The violation of expectation (VOE) paradigm and related habituation methods are the primary tools used to study higher-level cognition in preverbal infants. A common assumption of the paradigm is that longer looking to impossible events than possible events is indicative of infants' surprise at witnessing the impossible. Experiments can thus be designed to reveal infants' prior expectations for the behaviour of objects in the environment and so forth. This thesis explored the nature of infants' expectations in VOE-type events, and introduces pupil dilation as a novel dependent measure in tests of infant cognition. Chapter 1 reviews the history of, and rationale for, the use of habituation testing in infants, and presents the case for pupil dilation's potential as a viable and useful measure for tests in infancy. Chapters 2, 3 and 4 present four experiments in which infants are habituated to either possible or impossible events, before being tested on all event types, in order to explore the role of online learning in the formation of infants' expectations in VOE tasks. Both looking times and pupil dilation data were used as dependent measures in each of these tasks. In Chapter 5 Baillargeon's (1987; Baillargeon, Spelke, & Wasserman, 1985) influential 'drawbridge' experiments and the many subsequent replications of them are reviewed before a further replication is introduced in which the novel contribution of pupil dilation data is assessed. The discussion focuses on the findings of the empirical work of this thesis, and concludes that it is crucial to incorporate efforts to refute hypotheses into the designs of tests for infant cognition, and also that pupil data is a valuable complementary measure to, and potentially even superior than, looking times.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:529926 |
| Date | January 2011 |
| Creators | Jackson, Iain Robert |
| Contributors | Sirois, Sylvain ; Montaldi, Daniela |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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