Amanda Seed

Cognitive adaptations of social bonding in birds

The ‘social intelligence hypothesis’ was originally conceived to explain how primates may have evolved their superior intellect and large brains when compared with other animals. Although some birds such as corvids may be intellectually comparable to apes, the same relationship between sociality and brain size seen in primates has not been found for birds, possibly suggesting a role for other non-social factors. But bird sociality is different from primate sociality. Most monkeys and apes form stable groups, whereas most birds are monogamous, and only form large flocks outside of the breeding season. Some birds form lifelong pair bonds and these species tend to have the largest brains relative to body size. Some of these species are known for their intellectual abilities (e.g. corvids and parrots), while others are not (e.g. geese and albatrosses). Although socio-ecological factors may explain some of the differences in brain size and intelligence between corvids/parrots and geese/albatrosses, we predict that the type and quality of the bonded relationship is also critical. Indeed, we present empirical evidence that rook and jackdaw partnerships resemble primate and dolphin alliances. Although social interactions within a pair may seem simple on the surface, we argue that cognition may play an important role in the maintenance of long-term relationships, something we name as ‘relationship intelligence’.

The Evolution of Self-Control

Significance Although scientists have identified surprising cognitive flexibility in animals and potentially unique features of human psychology, we know less about the selective forces that favor cognitive evolution, or the proximate biological mechanisms underlying this process. We tested 36 species in two problem-solving tasks measuring self-control and evaluated the leading hypotheses regarding how and why cognition evolves. Across species, differences in absolute (not relative) brain volume best predicted performance on these tasks. Within primates, dietary breadth also predicted cognitive performance, whereas social group size did not. These results suggest that increases in absolute brain size provided the biological foundation for evolutionary increases in self-control, and implicate species differences in feeding ecology as a potential selective pressure favoring these skills. Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.

How does cognition evolve? Phylogenetic comparative psychology

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution.

Cooperative problem solving in rooks (Corvus frugilegus)

Recent work has shown that captive rooks, like chimpanzees and other primates, develop cooperative alliances with their conspecifics. Furthermore, the pressures hypothesized to have favoured social intelligence in primates also apply to corvids. We tested cooperative problem-solving in rooks to compare their performance and cognition with primates. Without training, eight rooks quickly solved a problem in which two individuals had to pull both ends of a string simultaneously in order to pull in a food platform. Similar to chimpanzees and capuchin monkeys, performance was better when within-dyad tolerance levels were higher. In contrast to chimpanzees, rooks did not delay acting on the apparatus while their partner gained access to the test room. Furthermore, given a choice between an apparatus that could be operated individually over one that required the action of two individuals, four out of six individuals showed no preference. These results may indicate that cooperation in chimpanzees is underpinned by more complex cognitive processes than that in rooks. Such a difference may arise from the fact that while both chimpanzees and rooks form cooperative alliances, chimpanzees, but not rooks, live in a variable social network made up of competitive and cooperative relationships.

Animal Tool-Use

The sight of an animal making and using a tool captivates scientists and laymen alike, perhaps because it forces us to question some of our ideas about human uniqueness. Does the animal know how the tool works? Did it anticipate the need for the tool and make it in advance? To some, this fascination with tools seems arbitrary and anthropocentric; after all, animals engage in many other complex activities, like nest building, and we know that complex behaviour need not be cognitively demanding. But tool-using behaviour can also provide a powerful window into the minds of living animals, and help us to learn what capacities we share with them - and what might have changed to allow for the incontrovertibly unique levels of technology shown by modern humans.

Chimpanzees solve the trap problem when the confound of tool-use is removed.

The trap-tube problem is difficult for chimpanzees to solve; in several studies only 1 to 2 subjects learn the solution. The authors tested eight chimpanzees on a non-tool-using version of the problem to investigate whether the inclusion of a tool in previous tests of the trap problem may have masked the ability of chimpanzees to solve it. All eight learned to avoid the trap, in 40 to 100 trials. One transferred to two tasks that had no visual cue in common. The authors examined the performance of 15 chimpanzees on a new task in a 2 x 2 design: seven had experience on the two-trap box, eight had not; half of each group was tested with a tool, half without one. An ANOVA revealed a significant effect of tool-inclusion and experience (p < .05). Our results show that including a tool in the trap problem profoundly affects the ability of chimpanzees to solve it. With regard to what the chimpanzees had learned, the results support the notion that rather than using the available stimuli as arbitrary cues, the subjects had encoded information about functional properties.

If at first you don't succeed… Studies of ontogeny shed light on the cognitive demands of habitual tool use

Many species use tools, but the mechanisms underpinning the behaviour differ between species and even among individuals within species, depending on the variants performed. When considering tool use ‘as adaptation’, an important first step is to understand the contribution made by fixed phenotypes as compared to flexible mechanisms, for instance learning. Social learning of tool use is sometimes inferred based on variation between populations of the same species but this approach is questionable. Specifically, alternative explanations cannot be ruled out because population differences are also driven by genetic and/or environmental factors. To better understand the mechanisms underlying routine but non-universal (i.e. habitual) tool use, we suggest focusing on the ontogeny of tool use and individual variation within populations. For example, if tool-using competence emerges late during ontogeny and improves with practice or varies with exposure to social cues, then a role for learning can be inferred. Experimental studies help identify the cognitive and developmental mechanisms used when tools are used to solve problems. The mechanisms underlying the route to tool-use acquisition have important consequences for our understanding of the accumulation in technological skill complexity over the life course of an individual, across generations and over evolutionary time.

Animal Cognition: An End to Insight?

Once hailed as insightful, the string-pulling behaviour of birds may actually rely on immediate visual feedback rather than mental simulation or planning. But is this an end to the study of animal insight or a call for a new approach?

Do crows reason about causes or agents? The devil is in the controls

In a recent issue of PNAS, Taylor et al. (1) claimed that New Caledonian crows can reason about hidden causal agents (HCAs). Crows first experienced three trials in the HCA condition: they saw a human enter a hide within their aviary; a stick being poked from the hide toward a foraging site; and the human leaving. In the subsequent unknown causal agent (UCA) condition, the crows only saw the poking. The animals inspected the hide less often in the first condition, prompting the authors to suggest that the crows “attributed the movement of the stick…to the agent” and that the crows inferred that the stick was unlikely to move again once the human had left. The authors encouraged future comparative studies to adopt the same methodology to uncover the evolutionary forces that led to this cognitive ability, which we agree would be an interesting endeavor. However, we suggest additional controls are critical if the results are to be diagnostic of the ability to represent causes or agency.

Problem-Solving in Tool-Using and Non-Tool-Using Animals

Physical problem-solving is defined as the use of a novel means to reach a goal when direct means are unavailable. Problem-solving in the wild (approximated by reports of innovation) correlates with relative forebrain size in mammals and birds. In the laboratory, various cognitive and noncognitive factors influence problem-solving, making species comparisons difficult, but there is no evidence that tool-users outperform nontool-users. Most work has focused on large-brained primates and corvids, which show fast and flexible problem-solving in many contexts. Several theories concerning the cognitive processes are involved, including roles for predispositions, learning, representation, causal knowledge, and inference.