Genetic variation, brain, and intelligence differences

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Executive functions

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"General Intelligence," Objectively Determined and Measured

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Human Cognitive Abilities: A Survey of Factor-Analytic Studies

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The Bell Curve: Intelligence and Class Structure in American Life.

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The mismeasure of man

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Human cognitive abilities a survey of factor-analytic studies

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Intelligence: Knowns and unknowns.

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The g factor: the science of mental ability

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White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI

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Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

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Meta-analysis of the heritability of human traits based on fifty years of twin studies

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Hereditary genius: An inquiry into its laws and consequences.

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Heritability in the genomics era — concepts and misconceptions

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Massive IQ gains in 14 nations: What IQ tests really measure.

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Unity and diversity of executive functions: Individual differences as a window on cognitive structure

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Intelligence and educational achievement

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The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence

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Hereditary Genius: An Inquiry into its Laws and Consequences

Galton, F. (1914) · Nature · doi:10.1038/093453b0 · Cited by 1,552 · see citing works

Power and predictive accuracy of polygenic risk scores

Dudbridge, F. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003348 · Cited by 1,509 · see citing works

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

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General Mental Ability in the World of Work: Occupational Attainment and Job Performance.

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Selective review of cognitive aging

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Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography

Gottfredson, L. S. (1997) · Intelligence · doi:10.1016/s0160-2896(97)90011-8 · Cited by 1,137 · see citing works

Multi-trait analysis of genome-wide association summary statistics using MTAG

23andMe Research Team, Turley, P., Social Science Genetic Association Consortium, Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0009-4 · Cited by 1,112 · see citing works

The neuroscience of human intelligence differences

Deary, I. J., Penke, L., & Johnson, W. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2793 · Cited by 1,038 · see citing works

Intelligence: New findings and theoretical developments

Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012) · American Psychologist · doi:10.1037/a0026699 · Cited by 968 · see citing works

Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits

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Intelligence and socioeconomic success: A meta-analytic review of longitudinal research

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The nature of nurture: Effects of parental genotypes

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Intelligence and the Frontal Lobe: The Organization of Goal-Directed Behavior

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Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

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PRIMARY MENTAL ABILITIES

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What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

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What is the test–retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis

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Genetics and intelligence differences: five special findings

Plomin, R., & Deary, I. J. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.105 · Cited by 702 · see citing works

How Much Does Education Improve Intelligence? A Meta-Analysis

Ritchie, S. J., & Tucker-Drob, E. M. (2018) · Psychological Science · doi:10.1177/0956797618774253 · Cited by 680 · see citing works

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Davies, G., Lam, M., Harris, S. E., Trampush, J. W., Michelle Luciano, A., Hill, W. D., Hagenaars, S. P., Ritchie, S. J., Marioni, R. E., Fawns‐Ritchie, C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04362-x · Cited by 668 · see citing works

The heritability of general cognitive ability increases linearly from childhood to young adulthood

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Genome-wide association studies establish that human intelligence is highly heritable and polygenic

Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., Ke, X., Le Hellard, S., Christoforou, A., Luciano, M., et al. (2011) · Molecular Psychiatry · doi:10.1038/mp.2011.85 · Cited by 608 · see citing works

The new genetics of intelligence

Plomin, R. J., & von Stumm, S. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2017.104 · Cited by 495 · see citing works

Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

Sniekers, S., Stringer, S., Watanabe, K., Jansen, P. R., Coleman, J. R. I., Krapohl, E., Taskesen, E., Hammerschlag, A. R., Okbay, A., Zabaneh, D., et al. (2017) · Nature Genetics · doi:10.1038/ng.3869 · Cited by 490 · see citing works

Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation

Seidlitz, J., Váša, F., Shinn, M., Romero-García, R., Whitaker, K. J., Vértes, P. E., Wagstyl, K., Reardon, P. K., CLASEN, L. S., Liu, S., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.11.039 · Cited by 488 · see citing works

Ageing and brain white matter structure in 3,513 UK Biobank participants

Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., Wardlaw, J. M., Gale, C. R., Bastin, M. E., & Deary, I. J. (2016) · Nature Communications · doi:10.1038/ncomms13629 · Cited by 487 · see citing works

Hippocampal–anterior thalamic pathways for memory: uncovering a network of direct and indirect actions

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Intelligence

Deary, I. J. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100353 · Cited by 467 · see citing works

Process Overlap Theory: A Unified Account of the General Factor of Intelligence

Kovacs, K., & Conway, A. R. A. (2016) · Psychological Inquiry · doi:10.1080/1047840x.2016.1153946 · Cited by 432 · see citing works

Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses

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Changes in Thickness and Surface Area of the Human Cortex and Their Relationship with Intelligence

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Genetic correlations of polygenic disease traits: from theory to practice

van Rheenen, W., Peyrot, W. J., Schork, A. J., Lee, S., & Wray, N. R. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0137-z · Cited by 385 · see citing works

An integrative architecture for general intelligence and executive function revealed by lesion mapping.

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Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

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Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

Davies, G., Marioni, R. E., Liewald, D. C., Hill, W. D., Hagenaars, S. P., Harris, S. E., Ritchie, S. J., Luciano, M., Fawns-Ritchie, C., Lyall, D., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.45 · Cited by 373 · see citing works

Intelligence as the Tests Test It.

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Assortative mating, or who marries whom?

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Looking down on human intelligence.

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Just one g: consistent results from three test batteries

Johnson, W., Bouchard, T. J., Krueger, R. F., McGue, M., & Gottesman, I. I. (2004) · Intelligence · doi:10.1016/s0160-2896(03)00062-x · Cited by 353 · see citing works

Erratum: Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

Sniekers, S., Stringer, S., Watanabe, K., Jansen, P. R., Coleman, J. R. I., Krapohl, E. M. L., Taskesen, E., Hammerschlag, A. R., Okbay, A., Zabaneh, D., et al. (2017) · Nature Genetics · doi:10.1038/ng1017-1558c · Cited by 344 · see citing works

Working Memory and Executive Attention: A Revisit

Engle, R. W. (2018) · Perspectives on Psychological Science · doi:10.1177/1745691617720478 · Cited by 339 · see citing works

Associations between vascular risk factors and brain MRI indices in UK Biobank

Cox, S. R., Lyall, D. M., Ritchie, S. J., Bastin, M. E., Harris, M. A., Buchanan, C. R., Fawns‐Ritchie, C., Barbu, M. C., de Nooij, L., Reus, L. M., et al. (2019) · European Heart Journal · doi:10.1093/eurheartj/ehz100 · Cited by 329 · see citing works

A distributed brain network predicts general intelligence from resting-state human neuroimaging data

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Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean?

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A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence

Hill, W. D., Marioni, R. E., Maghzian, O., Ritchie, S. J., Hagenaars, S. P., McIntosh, A. M., Gale, C. R., Davies, G., & Deary, I. J. (2019) · Molecular Psychiatry · doi:10.1038/s41380-017-0001-5 · Cited by 311 · see citing works

Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligence

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Brain white matter tract integrity as a neural foundation for general intelligence

Penke, L., Maniega, S. M., Bastin, M. E., Hernández, M. C. V., Murray, C. L., Royle, N. A., Starr, J. M., Wardlaw, J. M., & Deary, I. J. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.66 · Cited by 303 · see citing works

Most Reported Genetic Associations with General Intelligence Are Probably False Positives

Chabris, C., Hebert, B. M., Benjamin, D. J., Beauchamp, J., Cesarini, D., van der Loos, M., Johannesson, M., Magnusson, P., Lichtenstein, P., Atwood, C., et al. (2012) · Psychology Science · doi:10.1177/0956797611435528 · Cited by 301 · see citing works

Looking Down on Human Intelligence

Deary, I. (2000) · doi:10.1093/acprof:oso/9780198524175.001.0001 · Cited by 296 · see citing works

Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits

Zhao, B., Luo, T., Li, T., Li, Y., Zhang, J., Shan, Y., Wang, X., Yang, L., Zhou, F., Zhu, Z., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0516-6 · Cited by 295 · see citing works

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Demange, P., Malanchini, M., Mallard, T. T., Biroli, P., Cox, S. R., Grotzinger, A. D., Tucker–Drob, E. M., Abdellaoui, A., Arseneault, L., van Bergen, E., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00754-2 · Cited by 288 · see citing works

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

Trampush, J. W., Yang, M. L. Z., Yu, J., Knowles, E., Davies, G., Liewald, D. C., Starr, J. M., Djurovic, S., Melle, I., Sundet, K., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.244 · Cited by 271 · see citing works

Distributed neural system for general intelligence revealed by lesion mapping

Gläscher, J. P., Rudrauf, D., Colom, R., Paul, L. K., Tranel, D., Damasio, H., & Adolphs, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910397107 · Cited by 270 · see citing works

Intelligence: A Very Short Introduction

Deary, I. J. (2020) · doi:10.1093/actrade/9780198796206.001.0001 · Cited by 258 · see citing works

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method

Rietveld, C. A., Esko, T., Davies, G., Pers, T. H., Turley, P., Benyamin, B., Chabris, C. F., Emilsson, V., Johnson, A. D., Lee, J. J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404623111 · Cited by 258 · see citing works

Normative brain size variation and brain shape diversity in humans

Reardon, P. K., Seidlitz, J., Vandekar, S., Liu, S., Patel, R., Park, M. T. M., Alexander-Bloch, A., Clasen, L. S., Blumenthal, J. D., Lalonde, F. M., et al. (2018) · Science · doi:10.1126/science.aar2578 · Cited by 255 · see citing works

Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits

Haplotype Reference Consortium, Evans, L. M., Tahmasbi, R., Vrieze, S. I., Abecasis, G. R., Das, S., Gazal, S., Bjelland, D. W., de Candia, T. R., Goddard, M. E., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0108-x · Cited by 239 · see citing works

Dominance Genetic Variation Contributes Little to the Missing Heritability for Human Complex Traits

Zhu, Z., Bakshi, A., Vinkhuyzen, A. A. E., Hemani, G., Lee, S. H., Nolte, I. M., van Vliet-Ostaptchouk, J. V., Snieder, H., Esko, T., Milani, L., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.01.001 · Cited by 224 · see citing works

Intergenerational social mobility and mid-life status attainment: Influences of childhood intelligence, childhood social factors, and education

Deary, I. J., Taylor, M. D., Hart, C., Wilson, V., Smith, G. D., Blane, D., & Starr, J. M. (2005) · Intelligence · doi:10.1016/j.intell.2005.06.003 · Cited by 215 · see citing works

The Neuroscience of Intelligence

Haier, R. J. (2016) · Cambridge University Press eBooks · doi:10.1017/9781316105771 · Cited by 207 · see citing works

Sex Differences in Variability in General Intelligence: A New Look at the Old Question

Johnson, W., Carothers, A. D., & Deary, I. J. (2008) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2008.00096.x · Cited by 202 · see citing works

Coupled cognitive changes in adulthood: A meta-analysis.

Tucker–Drob, E. M., Brandmaier, A. M., & Lindenberger, U. (2019) · Psychological Bulletin · doi:10.1037/bul0000179 · Cited by 197 · see citing works

Childhood intelligence in relation to major causes of death in 68 year follow-up: prospective population study

Calvin, C. M., Batty, G. D., Der, G., Brett, C. E., Taylor, A., Pattie, A., Čukić, I., & Deary, I. J. (2017) · BMJ · doi:10.1136/bmj.j2708 · Cited by 189 · see citing works

Influence of Gene Interaction on Complex Trait Variation with Multilocus Models

Mäki‐Tanila, A., & Hill, W. G. (2014) · Genetics · doi:10.1534/genetics.114.165282 · Cited by 185 · see citing works

Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds

Karama, S., Ad-Dab’bagh, Y., Haier, R. J., Deary, I. J., Lyttelton, O., Lepage, C., & Evans, A. C. (2008) · Intelligence · doi:10.1016/j.intell.2008.09.006 · Cited by 181 · see citing works

A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing

Davies, G., Harris, S. E., Reynolds, C. A., Payton, A., Knight, H. M., Liewald, D. C. M., Lopez, L. M., Michelle Luciano, A., Gow, A. J., Corley, J., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.159 · Cited by 180 · see citing works

Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income

Hill, W. D., Davies, N. M., Ritchie, S. J., Skene, N., Bryois, J., Bell, S., Angelantonio, E. D., Roberts, D. J., Shen, X., Davies, G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13585-5 · Cited by 178 · see citing works

Cognitive Aging and Dementia: A Life-Span Perspective

Tucker–Drob, E. M. (2019) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-121318-085204 · Cited by 178 · see citing works

Distinct aspects of frontal lobe structure mediate age-related differences in fluid intelligence and multitasking

Kievit, R., Davis, S. W., Mitchell, D. J., Taylor, J. R., Duncan, J., TYLER, L. K., Brayne, C., Bullmore, E. T., Calder, A. C., Cusack, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms6658 · Cited by 176 · see citing works

Molecular Genetic Contributions to Social Deprivation and Household Income in UK Biobank

Hill, W. D., Hagenaars, S. P., Marioni, R. E., Harris, S. E., Liewald, D. C. M., Davies, G., Okbay, A., McIntosh, A. M., Galé, C. R., & Deary, I. J. (2016) · Current Biology · doi:10.1016/j.cub.2016.09.035 · Cited by 176 · see citing works

Relatedness disequilibrium regression estimates heritability without environmental bias

Young, A. I., Frigge, M. L., Gudbjartsson, D. F., Thorleifsson, G., Bjornsdottir, G., Sulem, P., Masson, G., Thorsteinsdottir, U., Stefansson, K., & Kong, A. (2018) · Nature Genetics · doi:10.1038/s41588-018-0178-9 · Cited by 173 · see citing works

Are processing speed tasks biomarkers of cognitive aging?

Deary, I. J., Johnson, W., & Starr, J. M. (2010) · Psychology and Aging · doi:10.1037/a0017750 · Cited by 168 · see citing works

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence

Genç, E., Fraenz, C., Schlüter, C., Friedrich, P., Hossiep, R., Voelkle, M. C., Ling, J. M., Güntürkün, O., & Jung, R. E. (2018) · Nature Communications · doi:10.1038/s41467-018-04268-8 · Cited by 167 · see citing works

Structural brain imaging correlates of general intelligence in UK Biobank

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Brain and cognitive ageing: The present, and some predictions (…about the future)

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The biological basis of intelligence: Benchmark findings

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Brain aging differs with cognitive ability regardless of education

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Schooling substantially improves intelligence, but neither lessens nor widens the impacts of socioeconomics and genetics

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Genetically proxied lean mass and risk of Alzheimer’s disease: mendelian randomisation study

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Genetic evidence that the causal association of educational attainment with reduced risk of Alzheimer's disease is driven by intelligence

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Effect of strategic memory advanced reasoning training (SMART) therapy for enhancing final-year high school students career choices

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Mutation or not, what directly establishes a neoplastic state, namely cellular immortality and autonomy, still remains unknown and should be prioritized in our research

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Innate ability, health, motivation, and social capital as predictors of students’ cognitive, affective and psychomotor learning outcomes in secondary schools

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A General Cognitive Ability Factor for the UK Biobank

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Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

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A multi-faceted role of dual-state dopamine signaling in working memory, attentional control, and intelligence

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Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936

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Robust associations between white matter microstructure and general intelligence

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Multivariate prediction of cognitive performance from the sleep electroencephalogram

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Combined repetitive transcranial magnetic stimulation and gut microbiota modulation through the gut–brain axis for prevention and treatment of autism spectrum disorder

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Anticholinergic burden in middle and older age is associated with lower cognitive function, but not with brain atrophy

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Structural architecture and brain network efficiency link polygenic scores to intelligence

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The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis

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Ian Deary and Robert Sternberg answer five self-inflicted questions about human intelligence

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Evolving networks of human intelligence

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Brain volumes, thicknesses, and surface areas as mediators of genetic factors and childhood adversity on intelligence

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Cognitive predictors of mental health trajectories are mediated by inferior frontal and occipital development during adolescence

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The Contribution of Mental Capacity to Personality Formulation. An Overview

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Interrelationships between polygenic risk scores, cognition, symptoms, and functioning in first-episode psychosis: A network analysis approach.

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Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes

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Assessment of primary schoolchildren’s fluid intelligence using Raven's Colored progressive matrices: A pilot cross-sectional study in Lebanon

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A new beginning of intelligence research. Designing the playground

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Polygenic indices for cognition in healthy aging; the role of brain measures

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Education and Social Science

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Neurocognitive Aging

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Rethinking personhood and agency: how AI challenges human-centered concepts

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The impact of early adversity on the cerebral cortex - a Mendelian randomization study

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A new look at the relations between attachment and intelligence

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Cognitive variability is ubiquitous and distinct from mean performance across eleven tasks with over 7 million trialsPreprint

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Intersectional Inequalities in the Transition to Grandparenthood and Cognitive Functioning: A Longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy

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Toward a Molecular Biology of Human Intelligence: Psychometrics Meets Gene Expressions and Brain Metabolism

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Shared genetic architecture between ADHD and intelligence varies across ADHD subtypes

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Cognition and beyond: Intersections of personality traits and language

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Brain volumes and cortical thickness and associations with cognition in children born extremely preterm

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Biomarkers of preschool children with autism spectrum disorder: quantitative analysis of whole-brain tissue component volumes, intelligence scores, ADOS-CSS, and ages of first-word production and walking onset

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Aging Brain from a Lifespan Perspective

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Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study

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Openness/Intellect: A Unique Trait Requires Unique Considerations

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Integration of multiomic and multi-phenotypic data identifies biological pathways associated with physical fitness

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Interactive roles of preterm-birth and socioeconomic status in cortical thickness of language-related brain structures: Findings from the Adolescent Brain Cognitive Development (ABCD) study

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Why Some Mice Are Smarter than Others: The Impact of Bone Morphogenetic Protein Signaling on Cognition

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A partially functional linear regression framework for integrating genetic, imaging, and clinical data

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Intrauterine chromium exposure and cognitive developmental delay: The modifying effect of genetic predisposition

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The Role of Bioengineering in Healthcare

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SynaptopathyDB: a resource for studying the genetic and synaptic basis of nervous system disordersPreprint

Sorokina, O., Dominic, D., Bayés, À., Armstrong, J. D., & Grant, S. G. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.27.661932 · Cited by 4 · see citing works

Brain maps of general cognitive functioning: neuroimaging and neurobiological signatures

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Race, intelligence and genetics: colonialism in the era of neurotechnology

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Intelligence in Multiple Dimensions: Evolutionary Framework for the Study of Human Cognition

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The impact of early adversity and education on genetic and brain morphological predictors of cognitive ability

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Two Cheers for the Cognitive Irregulars: Intelligence’s Contributions to Ageing Well and Staying Alive

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Transcriptome-wide and Stratified Genomic Structural Equation Modeling Identify Neurobiological Pathways Underlying General and Specific Cognitive FunctionsPreprint

Grotzinger, A. D., de la Fuente, J., Davies, G., Nivard, M. G., & Tucker–Drob, E. M. (2021) · medRxiv · doi:10.1101/2021.04.30.21256409 · Cited by 3 · see citing works

Brain maps of general cognitive function and spatial correlations with neurobiological cortical profilesPreprint

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Functional Tests Guide Complex “Fidelity“ Tradeoffs in Whole-Brain Emulation

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“Those Evenings of the Brain – When Not a Moon Disclose a Sign”

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Common and rare genetic variant associations with cognitive performance across development in British birth cohorts

Malawsky, D. S., Koko, M., Danecek, P., Huang, W., Wootton, O., Huang, Q. Q., Wade, E. E., Lindsay, S., Arden, R., Hurles, M. E., et al. (2026) · Nature Human Behaviour · doi:10.1038/s41562-026-02491-8 · Cited by 2 · see citing works

Intelligence, empathy, and memory: Exploring moral enhancement through gene editing, training, and computer–brain interfaces

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Islamic Resilience of Marginal School Communities Management in An Effort to Educational Transformation

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Age-related changes of node degree in the multiple-demand network predict fluid intelligence

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The impact of metabolic syndrome on the cerebral cortex: a Mendelian randomization study

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How Mild Is the Mild Long COVID? A Comprehensive Neuropsychological Assessment of Patients with Cognitive Complaints

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Neurobiological Definition of Intelligence: A Neuroscience Review

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What is intelligence, really? The futile search for a Holy Grail

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SynaptopathyDB integrates synaptic proteomes, genetic and phenotypic data to advance research on nervous system disorders

Sorokina, O., Dominic, D., Bayés, À., Armstrong, J. D., & Grant, S. G. N. (2025) · Scientific Reports · doi:10.1038/s41598-025-26969-z · Cited by 2 · see citing works

Causal effects of cingulate morphology on executive functions in healthy young adults

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Intelligence predicts better cognitive performance after normal sleep but larger vulnerability to sleep deprivation

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Effectiveness of Early Childhood Care and Education on Intelligence of Children 2 to 24 Months, and their Mother’s Affective Capital and Parenting Stress

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The differential effects of common and rare genetic variants on cognitive performance across developmentPreprint

Malawsky, D. S., Koko, M., Danecek, P., Huang, W., Wootton, O., Huang, Q. Q., Wade, E. E., Lindsay, S., Arden, R., Hurles, M. E., et al. (2024) · medRxiv · doi:10.1101/2024.09.04.24313061 · Cited by 2 · see citing works

Multiple methods for assessing learning and memory in Drosophila melanogaster demonstrates the highly complex, context-dependent genetic underpinnings of cognitive traitsPreprint

Hamlin, V., Ansaf, H., Heffern, R., Williams‐Simon, P. A., & King, E. G. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.26.640179 · Cited by 2 · see citing works

Lessons we learned from the Lothian Birth Cohorts of 1921 and 1936

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El talento académico: una revisión conceptual

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Modifiable traits and genetic associations with grey matter volume in mid-to-late adulthood: a population-based study in the UK biobank

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Neurite density but not myelination of specific fiber tracts links polygenic scores to general intelligence

Stammen, C., Penate, J. S., Metzen, D., Hönscher, M. J., Fraenz, C., Schlüter, C., Güntürkün, O., Kumsta, R., & Genç, E. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf199 · Cited by 2 · see citing works

Association between maternal glycohemoglobin in pregnancy and adult offspring cognition: results from the Transgenerational Effects of Adult Morbidity (TEAM) Study

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Cognitive ability in childhood predicts adolescent structural and functional brain development: A longitudinal study

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Elaboration of Quantitative Assessment Technique for Genetic Predisposition to Cardiovascular System Diseases

Mosse, I. B., Булгак, А. Г., Sedlyar, N., Моссэ, К. А., Zotova, O. V., & Королёва, Т. C. (2023) · Кардиология в Беларуси · doi:10.34883/pi.2023.15.1.001 · Cited by 1 · see citing works

Protocol and preregistration for the CODEC project: measuring, modelling and mechanistically understanding the nature of cognitive variability in early childhood

Coolen, I. E. J. I., van Langen, J., Hofman, S., van Aagten, F. E., Schaaf, J. V., Michel, L. C., Aristodemou, M., Judd, N., van Hout, A. T. B., Meeussen, E., et al. (2024) · BMC Psychology · doi:10.1186/s40359-024-01904-5 · Cited by 1 · see citing works

Our faces and brains

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Evolução humana - inteligência como determinante

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¿Genes, células, áreas da inteligência cerebral e sociedade com inteligência prejudicada, o que tudo isso tem em comum?

Rodrigues, F. D. A. A. (2021) · Ciencia Latina Revista Científica Multidisciplinar · doi:10.37811/cl_rcm.v5i6.1145 · Cited by 1 · see citing works

Intelligence

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Behavioral Genetics

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Comparing the XGBoost machine learning algorithm to polygenic scoring for the prediction of intelligence based on genotype dataPreprint

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