream neural activity enables rapid visual categorization.

Primates can recognize objects embedded in complex natural scenes in a glimpse. Rapid categorization paradigms have been extensively used to study our core perceptual abilities when the visual system is forced to operate under strong time constraints. However, the neural underpinning of rapid categorization remains to be understood, and the incredible speed of sight has yet to be reconciled with modern ventral stream cortical theories of object recognition. Here we recorded multichannel subdural electrocorticogram (ECoG) signals from intermediate areas (V4/PIT) of the ventral stream of the visual cortex while monkeys were actively engaged in a rapid animal/non-animal categorization task. A traditional event-related potential (ERP) analysis revealed short visual latencies (<50-70ms) followed by a rapidly developing visual selectivity (within ~20-30ms) for most electrodes. A multi-variate pattern analysis (MVPA) technique further confirmed that reliable animal/non-animal category information was possible from this initial ventral stream neural activity (within ~90-100ms). Furthermore, this early category-selective neural activity was (a) unaffected by the presentation of a backward (pattern) mask, (b) generalized to novel (unfamiliar) stimuli and (c) co-varied with behavioral responses (both accuracy and reaction times). Despite the strong prevalence of task-related information on the neural signal, task-irrelevant visual information could still be decoded independently of monkey behavior. Monkey behavioral responses were also found to correlate significantly with human behavioral responses for the same set of stimuli. Together, the present study establishes that rapid ventral stream neural activity induces a visually selective signal subsequently used to drive rapid visual categorization and that this visual strategy may be shared between human and non-human primates.

The neural dynamics of face detection in the wild revealed by MVPA.

Previous magnetoencephalography/electroencephalography (M/EEG) studies have suggested that face processing is extremely rapid, indeed faster than any other object category. Most studies, however, have been performed using centered, cropped stimuli presented on a blank background resulting in artificially low interstimulus variability. In contrast, the aim of the present study was to assess the underlying temporal dynamics of face detection presented in complex natural scenes. We recorded EEG activity while participants performed a rapid go/no-go categorization task in which they had to detect the presence of a human face. Subjects performed at ceiling (94.8% accuracy), and traditional event-related potential analyses revealed only modest modulations of the two main components classically associated with face processing (P100 and N170). A multivariate pattern analysis conducted across all EEG channels revealed that face category could, however, be readout very early, under 100 ms poststimulus onset. Decoding was linked to reaction time as early as 125 ms. Decoding accuracy did not increase monotonically; we report an increase during an initial 95-140 ms period followed by a plateau ∼140-185 ms-perhaps reflecting a transitory stabilization of the face information available-and a strong increase afterward. Further analyses conducted on individual images confirmed these phases, further suggesting that decoding accuracy may be initially driven by low-level stimulus properties. Such latencies appear to be surprisingly short given the complexity of the natural scenes and the large intraclass variability of the face stimuli used, suggesting that the visual system is highly optimized for the processing of natural scenes.

Humans and monkeys share visual representations.

Conceptual abilities in animals have been shown at several levels of abstraction, but it is unclear whether the analogy with humans results from convergent evolution or from shared brain mechanisms inherited from a common origin. Macaque monkeys can access "non-similarity-based concepts," such as when sorting pictures containing a superordinate target category (animal, tree, etc.) among other scenes. However, such performances could result from low-level visual processing based on learned regularities of the photographs, such as for scene categorization by artificial systems. By using pictures of man-made objects or animals embedded in man-made or natural contexts, the present study clearly establishes that macaque monkeys based their categorical decision on the presence of the animal targets regardless of the scene backgrounds. However, as is found with humans, monkeys performed better with categorically congruent object/context associations, especially when small object sizes favored background information. The accuracy improvements and the response-speed gains attributable to superordinate category congruency in monkeys were strikingly similar to those of human subjects tested with the same task and stimuli. These results suggest analogous processing of visual information during the activation of abstract representations in both humans and monkeys; they imply a large overlap between superordinate visual representations in humans and macaques as well as the implicit use of experienced associations between object and context.