Literature DB >> 15512935

Parsing the recognition memory components of the WMS-III face memory subtest: normative data and clinical findings in dementia groups.

James A Holdnack1, Dean C Delis.   

Abstract

The WMS-III face memory subtest was developed as a quick, reliable, measure of non-verbal recognition memory. While the face memory subtest has demonstrated clinical sensitivity, the test has been criticized for low correlation with other WMS-III visual memory subtests and for failing to differentiate performance between clinical groups. One possible reason for these findings may be due to the impact of response bias associated with recognition memory tests. Four studies were conducted to evaluate the utility of applying signal detection measures to the face memory subtests. The first two studies used the WMS-III standardization data set to determine age and education effects and to present normative and reliability data for hits, false positives, discriminability and response bias. The third study tested the hypothesis that using response components and signal detection measures would enhance the correlation between face memory and the other WMS-III visual memory subtests. The fourth study compared performance of patients with Alzheimer's disease, Huntington's disease, Korsakoff's syndrome and demographically matched controls on the new face memory scores. The new measures did not have higher correlation with other WMS-III visual memory measures than the standard scoring of the test. Analysis of the clinical samples indicated that the discriminability index best differentiated patients from controls. The response components, particularly delayed false positives, differentiated performance among the clinical groups. Normative and reliability data are presented.

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Mesh:

Year:  2004        PMID: 15512935     DOI: 10.1080/13803390490496687

Source DB:  PubMed          Journal:  J Clin Exp Neuropsychol        ISSN: 1380-3395            Impact factor:   2.475


  7 in total

1.  Latent structure and factorial invariance of a neuropsychological test battery for the study of preclinical Alzheimer's disease.

Authors:  N Maritza Dowling; Bruce Hermann; Asenath La Rue; Mark A Sager
Journal:  Neuropsychology       Date:  2010-11       Impact factor: 3.295

2.  Item response theory analyses of the Cambridge Face Memory Test (CFMT).

Authors:  Sun-Joo Cho; Jeremy Wilmer; Grit Herzmann; Rankin Williams McGugin; Daniel Fiset; Ana E Van Gulick; Kaitlin F Ryan; Isabel Gauthier
Journal:  Psychol Assess       Date:  2015-02-02

3.  Memory for unfamiliar faces differentiates mild cognitive impairment from normal aging.

Authors:  Vinh Q Nguyen; Daniel L Gillen; Malcolm B Dick
Journal:  J Clin Exp Neuropsychol       Date:  2014-05-21       Impact factor: 2.475

4.  Wechsler Memory Scale-III Faces test performance in patients with mild cognitive impairment and mild Alzheimer's disease.

Authors:  Adriana M Seelye; Diane B Howieson; Katherine V Wild; Mindy Milar Moore; Jeffrey A Kaye
Journal:  J Clin Exp Neuropsychol       Date:  2008-11-26       Impact factor: 2.475

Review 5.  Face recognition: a model specific ability.

Authors:  Jeremy B Wilmer; Laura T Germine; Ken Nakayama
Journal:  Front Hum Neurosci       Date:  2014-10-10       Impact factor: 3.169

6.  Capturing specific abilities as a window into human individuality: the example of face recognition.

Authors:  Jeremy B Wilmer; Laura Germine; Christopher F Chabris; Garga Chatterjee; Margaret Gerbasi; Ken Nakayama
Journal:  Cogn Neuropsychol       Date:  2012       Impact factor: 2.468

Review 7.  What can individual differences reveal about face processing?

Authors:  Galit Yovel; Jeremy B Wilmer; Brad Duchaine
Journal:  Front Hum Neurosci       Date:  2014-08-19       Impact factor: 3.169

  7 in total

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