A watershed model of individual differences in fluid intelligence

NEUROPSYCHOLOGIA

卷:91

Article

Kievit, Rogier A.¹  Davis, Simon W.^2,3  Griffiths, John^2,4  Correia, Marta M.¹  Cam-Can^1,5  Henson, Richard N.¹ 

[1] MRC Cognit & Brain Sci Unit, 15 Chaucer Rd, Cambridge CB2 7EF, England

[2] Univ Cambridge, Dept Psychol, Downing St, Cambridge CB2 3EB, England

[3] Duke Univ, Ctr Cognit Neurosci, Durham, NC 27708 USA

[4] Baycrest, Rotman Res Inst, Toronto, ON M6A 2E1, Canada

[5] Univ Cambridge, Cambridge Ctr Ageing & Neurosci Cam CAN, Cambridge, England

关键词: Cognitive ageing;    White matter;    Processing speed;    Fluid intelligence;    Structural Equation Modelling;    Watershed model;   

DOI  :  10.1016/j.neuropsychologia.2016.08.008

来源: Elsevier

【 摘 要 】

Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes. (C) 2016 The Authors. Published by Elsevier Ltd.

【 授权许可】

Free