Legare, C. H., & Nielsen, M. (). Imitation and Innovation: The Dual Engines of Cultural Learning. Trends in Cognitive Sciences, 19(11), 688–699.
Abstract: Imitation and innovation work in tandem to support cultural learning in children and facilitate our capacity for cumulative culture. Here we propose an integrated theoretical account of how the unique demands of acquiring instrumental skills and cultural conventions provide insight into when children imitate, when they innovate, and to what degree. For instrumental learning, with an increase in experience, high fidelity imitation decreases and innovation increases. By contrast, for conventional learning, imitative fidelity stays high, regardless of experience, and innovation stays low. We synthesize cutting edge research on the development of imitative flexibility and innovation to provide insight into the social learning mechanisms underpinning the uniquely human mind.
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Worden, R. P. (1996). Primate social intelligence. Cognit. Sci., 20(4), 579–616.
Abstract: A computational theory of primate social intelligence is proposed in which primates represent social situations internally by discrete symbol structures, called scripts. Three well-defined computational operations on scripts are sufficient to support social learning, planning, and prediction. This gives a formal, predictive model with which to analyse how primate social knowledge is acquired, as well as how it is used. The theory is compared with primate data, such as Cheney and Seyfarth's observations of vervet monkeys. It gives simple, understandable script-based analyses of many observed phenomena--such as the recognition and use of kin relations, learning of alarm calls, habituation to calls, knowledge of rank, tactical deception, and attachment behaviour. I argue that a tight, concise theory of social cognition, such as script theory, is needed to explain the rapid learning and social guile seen in primates. It also has the benefits of simplicity and testability. The extension of scripts to incorporate a primate theory of mind is described in a subsequent paper.
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Schnall, S., & Gattis, M. (1998). Transitive Inference by Visual Reasoning.
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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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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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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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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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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