BACKGROUND AND PURPOSE: Fractional anisotropy (FA) is a useful measure of connectivity in the brain that can be derived from the diffusion tensor imaging (DTI) dataset. This study investigated the relationship between FA and selected measures of cognition across a broad age group to explore a possible structural basis for cognitive changes with age. METHODS: FA images were generated from DTI data acquired at 1.5T in 87 healthy subjects (age range, 20-73 years). Relationships between a range of cognitive measures and FA were explored using regional and voxel-based analysis. RESULTS: Age and regional average FA were significantly associated in the frontal, parietal, and temporal lobes but not in the occipital lobe. This negative relationship was especially prominent in the prefrontal regions of the frontal lobe, where FA declined at a rate of approximately 3% per decade. Decreased FA in the frontal, temporal, and parietal lobes was associated with poorer cognitive performance in executive maze and in an attention-switching task. A voxel-level analysis of these data revealed that the executive function-FA association was particularly strong and regionally delineated over 2 continuous, bilateral areas extending from the prefrontal cortex to the parietal lobe, with projections to the anterior portions of the thalamus. CONCLUSIONS: We demonstrate a relationship between FA and a measure of executive function-a core cognitive component that is a key feature of cognitive aging. We propose that that FA may provide an early means for the detection of age-related cognitive change and suggest a need for prospective data to explore this association.
BACKGROUND AND PURPOSE: Fractional anisotropy (FA) is a useful measure of connectivity in the brain that can be derived from the diffusion tensor imaging (DTI) dataset. This study investigated the relationship between FA and selected measures of cognition across a broad age group to explore a possible structural basis for cognitive changes with age. METHODS: FA images were generated from DTI data acquired at 1.5T in 87 healthy subjects (age range, 20-73 years). Relationships between a range of cognitive measures and FA were explored using regional and voxel-based analysis. RESULTS: Age and regional average FA were significantly associated in the frontal, parietal, and temporal lobes but not in the occipital lobe. This negative relationship was especially prominent in the prefrontal regions of the frontal lobe, where FA declined at a rate of approximately 3% per decade. Decreased FA in the frontal, temporal, and parietal lobes was associated with poorer cognitive performance in executive maze and in an attention-switching task. A voxel-level analysis of these data revealed that the executive function-FA association was particularly strong and regionally delineated over 2 continuous, bilateral areas extending from the prefrontal cortex to the parietal lobe, with projections to the anterior portions of the thalamus. CONCLUSIONS: We demonstrate a relationship between FA and a measure of executive function-a core cognitive component that is a key feature of cognitive aging. We propose that that FA may provide an early means for the detection of age-related cognitive change and suggest a need for prospective data to explore this association.
Authors: Elizabeth R Sowell; Bradley S Peterson; Paul M Thompson; Suzanne E Welcome; Amy L Henkenius; Arthur W Toga Journal: Nat Neurosci Date: 2003-03 Impact factor: 24.884
Authors: David J Madden; Wythe L Whiting; Scott A Huettel; Leonard E White; James R MacFall; James M Provenzale Journal: Neuroimage Date: 2004-03 Impact factor: 6.556
Authors: Stuart M Grieve; C Richard Clark; Leanne M Williams; Anthony J Peduto; Evian Gordon Journal: Hum Brain Mapp Date: 2005-08 Impact factor: 5.038
Authors: S M Resnick; A F Goldszal; C Davatzikos; S Golski; M A Kraut; E J Metter; R N Bryan; A B Zonderman Journal: Cereb Cortex Date: 2000-05 Impact factor: 5.357
Authors: M M Breteler; N M van Amerongen; J C van Swieten; J J Claus; D E Grobbee; J van Gijn; A Hofman; F van Harskamp Journal: Stroke Date: 1994-06 Impact factor: 7.914
Authors: Ysbrand D Van der Werf; Philip Scheltens; Jaap Lindeboom; Menno P Witter; Harry B M Uylings; Jelle Jolles Journal: Neuropsychologia Date: 2003 Impact factor: 3.139
Authors: Po H Lu; Grace J Lee; Erika P Raven; Kathleen Tingus; Theresa Khoo; Paul M Thompson; George Bartzokis Journal: J Clin Exp Neuropsychol Date: 2011-08-26 Impact factor: 2.475
Authors: Barbara B Bendlin; Michele E Fitzgerald; Michele L Ries; Guofan Xu; Erik K Kastman; Brent W Thiel; Howard A Rowley; Mariana Lazar; Andrew L Alexander; Sterling C Johnson Journal: Dev Neuropsychol Date: 2010 Impact factor: 2.253
Authors: David J Madden; Julia Spaniol; Matthew C Costello; Barbara Bucur; Leonard E White; Roberto Cabeza; Simon W Davis; Nancy A Dennis; James M Provenzale; Scott A Huettel Journal: J Cogn Neurosci Date: 2009-02 Impact factor: 3.225
Authors: A R Mayer; J Ling; M V Mannell; C Gasparovic; J P Phillips; D Doezema; R Reichard; R A Yeo Journal: Neurology Date: 2010-01-20 Impact factor: 9.910