9 results match your criteria Applied Intelligence[Journal]

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Predictors of ageing-related decline across multiple cognitive functions.

Intelligence 2016 Nov-Dec;59:115-126

Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom; Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom.

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years ( = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. Read More

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http://dx.doi.org/10.1016/j.intell.2016.08.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5127886PMC
December 2016
17 Reads

Do cognitive interventions alter the rate of age-related cognitive change?

Intelligence 2015 Nov-Dec;53:86-91

Department of Psychology, University of Virginia, Charlottesville, VA 22904-4400.

There has recently been a great deal of interest in cognitive interventions, particularly when applied in older adults with the goal of slowing or reversing age-related cognitive decline. Although seldom directly investigated, one of the fundamental questions concerning interventions is whether the intervention alters the rate of cognitive change, or affects the level of certain cognitive measures with no effect on the trajectory of change. This question was investigated with a very simple intervention consisting of the performance of three versions (treatment) or one version (control) of the relevant cognitive tests at an initial occasion. Read More

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http://dx.doi.org/10.1016/j.intell.2015.09.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4604606PMC
October 2015

Molecular genetic contributions to socioeconomic status and intelligence.

Intelligence 2014 May;44(100):26-32

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK ; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK.

Education, socioeconomic status, and intelligence are commonly used as predictors of health outcomes, social environment, and mortality. Education and socioeconomic status are typically viewed as environmental variables although both correlate with intelligence, which has a substantial genetic basis. Using data from 6815 unrelated subjects from the Generation Scotland study, we examined the genetic contributions to these variables and their genetic correlations. Read More

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http://biorxiv.org/content/biorxiv/early/2016/03/09/043000.f
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http://linkinghub.elsevier.com/retrieve/pii/S016028961400017
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http://dx.doi.org/10.1016/j.intell.2014.02.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051988PMC
May 2014
18 Reads

Intelligence indexes generalist genes for cognitive abilities.

Intelligence 2013 Sep;41(5):560-565

King's College London, Institute of Psychiatry, MRC Social, Genetic and Developmental Psychiatry Centre, London, England SE5 8AF, United Kingdom.

Twin research has supported the concept of intelligence (general cognitive ability, g) by showing that genetic correlations between diverse tests of verbal and nonverbal cognitive abilities are greater than 0.50. That is, most of the genes that affect cognitive abilities are highly pleiotropic in the sense that genes that affect one cognitive ability affect all cognitive abilities. Read More

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http://dx.doi.org/10.1016/j.intell.2013.07.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3928847PMC
September 2013
3 Reads

Low-Frequency Copy-Number Variants and General Cognitive Ability: No Evidence of Association.

Intelligence 2014 Jan;42:98-106

University of Minnesota Medical School, Department of Laboratory Medicine & Pathology, 420 Delaware St. SE, Minneapolis, MN 55455.

Although twin, family, and adoption studies have shown that general cognitive ability (GCA) is substantially heritable, GWAS has not uncovered a genetic polymorphism replicably associated with this phenotype. However, most polymorphisms used in GWAS are common SNPs. The present study explores use of a different class of genetic variant, the copy-number variant (CNV), to predict GCA in a sample of 6,199 participants, combined from two longitudinal family studies. Read More

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http://dx.doi.org/10.1016/j.intell.2013.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909536PMC
January 2014
4 Reads

Genetic influence on family socioeconomic status and children's intelligence.

Intelligence 2014 Jan;42(100):83-88

King's College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, De Crespigny Park, London, SE5 8AF, United Kingdom.

Environmental measures used widely in the behavioral sciences show nearly as much genetic influence as behavioral measures, a critical finding for interpreting associations between environmental factors and children's development. This research depends on the twin method that compares monozygotic and dizygotic twins, but key aspects of children's environment such as socioeconomic status (SES) cannot be investigated in twin studies because they are the same for children growing up together in a family. Here, using a new technique applied to DNA from 3000 unrelated children, we show significant genetic influence on family SES, and on its association with children's IQ at ages 7 and 12. Read More

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http://dx.doi.org/10.1016/j.intell.2013.11.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907681PMC
January 2014
5 Reads

Is age kinder to the initially more able?: Yes, and no.

Intelligence 2012 Jan;40(1):49-59

Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.

Although a number of analyses have addressed whether initial cognitive ability level is associated with age-related cognitive decline, results have been inconsistent. Latent growth curve modeling was applied to two aging cohorts, extending previous analyses with a further wave of data collection, or as a more appropriate analytical methodology than used previously. In the Lothian Birth Cohort 1921, cognitive ability at age 11 was not associated with cognitive change from age 79 to 87, either in general cognitive ability, or in tests of reasoning, memory and executive function. Read More

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http://dx.doi.org/10.1016/j.intell.2011.10.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657153PMC
January 2012
3 Reads

A Comparison of Laboratory and Clinical Working Memory Tests and Their Prediction of Fluid Intelligence.

Intelligence 2009 May;37(3):283

Louisiana State University.

The working memory (WM) construct is conceptualized similarly across domains of psychology, yet the methods used to measure WM function vary widely. The present study examined the relationship between WM measures used in the laboratory and those used in applied settings. A large sample of undergraduates completed three laboratory-based WM measures (operation span, listening span, and n-back), as well as the WM subtests from the Wechsler Adult Intelligence Scale-III and the Wechsler Memory Scale-III. Read More

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http://linkinghub.elsevier.com/retrieve/pii/S016028960800162
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http://dx.doi.org/10.1016/j.intell.2008.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2818304PMC
May 2009
5 Reads

Structure and Continuity of Intellectual Development in Early Childhood.

Intelligence 2009 ;37(1):106-113

The University of Kansas.

We evaluated over 200 participants semiannually from 12 to 48 months of age on measures of intellectual (Bayley Scales, Stanford-Binet Scale) and verbal (MacArthur-Bates Inventory, Peabody Picture Vocabulary Test) status. Structural equation modeling and hierarchical linear (growth curve) analyses were applied to address the nature of development and individual differences during this time. Structural analyses showed a strong and robust simplex model from infancy to the preschool period, with no evidence of qualitative reorganizations or discontinuities. Read More

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http://dx.doi.org/10.1016/j.intell.2008.09.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2631272PMC
January 2009
3 Reads
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