ArticleNeuropsychologia2016
A watershed model of individual differences in fluid intelligence.
Article in Neuropsychologia, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 60 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
60 citing papers in PubMed.
- Fifteen years on: a review of the Cam-CAN study of the cognitive neuroscience of ageing.GeroScience · 2026Review
- Pulse Pressure Impairs Cognition via White Matter Disruption.Hypertension (Dallas, Tex. : 1979) · 2025Article
- Complementary MR measures of white matter and their relation to cardiovascular health and cognition.Scientific reports · 2025Article
- Distinct cognitive trajectories in the early course of psychosis are associated with clinical and functional outcomes longitudinally.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
- Non-decision time: The Higgs Boson of decision.Psychological review · 2025Article
- WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis.Scientific data · 2025Article
- Distributed associations among white matter hyperintensities and structural brain networks with fluid cognition in healthy aging.Cognitive, affective & behavioral neuroscience · 2024Article
- Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance: Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach.Human brain mapping · 2023Article
- Distinct components of cardiovascular health are linked with age-related differences in cognitive abilities.Scientific reports · 2023Article
- A Psychometric Network Analysis of CHC Intelligence Measures: Implications for Research, Theory, and Interpretation of Broad CHC Scores "BeyondJournal of Intelligence · 2023Article
- Neural Contributions to Reduced Fluid Intelligence across the Adult Lifespan.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the adult lifespan.Neurobiology of aging · 2023Article
- Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects.Human brain mapping · 2022Article
- Individual differences in white matter microstructure of the face processing brain network are more differentiated from global fibers with increasing ability.Scientific reports · 2022Article
- Wisdom and fluid intelligence are dissociable in healthy older adults.International psychogeriatrics · 2022Article
- Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan.Frontiers in neuroscience · 2022Article
- Genetic variation, brain, and intelligence differences.Molecular psychiatry · 2022Review
- Cognitive Dimensions of Learning in Children With Problems in Attention, Learning, and Memory.Journal of educational psychology · 2021Article
- Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners.Journal of Intelligence · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.