Linked Life Data

11957400

Source:http://linkedlifedata.com/resource/pubmed/id/11957400

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2002-4-17
pubmed:abstractText
An overview of mechanistic and functional accounts of stimulus generalisation is given. Mechanistic accounts rely on the process of spreading activation across units representing stimuli. Different models implement the spread in different ways, ranging from diffusion to connectionist networks. A functional account proposed by Shepard analyses the probabilistic structure of the world for invariants. A universal law based on one such invariant claims that under a suitable scaling of the stimulus dimension, generalisation gradients should be approximately exponential in shape. Data from both vertebrates and invertebrates so far uphold Shepard's law. Some data on spatial generalisation in honeybees are presented to illustrate how Shepard's law can be used to determine the metric for combining discrepancies in different stimulus dimensions. The phenomenon of peak shift is discussed. Comments on mechanistic and functional approaches to generalisation are given.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1435-9448
pubmed:author
pubmed:issnType
Print
pubmed:volume
5
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
33-40
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Generalisation: mechanistic and functional explanations.
pubmed:affiliation
Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia. kcheng@axon.bhs.mq.edu.au
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't