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McLaren I.P.L. (1998). Animal Learning and Cognition: A neural network approach. Trends. Cognit. Sci., 2, 236.
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Vallortigara G. (1998). Minds of Their Own. Trends. Cognit. Sci., 2, 118.
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Tomasello M., Call J., & Hare B. (2003). Chimpanzees understand psychological states – the question is which ones and to what extent. Trends. Cognit. Sci., 7, 153–156.
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Schnall, S., & Gattis, M. (1998). Transitive Inference by Visual Reasoning. Retrieved June 6, 2024, from http://faculty.virginia.edu/schnall/Schnall%20&%20Gattis.pdf
Abstract: Two experiments are reported that investigated the influence
of linear spatial organization on transitive inference
performance. Reward/no-reward relations between
overlapping pairs of elements were presented in a context of
linear spatial order or random spatial order. Participants in
the linear arrangement condition showed evidence for visual
reasoning: They systematically mapped spatial relations to
conceptual relation and used the spatial relations to make
inferences on a reasoning task in a new spatial context. We
suggest that linear ordering may be a “good figure”, by
constituting a parsimonious representation for the integration
of premises, as well as for the inferencing process. The late
emergence of transitive inference in children may be the
result of limited cognitive capacity, which --unless an
external spatial array is available --constrains the
construction of an internal spatial array.
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Griffiths D., Dickinson A., & Clayton N. (1999). Episodic memory: what can animals remember about their past? Trends. Cognit. Sci., 3, 74–80.
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Byrne R.W. (2000). - Animal Cognition in Nature, edited by Russell P. Balda, Irene M. Pepperberg and Alan C. Kamil. Trends. Cognit. Sci., 4, 73.
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Hanggi, E. B. (2001). Can Horses Recognize Pictures? Proceedings of the Third International Conference of Cognitive Science, , 52–56.
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Hampton, R. R., Healy, S. D., Shettleworth, S. J., & Kamil, A. C. (2002). Neuroecologists' are not made of straw. Trends. Cognit. Sci., 6(1), 6–7.
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Bolhuis, J. J., & Macphail, E. M. (2001). A critique of the neuroecology of learning and memory. Trends. Cognit. Sci., 5(10), 426–433.
Abstract: Recent years have seen the emergence of neuroecology, the study of the neural mechanisms of behaviour guided by functional and evolutionary principles. This research has been of enormous value for our understanding of the evolution of brain- and species-specific behaviour. However, we question the validity of the neuroecological approach when applied to the analysis of learning and memory, given its arbitrary assumption that different [`]problems' engage different memory mechanisms. Differences in memory-based performance in [`]natural' tasks do not prove differences in memory capacity; similarly, differences in the use of memory in the natural environment do not provide a sound basis for expecting differences in anatomical structures that subserve learning and memory. This critique is illustrated with examples taken from the study of the neurobiology of food storing and song learning in birds.
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Markman, E. M., & Abelev, M. (2004). Word learning in dogs? Trends. Cognit. Sci., 8(11), 479–81; discussion 481.
Abstract: In a recent paper, Kaminski, Call and Fischer report pioneering research on word-learning in a dog. In this commentary we suggest ways of distinguishing referential word use from mere association. We question whether the dog is reasoning by exclusion and, if so, compare three explanations – learned heuristics, default assumptions, and pragmatic reasoning – as they apply to children and might apply to dogs. Kaminski et al.'s work clearly raises important questions about the origins and basis of word learning and social cognition.
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