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The serial organisation of behaviour by non-human primates; an evaluation of experimental paradigms

By Carlo De Lillo


This article was published as Behavioural brain research, 1996, Vol. 81, [issues 1-2], pp. 1-17. It is available from:\ud only entryOn close examination of research programs which focus, either implicitly or explicitly, on the problem of the organisation of\ud serial order in non-human primates, it is possible to detect some limitations in the paradigms conventionally used. Serial learning\ud studies, which focus on the acquisition of arbitrary lists of unconnected elements point towards a distinction between the\ud representation of ordered series formed by monkeys and pigeons. However, the use of unconnected items prevents an assay of the\ud degree to which primates might be able to impose a structure over the list to be reported. The study of transitive reasoning has\ud been implemented by means of a paradigm where the order of a series is conveyed by presenting a common item in pairs of binary\ud discriminations. Animals tested with this paradigm develop control strategies using more information than that provided by reward\ud contingencies alone. A restriction of this paradigm is that, in its binary form, it does not allow a differentiation between the\ud performance of monkeys and pigeons and even simple models account for a transitive bias in the task. On the basis of these\ud observations it is proposed that novel paradigms which go beyond the binary context, feature multiple connected items, and\ud accord a high degree of spontaneity to the subjects might allow better than traditional ones to uncover qualitative different ways\ud in which different organisms serially organise their behaviour. Some recent research programs based on such rationale, and\ud implemented as search tasks, are then outlined and compared with other approaches to the study of search behaviour. Preliminary\ud results obtained from these studies indicate that th

Topics: Primates, serial learning, serial order, transitive inference, learning
Publisher: Elsevier
Year: 1996
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