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Differences in cognitive aging: typology based on a community structure detection approach

Overview of attention for article published in Frontiers in Aging Neuroscience, March 2015
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Title
Differences in cognitive aging: typology based on a community structure detection approach
Published in
Frontiers in Aging Neuroscience, March 2015
DOI 10.3389/fnagi.2015.00035
Pubmed ID
Authors

Emi Saliasi, Linda Geerligs, Jelle R. Dalenberg, Monicque M. Lorist, Natasha M. Maurits

Abstract

The current study investigated the extent and patterns of cognitive variability in younger and older adults. An important novelty of this study is the use of graph-based community structure detection analysis to map performance in a mixed population of 79 young and 76 older adults, without separating the age groups a-priori. We identified six subgroups, with distinct patterns of neuropsychological performance. The stability of the identified subgroups was confirmed by employing a cross-validation support vector machine based analysis. The majority of these subgroups comprised either young or older adults, confirming the expected role of aging in cognitive performance. In addition, we identified a subgroup of young and older adults who performed at a similar cognitive level of overall good cognitive performance with slightly decreased processing speed. This result showed that older age is not necessarily associated with general lower cognitive performance and that being young is not necessarily associated with superior cognitive performance. Moreover, cognitively better performing elderly had a significantly higher level of education attainment and higher crystallized intelligence than the other elderly, which suggests that older adults with higher cognitive reserve may be able to cope better with age-related neurobiological change.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Cuba 1 2%
United States 1 2%
Puerto Rico 1 2%
Unknown 48 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 29%
Professor 6 12%
Student > Bachelor 5 10%
Student > Master 5 10%
Researcher 3 6%
Other 5 10%
Unknown 12 24%
Readers by discipline Count As %
Psychology 16 31%
Computer Science 5 10%
Medicine and Dentistry 5 10%
Neuroscience 4 8%
Agricultural and Biological Sciences 1 2%
Other 4 8%
Unknown 16 31%