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Memory lane

Descriptive

TitleInfo
Title
Memory lane
SubTitle
evaluating factors that contribute to long-term episodic memory
Name (type = personal)
NamePart (type = family)
Persaud
NamePart (type = given)
Kimele
NamePart (type = date)
1990-
DisplayForm
Kimele Persaud
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Hemmer
NamePart (type = given)
Pernille
DisplayForm
Pernille Hemmer
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2018
DateOther (type = degree); (qualifier = exact)
2018-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2018
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Visual working (WM) and long-term memory (LTM) are intricately intertwined. As such, current theories and models of VWM have been extended to characterize behavior in long-term memory. For example, a popular framework for investigating VWM is the remember-guess paradigm, which suggests that information is either recalled with some noise, or is no longer retrievable and individuals resort to random guessing (e.g. Brady et al., 2013). This framework has been extended to include an additional factor that contributes to memory, namely interference from non-target information (a.k.a. misassociations; Lew et al, 2015). In this way, individuals recall information with noise, missassociate memories to other task relevant information, or guess randomly. The compilation of these studies has identified the contribution of memory fidelity, misassociations, and random guesses to recall performance. Notably, the remember-guess framework stands in stark contrast to theoretical Bayesian models of memory, which suggests that prior knowledge and expectations for the statistical regularities of the environment influences recall from long-term memory (Hemmer & Steyvers, 2009b). The influence of prior knowledge is most prevalent when the stimuli in the memory tasks mirror the regularities of the natural world. In this dissertation, I seek to challenge current theories of memory regarding the contribution of fidelity, misassociations, and random guesses to LTM, by evaluating the simultaneous contribution of prior knowledge. The combination of results from these studies suggest that prior knowledge plays a crucial recall in reconstruction from long-term episodic memory, and when prior knowledge is brought to the task of remembering, it alters the contribution of misassociations and random guessing to recall performance.
Subject (authority = RUETD)
Topic
Psychology
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8836
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (x, 122 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Long-term memory
Note (type = statement of responsibility)
by Kimele Persaud
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3QJ7MR3
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Persaud
GivenName
Kimele
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2018-04-11 15:16:56
AssociatedEntity
Name
Kimele Persaud
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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ETD
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windows xp
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DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2018-04-11T15:15:22
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2018-04-11T15:15:22
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Microsoft® Word 2010
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