Mulcahy, N. J., & Call, J. (2006). Apes save tools for future use. Science, 312(5776), 1038–1040.
Abstract: Planning for future needs, not just current ones, is one of the most formidable human cognitive achievements. Whether this skill is a uniquely human adaptation is a controversial issue. In a study we conducted, bonobos and orangutans selected, transported, and saved appropriate tools above baseline levels to use them 1 hour later (experiment 1). Experiment 2 extended these results to a 14-hour delay between collecting and using the tools. Experiment 3 showed that seeing the apparatus during tool selection was not necessary to succeed. These findings suggest that the precursor skills for planning for the future evolved in great apes before 14 million years ago, when all extant great ape species shared a common ancestor.
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Kirkwood, J. K. (2000). Animal minds and animal welfare. Vet. Rec., 146(11), 327.
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Helton, W. S. (2005). Animal expertise, conscious or not. Anim. Cogn., 8(2), 67–74.
Abstract: Rossano (Cognition 89:207, 2003) proposes expertise as an indicator of consciousness in humans and other animals. Since there is strong evidence that the development of expertise requires deliberate practice (Ericsson in The road to excellence: the acquisition of expert performance in the arts and sciences, sports and games 1996), and deliberate practice appears to be outside of the bounds of unconscious processing, then any signs of expertise development in an animal are indicators of consciousness. Rossano's argument may lead to an unsolvable debate about animal consciousness while causing researchers to overlook the underlying reality of animal expertise. This article provides evidence indicative of animals meeting each of the three definitions of expertise established in the scientific literature: expertise as a social construction, expertise as exceptional performance, and expertise as knowledge. In addition, cases of deliberate practice by non-human animals are offered. Acknowledging some animals as experts, regardless of consciousness, is warranted by the research findings and would prove useful in solving many issues remaining in the human expertise literature.
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Pennisi, E. (2006). Animal cognition. Social animals prove their smarts (Vol. 312).
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Pennisi, E. (2006). Animal cognition. Man's best friend(s) reveal the possible roots of social intelligence (Vol. 312).
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Epstein, R. (1985). Animal cognition as the praxist views it. Neurosci Biobehav Rev, 9(4), 623–630.
Abstract: The distinction between psychology and praxics provides a clear answer to the question of animal cognition. As Griffin and others have noted, the kinds of behavioral phenomena that lead psychologists to speak of cognition in humans are also observed in nonhuman animals, and therefore those who are convinced of the legitimacy of psychology should not hesitate to speak of and to attempt to study animal cognition. The behavior of organisms is also a legitimate subject matter, and praxics, the study of behavior, has led to significant advances in our understanding of the kinds of behaviors that lead psychologists to speak of cognition. Praxics is a biological science; the attempt by students of behavior to appropriate psychology has been misguided. Generativity theory is an example of a formal theory of behavior that has proved useful both in the engineering of intelligent performances in nonhuman animals and in the prediction of intelligent performances in humans.
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Real, L. A. (1991). Animal choice behavior and the evolution of cognitive architecture. Science, 253(5023), 980–986.
Abstract: Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.
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Moses, S. N., Villate, C., & Ryan, J. D. (2006). An investigation of learning strategy supporting transitive inference performance in humans compared to other species. Neuropsychologia, 44(8), 1370–1387.
Abstract: Generalizations about neural function are often drawn from non-human animal models to human cognition, however, the assumption of cross-species conservation may sometimes be invalid. Humans may use different strategies mediated by alternative structures, or similar structures may operate differently within the context of the human brain. The transitive inference problem, considered a hallmark of logical reasoning, can be solved by non-human species via associative learning rather than logic. We tested whether humans use similar strategies to other species for transitive inference. Results are crucial for evaluating the validity of widely accepted assumptions of similar neural substrates underlying performance in humans and other animals. Here we show that successful transitive inference in humans is unrelated to use of associative learning strategies and is associated with ability to report the hierarchical relationship among stimuli. Our work stipulates that cross-species generalizations must be interpreted cautiously, since performance on the same task may be mediated by different strategies and/or neural systems.
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Straub, A. (2007). An intelligent crow beats a lab. Science, 316(5825), 688.
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Okamoto, S., Tomonaga, M., Ishii, K., Kawai, N., Tanaka, M., & Matsuzawa, T. (2002). An infant chimpanzee (Pan troglodytes) follows human gaze. Anim. Cogn., 5(2), 107–114.
Abstract: The ability of non-human primates to follow the gaze of other individuals has recently received much attention in comparative cognition. The aim of the present study was to investigate the emergence of this ability in a chimpanzee infant. The infant was trained to look at one of two objects, which an experimenter indicated by one of four different cue conditions: (1) tapping on the target object with a finger; (2) pointing to the target object with a finger; (3) gazing at the target object with head orientation; or (4) glancing at the target object without head orientation. The subject was given food rewards independently of its responses under the first three conditions, so that its responses to the objects were not influenced by the rewards. The glancing condition was tested occasionally, without any reinforcement. By the age of 13 months, the subject showed reliable following responses to the object that was indicated by the various cues, including glancing alone. Furthermore, additional tests clearly showed that the subject's performance was controlled by the “social” properties of the experimenter-given cues but not by the non-social, local-enhancing peripheral properties.
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