Visual artificial grammar learning: comparative research on humans, kea (Nestor notabilis) and pigeons (Columba livia)

Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Prese...

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Bibliographic Details
Published inPhilosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 367; no. 1598; pp. 1995 - 2006
Main Authors Stobbe, Nina, Westphal-Fitch, Gesche, Aust, Ulrike, Fitch, W. Tecumseh
Format Journal Article
LanguageEnglish
Published England The Royal Society 19.07.2012
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Summary:Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Presenting entire visual patterns simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human participants. After being trained to discriminate between two types of visual patterns generated by rules at different levels of computational complexity and presented on a computer screen, birds and humans received further training with a series of novel stimuli that followed the same rules, but differed in various visual features from the training stimuli. Most avian and all human subjects continued to perform well above chance during this initial generalization phase, suggesting that they were able to generalize learned rules to novel stimuli. However, detailed testing with stimuli that violated the intended rules regarding the exact number of stimulus elements indicates that neither bird species was able to successfully acquire the intended pattern rule. Our data suggest that, in contrast to humans, these birds were unable to master a simple rule above the finite-state level, even with simultaneous item presentation and despite intensive training.
Bibliography:istex:7C02D065A1D53B6EEFB8598D0D61EAB2246CF6E8
href:rstb20120096.pdf
One contribution of 13 to a Theme Issue ‘Pattern perception and computational complexity’.
ArticleID:rstb20120096
ark:/67375/V84-WFL3MLGN-D
Theme Issue 'Pattern perception and computational complexity' compiled and edited by W. Tecumseh Fitch, Angela D. Friederici and Peter Hagoort
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0962-8436
1471-2970
1471-2970
DOI:10.1098/rstb.2012.0096