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Neuropsychologia. 2016 Oct;91:186-198. doi: 10.1016/j.neuropsychologia.2016.08.008. Epub 2016 Aug 9.

A watershed model of individual differences in fluid intelligence.

Author information

1
MRC Cognition and Brain Sciences Unit, 15 Chaucer Rd, Cambridge CB2 7EF, United Kingdom. Electronic address: Rogier.Kievit@mrc-cbu.cam.ac.uk.
2
Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, United States.
3
Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom; Rotman Research Institute, Baycrest, Toronto, Ontario, Canada M6A 2E1.
4
MRC Cognition and Brain Sciences Unit, 15 Chaucer Rd, Cambridge CB2 7EF, United Kingdom.
5
Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.

Abstract

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.

KEYWORDS:

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

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