Animal Cognition: Deconstructing Avian Insight

SummaryA new study of how experience contributes to apparently insightful problem-solving by tool-using crows has shown that operating an apparatus with the beak or a stick promotes novel use of stones on the same apparatus

cognitive ecology (Real 1993; Dukas 1998a), evolutionary psychology (Daly & Wilson 1999) and comparative cognition

Cognitive processes such as perception, learning, memory and decision making play an important role in mate choice, foraging and many other behaviours. In this review, I summarize a few key ideas about animal cognition developed in a recent book (Shettleworth 1998, Cognition, Evolution and Behaviour) and briefly review some areas in which interdisciplinary research on animal cognition is currently proving especially productive. Cognition, broadly defined, includes all ways in which animals take in information through the senses, process, retain and decide to act on it. Studying animal cognition does not entail any particular position on whether or to what degree animals are conscious. Neither does it entail rejecting behaviourism in that one of the greatest challenges in studing animal cognition is to formulate clear behavioural criteria for inferring specific mental processes. Tests of whether or not apparently goaldirected behaviour is controlled by a representation of its goal, episodic-like memory in birds, and deceptive behaviour in monkeys provide examples. Functional modelling has been integrated with analyses of cognitive mechanisms in a number of areas, including studies of communication, models of how predator learning and attention affect the evolution of conspicuous and cryptic prey, tests of the relationship betweeen ecological demands on spatial cognition and brain evolution, and in research on social learning. Rather than a 'new field' of cognitive ecology, such interdisciplinary research on animal cognition exemplifies a revival of interest in proximate mechanisms of behaviour. 2001 The Association for the Study of Animal Behaviour T hroughout much of the 20th century, ethology and animal psychology developed independently Recently, however, students of animal behaviour have witnessed the emergence of a number of subfields with names that promise an integration of psychological and biological approaches to mechanisms of animal information processing and decision making

A Comparative Study of Geometric Rule Learning by Nutcrackers (\u3ci\u3eNucifraga columbiana\u3c/i\u3e), Pigeons (\u3ci\u3eColumba livia\u3c/i\u3e), and Jackdaws (\u3ci\u3eCorvus monedula\u3c/i\u3e )

Three avian species, a seed-caching corvid (Clark’s nutcrackers; Nucifraga columbiana), a non-seed-caching corvid (jackdaws; Corvus monedula), and a non-seed-caching columbid (pigeons; Columba livia), were tested for ability to learn to find a goal halfway between 2 landmarks when distance between the landmarks varied during training. All 3 species learned, but jackdaws took much longer than either pigeons or nutcrackers. The nutcrackers searched more accurately than either pigeons or jackdaws. Both nutcrackers and pigeons showed good transfer to novel landmark arrays in which interlandmark distances were novel, but inconclusive results were obtained from jackdaws. Species differences in this spatial task appear quantitative rather than qualitative and are associated with differences in natural history rather than phylogeny

Bayesian integration of spatial information

Spatial judgments and actions are often based on multiple cues. The authors review a multitude of phenomena on the integration of spatial cues in diverse species to consider how nearly optimally animals combine the cues. Under the banner of Bayesian perception, cues are sometimes combined and weighted in a near optimal fashion. In other instances when cues are combined, how optimal the integration is might be unclear. Only 1 cue may be relied on, or cues may seem to compete with one another. The authors attempt to bring some order to the diversity by taking into account the subjective discrepancy in the dictates of multiple cues. When cues are too discrepant, it may be best to rely on 1 cue source. When cues are not too discrepant, it may be advantageous to combine cues. Such a dual principle provides an extended Bayesian framework for understanding the functional reasons for the integration of spatial cues.13 page(s