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Review Article

Free Access

Functional Magnetic Resonance Imaging of Compensatory Neural Recruitment in Aging and Risk for Alzheimer’s Disease: Review and Recommendations

Han S.D.a–c · Bangen K.J.d · Bondi M.W.e, f

Author affiliations

aDepartment of Psychology, Loyola University Chicago, Chicago, Ill., bDepartment of Neurology and cNeuroscience Institute, Loyola University Medical Center, Maywood, Ill., dSDSU/UCSD Joint Doctoral Program, eDepartment of Psychiatry, University of California San Diego School of Medicine, and fPsychology Service, VA San Diego Healthcare System, San Diego, Calif., USA

Corresponding Author

S. Duke Han, PhD

Department of Psychology

6525 N. Sheridan Road

Chicago, IL 60626 (USA)

Tel. +1 773 508 3073, Fax +1 773 508 8713, E-Mail dhan2@luc.edu

Related Articles for ""

Dement Geriatr Cogn Disord 2009;27:1–10

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Abstract

There has been a recent proliferation of functional magnetic resonance imaging (fMRI) studies that interpret between-group or within-group differences in brain response patterns as evidence for compensatory neural recruitment. However, it is currently a challenge to determine whether these observed differences are truly attributable to compensatory neural recruitment or whether they are indicative of some other cognitive or physiological process. Therefore, the need for a standardized set of criteria for interpreting whether differences in brain response patterns are compensatory in nature is great. Focusing on studies of aging and potentially prodromal Alzheimer’s disease conditions (genetic risk, mild cognitive impairment), we critically review the functional neuroimaging literature purporting evidence for compensatory neural recruitment. Finally, we end with a comprehensive model set of criteria for ascertaining the degree to which a ‘compensatory’ interpretation may be supported. This proposed model addresses significant brain region, activation pattern, and behavioral performance considerations, and is therefore termed the Region-Activation-Performance model (RAP model).

© 2008 S. Karger AG, Basel


Article / Publication Details

First-Page Preview
Abstract of Review Article

Accepted: October 01, 2008
Published online: December 16, 2008
Issue release date: February 2009

Number of Print Pages: 10
Number of Figures: 1
Number of Tables: 0

ISSN: 1420-8008 (Print)
eISSN: 1421-9824 (Online)

For additional information: http://www.karger.com/DEM


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