Literature DB >> 21859178

Between-individual variability and interpretation of associations between neurophysiological and behavioral measures in aging populations: comment on Salthouse (2011).

Patrick Rabbitt1.   

Abstract

Salthouse (2011) argued that (a) variance between individuals on cognitive test scores remains constant between 20 and 90 years of age and (b) widely recognized problems of deducing functional relationships from patterns of correlations between measurements become especially severe for neuropsychological indices, especially for gross indices of age-related brain changes (e.g., losses of brain volume or increases in white matter lesions). I argue that between-individual variability on cognitive tests does increase with age and provides useful information on causes of age-related cognitive decline. I suggest that problems of inference from correlations are just as difficult for behavioral as for neurophysiological indices and that inclusion, in analyses, of even gross measures of brain status such as loss of volume and white matter lesions can correct misinterpretations that occur when only behavioral data are examined. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

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Year:  2011        PMID: 21859178     DOI: 10.1037/a0024580

Source DB:  PubMed          Journal:  Psychol Bull        ISSN: 0033-2909            Impact factor:   17.737


  8 in total

1.  All data collection and analysis methods have limitations: reply to Rabbitt (2011) and Raz and Lindenberger (2011).

Authors:  Timothy A Salthouse
Journal:  Psychol Bull       Date:  2011-09       Impact factor: 17.737

2.  Life experience and demographic influences on cognitive function in older adults.

Authors:  Paul W H Brewster; Rebecca J Melrose; María J Marquine; Julene K Johnson; Anna Napoles; Anna MacKay-Brandt; Sarah Farias; Bruce Reed; Dan Mungas
Journal:  Neuropsychology       Date:  2014-06-16       Impact factor: 3.295

3.  Variation in longitudinal trajectories of regional brain volumes of healthy men and women (ages 10 to 85 years) measured with atlas-based parcellation of MRI.

Authors:  Adolf Pfefferbaum; Torsten Rohlfing; Margaret J Rosenbloom; Weiwei Chu; Ian M Colrain; Edith V Sullivan
Journal:  Neuroimage       Date:  2012-10-12       Impact factor: 6.556

Review 4.  What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus.

Authors:  Anders M Fjell; Linda McEvoy; Dominic Holland; Anders M Dale; Kristine B Walhovd
Journal:  Prog Neurobiol       Date:  2014-02-16       Impact factor: 11.685

5.  Cross-sectional versus longitudinal estimates of age-related changes in the adult brain: overlaps and discrepancies.

Authors:  Adolf Pfefferbaum; Edith V Sullivan
Journal:  Neurobiol Aging       Date:  2015-05-19       Impact factor: 4.673

6.  Correlational structure of 'frontal' tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age.

Authors:  Simon R Cox; Sarah E MacPherson; Karen J Ferguson; Jack Nissan; Natalie A Royle; Alasdair M J MacLullich; Joanna M Wardlaw; Ian J Deary
Journal:  Intelligence       Date:  2014-09

7.  Adult Lifespan Cognitive Variability in the Cross-Sectional Cam-CAN Cohort.

Authors:  Emma Green; Meredith A Shafto; Fiona E Matthews; Simon R White
Journal:  Int J Environ Res Public Health       Date:  2015-12-07       Impact factor: 3.390

8.  Revisiting measurement invariance in intelligence testing in aging research: Evidence for almost complete metric invariance across age groups.

Authors:  Briana N Sprague; Jinshil Hyun; Peter C M Molenaar
Journal:  J Pers Oriented Res       Date:  2018-03-11
  8 in total

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