scholarly journals Individual differences in memory search and their relation to intelligence.

2014 ◽  
Vol 143 (4) ◽  
pp. 1553-1569 ◽  
Author(s):  
M. Karl Healey ◽  
Patrick Crutchley ◽  
Michael J. Kahana
Keyword(s):  
Individual Differences ◽  
Memory Search

Focus shift and individual differences in the Sternberg memory-search task

1983 ◽  
Vol 53 (2) ◽  
pp. 129-139 ◽  
Author(s):  
Robert C. Haygood ◽  
David F. Johnson
Keyword(s):  
Individual Differences ◽  
Search Task ◽  
Memory Search

Computational modeling of individual differences in short term memory search

2007 ◽  
Vol 8 (3) ◽  
pp. 161-173 ◽  
Author(s):  
Adam Chuderski ◽  
Zbigniew Stettner ◽  
Jaroslaw Orzechowski
Keyword(s):  
Individual Differences ◽  
Computational Modeling ◽  
Short Term Memory ◽  
Memory Search ◽  
Short Term ◽  
Term Memory

Aging and individual differences in the development of skilled memory search performance.

1996 ◽  
Vol 11 (3) ◽  
pp. 497-520 ◽  
Author(s):  
Christopher Hertzog ◽  
Brian P. Cooper ◽  
Arthur D. Fisk
Keyword(s):  
Individual Differences ◽  
Memory Search ◽  
Search Performance

scholarly journals Individual Differences in Memory Search and Their Relation to Intelligence

2013 ◽  
Author(s):  
Karl Healey ◽  
Patrick Crutchley ◽  
Michael J. Kahana
Keyword(s):  
Individual Differences ◽  
Memory Search

The challenge of accounting for individual differences in folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Benjamin C. Ruisch ◽  
Rajen A. Anderson ◽  
David A. Pizarro
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Political Ideologies ◽  
Economic Beliefs ◽  
Existing Data

AbstractWe argue that existing data on folk-economic beliefs (FEBs) present challenges to Boyer & Petersen's model. Specifically, the widespread individual variation in endorsement of FEBs casts doubt on the claim that humans are evolutionarily predisposed towards particular economic beliefs. Additionally, the authors' model cannot account for the systematic covariance between certain FEBs, such as those observed in distinct political ideologies.

Individual differences, social attention, and the history of the social motivation hypotheses of autism

2019 ◽  
Vol 42 ◽  
Author(s):  
Peter C. Mundy
Keyword(s):  
Individual Differences ◽  
Early Development ◽  
Emotional Development ◽  
Social Motivation ◽  
Social Attention ◽  
Social Emotional Development ◽  
Social Emotional ◽  
Precise Understanding ◽  
The Social ◽  
History Of

Abstract The stereotype of people with autism as unresponsive or uninterested in other people was prominent in the 1980s. However, this view of autism has steadily given way to recognition of important individual differences in the social-emotional development of affected people and a more precise understanding of the possible role social motivation has in their early development.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

Inter-individual variation shapes the human microbiome

2019 ◽  
Vol 42 ◽  
Author(s):  
Emily F. Wissel ◽  
Leigh K. Smith
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Human Microbiome ◽  
Individual Variability ◽  
Microbiota Composition ◽  
Target Article ◽  
Microbiome Research

Abstract The target article suggests inter-individual variability is a weakness of microbiota-gut-brain (MGB) research, but we discuss why it is actually a strength. We comment on how accounting for individual differences can help researchers systematically understand the observed variance in microbiota composition, interpret null findings, and potentially improve the efficacy of therapeutic treatments in future clinical microbiome research.

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