Linked Life Data

16532852

Source:http://linkedlifedata.com/resource/pubmed/id/16532852

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2006-3-14
pubmed:abstractText
We explore the implications of an event-based expectancy generation approach to language understanding, suggesting that one useful strategy employed by comprehenders is to generate expectations about upcoming words. We focus on two questions: (1) What role is played by elements other than verbs in generating expectancies? (2) What connection exists between expectancy generation and event-based knowledge? Because verbs follow their arguments in many constructions (particularly in verb-final languages), deferring expectations until the verb seems inefficient. Both human data and computational modeling suggest that other sentential elements may also play a role in predictive processing and that these constraints often reflect knowledge regarding typical events. We investigated these predictions, using both short and long stimulus onset asynchrony priming. Robust priming obtained when verbs were named aloud following typical agents, patients, instruments, and locations, suggesting that event memory is organized so that nouns denoting entities and objects activate the classes of events in which they typically play a role. These computations are assumed to be an important component of expectancy generation in sentence processing.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0090-502X
pubmed:author
pubmed:issnType
Print
pubmed:volume
33
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1174-84
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
A basis for generating expectancies for verbs from nouns.
pubmed:affiliation
Department of Psychology, Social Science Centre, University of Western Ontario, London, Ontario, Canada. mcrae@uwo.ca
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural