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dc.contributor.authorGerard, Christophe J.
dc.contributor.authorMacKay, Harry A.
dc.contributor.authorThompson, Brooks
dc.contributor.authorMcIlvane, William J.
dc.date2022-08-11T08:10:53.000
dc.date.accessioned2022-08-23T17:23:30Z
dc.date.available2022-08-23T17:23:30Z
dc.date.issued2014-01-01
dc.date.submitted2013-12-23
dc.identifier.citation<p>Gerard CJ, Mackay HA, Thompson B, McIlvane WJ. Rapid generation of balanced trial distributions for discrimination learning procedures: a technical note. J Exp Anal Behav. 2014 Jan;101(1):171-8. doi: 10.1002/jeab.58. Epub 2013 Nov 19. PubMed PMID: 24249664; PubMed Central PMCID: PMC3995156. <a href="http://dx.doi.org/10.1002/jeab.58" target="_blank">Link to article on publisher's site</a></p>
dc.identifier.issn0022-5002 (Linking)
dc.identifier.doi10.1002/jeab.58
dc.identifier.pmid24249664
dc.identifier.urihttp://hdl.handle.net/20.500.14038/48974
dc.description.abstractWe describe novel computer algorithms for rapid, sometimes virtually instantaneous generation of trial sequences needed to instrument many behavioral research procedures. Implemented on typical desktop or laptop computers, the algorithms impose constraints to forestall development of undesired stimulus control by position, recent trial outcomes, and other variables that could impede simple and conditional discrimination learning. They yield trial-by-trial lists of sequences that can serve (1) as inputs to procedure control software or (2) in generating templates for constructing sessions for implementation by hand or machine.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=24249664&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3995156/
dc.subjectDiscrimination
dc.subjectMultitrial procedures
dc.subjectRapid session construction tool
dc.subjectBehavioral Neurobiology
dc.subjectBehavior and Behavior Mechanisms
dc.subjectExperimental Analysis of Behavior
dc.titleRapid generation of balanced trial distributions for discrimination learning procedures: A technical note
dc.typeJournal Article
dc.source.journaltitleJournal of the experimental analysis of behavior
dc.source.volume101
dc.source.issue1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/shriver_pp/51
dc.identifier.contextkey4943692
html.description.abstract<p>We describe novel computer algorithms for rapid, sometimes virtually instantaneous generation of trial sequences needed to instrument many behavioral research procedures. Implemented on typical desktop or laptop computers, the algorithms impose constraints to forestall development of undesired stimulus control by position, recent trial outcomes, and other variables that could impede simple and conditional discrimination learning. They yield trial-by-trial lists of sequences that can serve (1) as inputs to procedure control software or (2) in generating templates for constructing sessions for implementation by hand or machine.</p>
dc.identifier.submissionpathshriver_pp/51
dc.contributor.departmentIntellectual and Developmental Disabilities Research Center
dc.contributor.departmentShriver Center
dc.source.pages171-8


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