| Records |
Author  |
Galef, B.G.; Laland, K.N. |
| Title |
Social Learning in Animals: Empirical Studies and Theoretical Models |
Type |
Journal Article |
| Year |
2005 |
Publication |
BioScience |
Abbreviated Journal |
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| Volume |
55 |
Issue |
6 |
Pages |
489-499 |
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| Abstract |
AbstractThe last two decades have seen a virtual explosion in empirical research on the role of social interactions in the development of animals' behavioral repertoires, and a similar increase in attention to formal models of social learning. Here we first review recent empirical evidence of social influences on food choice, tool use, patterns of movement, predator avoidance, mate choice, and courtship, and then consider formal models of when animals choose to copy behavior, and which other animals' behavior they copy, together with empirical tests of predictions from those models. |
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0006-3568 |
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| Notes |
10.1641/0006-3568(2005)055[0489:Sliaes]2.0.Co;2 |
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| Call Number |
Equine Behaviour @ team @ |
Serial |
6398 |
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| Author |
Kiltie, R.A.; Fan, J.; Laine, A.F. |
| Title |
A wavelet-based metric for visual texture discrimination with applications in evolutionary ecology |
Type |
Journal Article |
| Year |
1995 |
Publication |
Mathematical Biosciences |
Abbreviated Journal |
Math Biosci |
| Volume |
126 |
Issue |
1 |
Pages |
21-39 |
| Keywords |
Animals; Carnivora; *Ecology; Equidae; *Evolution; Humans; Mathematics; Models, Biological; Moths; *Pattern Recognition, Visual; Pigmentation |
| Abstract |
Much work on natural and sexual selection is concerned with the conspicuousness of visual patterns (textures) on animal and plant surfaces. Previous attempts by evolutionary biologists to quantify apparency of such textures have involved subjective estimates of conspicuousness or statistical analyses based on transect samples. We present a method based on wavelet analysis that avoids subjectivity and that uses more of the information in image textures than transects do. Like the human visual system for texture discrimination, and probably like that of other vertebrates, this method is based on localized analysis of orientation and frequency components of the patterns composing visual textures. As examples of the metric's utility, we present analyses of crypsis for tigers, zebras, and peppered moth morphs. |
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Department of Zoology, University of Florida, Gainesville |
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English |
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0025-5564 |
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| Notes |
PMID:7696817 |
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no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
2660 |
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| Author |
Reddon, A.R.; Hurd, P.L. |
| Title |
Acting unilaterally: Why do animals with strongly lateralized brains behave differently than those with weakly lateralized brains? |
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Journal Article |
| Year |
2009 |
Publication |
Bioscience Hypotheses |
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| Volume |
2 |
Issue |
6 |
Pages |
383-387 |
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Cerebral lateralization; Individual variation; Personality; Habenula; Dorsal-diencephalic conduction system |
| Abstract |
Cerebral lateralization was once thought to be unique to humans, but is now known to be widespread among the vertebrates. Lateralization appears to confer cognitive advantages upon those that possess it. Despite the taxonomic ubiquity and described advantages of lateralization, substantial individual variation exists in all species. Individual variation in cerebral lateralization may be tied to individual variation in behaviour and the selective forces that act to maintain variation in behaviour may also act to maintain variation in lateralization. The mechanisms linking individual variation in the strength of cerebral lateralization to individual variation in behaviour remain obscure. We propose here a general hypothesis which may help to explain this link. We suggest that individuals with strong and weak lateralizations behave differently because of differences in the ability of one hemisphere to inhibit the functions of the other in each type of brain organization. We also suggest a specific mechanism involving the asymmetric epithalamic nucleus, the habenula. We conclude by discussing some predictions and potential tests of our hypothesis. |
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1756-2392 |
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no |
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Equine Behaviour @ team @ |
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5417 |
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