Jaeggi, S. M., Buschkuehl, M., Jonides, J. & Perrig, W. J. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences of the United States of America, 105, 6829–6833.
Jaeggi, S. M., Buschkuehl, M., Jonides, J. Jaeggi, S. M., Buschkuehl, M., Jonides, J. & Shah, P. (2011). Short- and long-term benefits of cognitive training. Proceedings of the National Academy of Sciences of the United States of America, 108, 10081–10086.
Jaeggi, S. M., Buschkuehl, M., Shah, P. & Jonides, J. (2014). The role of individual differences in cognitive training and transfer. Memory and Cognition, 42, 464–480.
Jaeggi, S. M., Studer-Luethi, B., Buschkuehl, M., Su, Y. F., Jonides, J. & Perrig, W. J. (2010). The relationship between n-back performance and matrix reasoning – implications for training and transfer. Intelligence, 38, 625–635.
Jaenisch, R. & Bird, A. (2003). Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature Genetics, 33(Suppl), 245–254.
Jauk, E., Neubauer, A. C., Dunst, B., Fink, A. & Benedek, M. (2015). Gray matter correlates of creative potential: a latent variable voxel-based morphometry study. Neuroimage, 111, 312–320.
Jensen, A. (1980). Bias in Mental Testing, New York, NY: Free Press.
Jensen, A. R. (1969). How much can we boost IQ and scholastic achievement. Harvard Educational Review, 39, 1–123.
Jensen, A. R. (1974). Kinship correlations reported by Sir Cyril Burt. Behavior Genetics, 4, 1–28.
Jensen, A. R. (1981). Straight Talk About Mental Tests, New York, NY: Free Press.
Jensen, A. R. (1998). The g Factor: The Science of Mental Ability, Westport, CT: Praeger.
Jensen, A. R. (2006). Clocking the Mind: Mental Chronometry and Individual Differences, New York, NY: Elsevier.
Jensen, A. R. & Miele, F. (2002). Intelligence, Race, and Genetics: Conversations with Arthur R. Jensen, Boulder, CO: Westview.
Johnson, M. R., Shkura, K., Langley, S. R., Delahaye-Duriez, A., Srivastava, P., Hill, W. D., et al. (2016). Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease. Nature Neuroscience, 19, 223–232.
Johnson, W. & Bouchard, T. J. (2005). The structure of human intelligence: it is verbal, perceptual, and image rotation (VPR), not fluid and crystallized. Intelligence, 33, 393–416.
Johnson, W., Bouchard, T. J., Krueger, R. F., McGue, M. & Gottesman, I. I. (2004). Just one g: consistent results from three test batteries. Intelligence, 32, 95–107.
Johnson, W., Jung, R. E., Colom, R. & Haier, R. J. (2008a). Cognitive abilities independent of IQ correlate with regional brain structure. Intelligence, 36, 18–28.
Johnson, W., Te Nijenhuis, J. & Bouchard, T. J. (2008b). Still just 1 g: consistent results from five test batteries. Intelligence, 36, 81–95.
Jung, R. E. (2014). Evolution, creativity, intelligence, and madness: “Here Be Dragons”. Frontiers in Psychology, 5, 784.
Jung, R. E., Brooks, W. M., Yeo, R. A., Chiulli, S. J., Weers, D. C. & Sibbitt, W. L. (1999a). Biochemical markers of intelligence: a proton MR spectroscopy study of normal human brain. Proceedings of the Royal Society of London Series B – Biological Sciences, 266, 1375–1379.
Jung, R. E. & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and Brain Sciences, 30, 135–154.
Jung, R. E. & Haier, R. J. (2013). Creativity and intelligence: brain networks that link and differentiate the expression of genius. In O. Vartanian, A. S. Bristol & J. C. Kaufman, (Eds.), Neuroscience of Creativity, Cambridge, MA: The MIT Press.
Jung, R. E., Haier, R. J., Yeo, R. A., Rowland, L. M., Petropoulos, H., Levine, A. S., Sibbitt, W. L. & Brooks, W. M. (2005). Sex differences in N-acetylaspartate correlates of general intelligence: an 1H-MRS study of normal human brain. Neuroimage, 26, 965–972.
Jung, R. E., Yeo, R. A., Chiulli, S. J., Sibbitt, W. L., Weers, D. C., Hart, B. L. & Brooks, W. M. (1999b). Biochemical markers of cognition: a proton MR spectroscopy study of normal human brain. NeuroReport, 10, 3327–3331.
Kanai, R. & Rees, G. (2011). The structural basis of inter-individual differences in human behaviour and cognition. Nature Reviews Neuroscience, 12, 231–242.
Kane, M. J. & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: an individual-differences perspective. Psychonomic Bulletin & Review, 9, 637–671.
Kane, M. J., Hambrick, D. Z. & Conway, A. R. A. (2005). Working memory capacity and fluid intelligence are strongly related constructs: comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 66–71.
Karama, S., Ad-Dab’bagh, Y., Haier, R. J., Deary, I. J., Lyttelton, O. C., Lepage, C. & Evans, A. C. (2009). Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds. Intelligence, 37, 145–155.
Karama, S., Colom, R., Johnson, W., Deary, I. J., Haier, R., Waber, D. P., Lepage, C., Ganjavi, H., Jung, R., Evans, A. C. & Grp, B. D. C. (2011). Cortical thickness correlates of specific cognitive performance accounted for by the general factor of intelligence in healthy children aged 6 to 18. Neuroimage, 55, 1443–1453.
Kendler, K. S., Turkheimer, E., Ohlsson, H., Sundquist, J. & Sundquist, K. (2015). Family environment and the malleability of cognitive ability: a Swedish national home-reared and adopted-away cosibling control study. Proceedings of the National Academy of Sciences of the United States of America, 112, 4612–4617.
Keyes, D. (1966). Flowers for Algernon, New York, NY: Harcourt.
Kievit, R. A., Romeijn, J. W., Waldorp, L. J., Wicherts, J. M., Scholte, H. S. & Borsboom, D. (2011). Mind the gap: a psychometric approach to the reduction problem. Psychological Inquiry, 22, 67–87.
Kievit, R. A., Van Rooijen, H., Wicherts, J. M., Waldorp, L. J., Kan, K. J., Scholte, H. S. & Borsboom, D. (2012). Intelligence and the brain: a model-based approach. Cognitive Neuroscience, 3, 89–97.
Kim, D.-J., Davis, E. P., Sandman, C. A., Sporns, O., O’Donnell, B. F., Buss, C. & Hetrick, W. P. (2016). Children’s intellectual ability is associated with structural network integrity. Neuroimage, 124(Part A), 550–556.
Koenis, M. M., Brouwer, R. M., Van Den Heuvel, M. P., Mandl, R. C., Van Soelen, I. L., Kahn, R. S., Boomsma, D. I. & Hulshoff Pol, H. E. (2015). Development of the brain’s structural network efficiency in early adolescence: a longitudinal DTI twin study. Human Brain Mapping, 36, 4938–4953.
Kohannim, O., Hibar, D. P., Stein, J. L., Jahanshad, N., Hua, X., Rajagopalan, P., Toga, A. W., Jack, C. R., Jr., Weiner, M. W., De Zubicaray, G. I., McMahon, K. L., Hansell, N. K., Martin, N. G., Wright, M. J., Thompson, P. M. & Alzheimer’s Disease Neuroimaging Initiative. (2012a). Discovery and replication of gene influences on brain structure using LASSO regression. Frontiers in Neuroscience, 6, 115.
Kohannim, O., Jahanshad, N., Braskie, M. N., Stein, J. L., Chiang, M.-C., Reese, A. H., et al. (2012b). Predicting white matter integrity from multiple common genetic variants. Neuropsychopharmacology, 37, 2012–2019.
Kolata, S., Light, K., Wass, C. D., Colas-Zelin, D., Roy, D. & Matzel, L. D. (2010). A dopaminergic gene cluster in the prefrontal cortex predicts performance indicative of general intelligence in genetically heterogeneous mice. PLoS ONE, 5, e14036.
Kovas, Y. & Plomin, R. (2006). Generalist genes: implications for the cognitive sciences. Trends in Cognitive Sciences, 10, 198–203.
Krause, B. & Cohen Kadosh, R. (2014). Not all brains are created equal: the relevance of individual differences in responsiveness to transcranial electrical stimulation. Frontiers in Systems Neuroscience, 8, 25.
Kuhl, P. K. (2000). A new view of language acquisition. Proceedings of the National Academy of Sciences of the United States of America, 97, 11850–11857.
Kuhl, P. K. (2004). Early language acquisition: cracking the speech code. Nature Reviews Neuroscience, 5, 831–843
.
Kyllonen, P. C. & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity. Intelligence, 14, 389–433.
Langer, N., Pedroni, A., Gianotti, L. R., Hanggi, J., Knoch, D. & Jancke, L. (2012). Functional brain network efficiency predicts intelligence. Human Brain Mapping, 33, 1393–1406.
Lashley, K. S. (1964). Brain Mechanisms and Intelligence, New York, NY: Hafner.
Lee, J. J. (2010). Review of intelligence and how to get it: why schools and cultures count. Personality and Individual Differences, 48, 247–255.
Lee, K. H., Choi, Y. Y., Gray, J. R., Cho, S. H., Chae, J. H., Lee, S. & Kim, K. (2006). Neural correlates of superior intelligence: stronger recruitment of posterior parietal cortex. Neuroimage, 29, 578–586.
Lemos, G. C., Almeida, L. S. & Colom, R. (2011). Intelligence of adolescents is related to their parents’ educational level but not to family income. Personality and Individual Differences, 50, 1062–1067.
Lerner, B. (1980). The war on testing – Detroit Edison in perspective. Personnel Psychology, 33, 11–16.
Li, Y., Liu, Y., Li, J., Qin, W., Li, K., Yu, C. & Jiang, T. (2009). Brain anatomical network and intelligence. PLoS Computational Biology, 5, e1000395.
Limb, C. J. & Braun, A. R. (2008). Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation. PLoS ONE, 3, e1679.
Lipp, I., Benedek, M., Fink, A., Koschutnig, K., Reishofer, G., Bergner, S., Ischebeck, A., Ebner, F. & Neubauer, A. (2012). Investigating neural efficiency in the visuo-spatial domain: an FMRI study. PLoS ONE, 7, e51316.
Liu, S., Chow, H. M., Xu, Y., Erkkinen, M. G., Swett, K. E., Eagle, M. W., Rizik-Baer, D. A. & Braun, A. R. (2012). Neural correlates of lyrical improvisation: an FMRI study of freestyle rap. Science Reports, 2, 834.
Loehlin, J. C. (1989). Partitioning environmental and genetic contributions to behavioral development. American Psychologist, 44, 1285–1292.
Loehlin, J. C. & Nichols, R. C. (1976). Heredity, Environment, & Personality: A Study of 850 Sets of Twins, Austin, TX: University of Texas Press.
Luber, B. & Lisanby, S. H. (2014). Enhancement of human cognitive performance using transcranial magnetic stimulation (TMS). Neuroimage, 85(Pt 3), 961–970.
Lubinski, D. (2009). Cognitive epidemiology: with emphasis on untangling cognitive ability and socioeconomic status. Intelligence, 37, 625–633.
Lubinski, D., Benbow, C. P. & Kell, H. J. (2014). Life paths and accomplishments of mathematically precocious males and females four decades later. Psychological Science, 25, 2217–2232.
Lubinski, D., Benbow, C. P., Webb, R. M. & Bleske-Rechek, A. (2006). Tracking exceptional human capital over two decades. Psychological Science, 17, 194–199.
Lubinski, D., Schmidt, D. B. & Benbow, C. P. (1996). A 20-year stability analysis of the study of values for intellectually gifted individuals from adolescence to adulthood. Journal of Applied Psychology, 81, 443–451.
Luciano, M., Wright, M. J., Smith, G. A., Geffen, G. M., Geffen, L. B. & Martin, N. G. (2001). Genetic covariance among measures of information processing speed, working memory, and IQ. Behavior and Genetics, 31, 581–592.
Luders, E., Harr, K. L., Thompson, P. M., Rex, D. E., Woods, R. P., Deluca, H., Jancke, L. & Toga, A. W. (2006). Gender effects on cortical thickness and the influence of scaling. Human Brain Mapping, 27, 314–324.
Luders, E., Narr, K. L., Bilder, R. M., Thompson, P. M., Szeszko, P. R., Hamilton, L. & Toga, A. W. (2007). Positive correlations between corpus callosum thickness and intelligence. Neuroimage, 37, 1457–1464.
Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Jancke, L., Steinmetz, H. & Toga, A. W. (2004). Gender differences in cortical complexity. Nature Neuroscience, 7, 799–800.
Luo, Q., Perry, C., Peng, D. L., Jin, Z., Xu, D., Ding, G. S. & Xu, S. Y. (2003). The neural substrate of analogical reasoning: an fMRI study. Cognitive Brain Research, 17, 527–534.
Mackey, A. P., Finn, A. S., Leonard, J. A., Jacoby-Senghor, D. S., West, M. R., Gabrieli, C. F. & Gabrieli, J. D. (2015). Neuroanatomical correlates of the income-achievement gap. Psychological Science, 26, 925–933.
Mackey, A. P., Hill, S. S., Stone, S. I. & Bunge, S. A. (2011). Differential effects of reasoning and speed training in children. Developmental Science, 14, 582–590.
Mackintosh, N. J. (1995). Cyril Burt: Fraud or Framed? Oxford: Oxford University Press.
Mackintosh, N. J. (2011) IQ and Human Intelligence, Oxford: Oxford University Press.
Maguire, E. A., Valentine, E. R., Wilding, J. M. & Kapur, N. (2003). Routes to remembering: the brains behind superior memory. Nature Neuroscience, 6, 90–95.
Maher, B. (2008). Poll results: look who’s doping. Nature, 452, 674–675.
Maldjian, J. A., Davenport, E. M. & Whitlow, C. T. (2014). Graph theoretical analysis of resting-state MEG data: identifying interhemispheric connectivity and the default mode. Neuroimage, 96, 88–94.
Mardis, E. R. (2008). Next-generation DNA sequencing methods. Annual Review of Genomics and Humam Genetics, 9, 387–402.
Marioni, R. E., Davies, G., Hayward, C., Liewald, D., Kerr, S. M., Campbell, A., et al. (2014). Molecular genetic contributions to socioeconomic status and intelligence. Intelligence, 44, 26–32.
Maslen, H., Faulmuller, N. & Savulescu, J. (2014). Pharmacological cognitive enhancement – how neuroscientific research could advance ethical debate. Frontiers in Systems Neuroscience, 8, 107.
Matzel, L. D., Han, Y. R., Grossman, H., Karnik, M. S., Patel, D., Scott, N., Specht, S. M. & Gandhi, C. C. (2003). Individual differences in the expression of a “general” learning ability in mice. Journal of Neuroscience, 23, 6423–6433.
Matzel, L. D. & Kolata, S. (2010). Selective attention, working memory, and animal intelligence. Neuroscience and Biobehavioral Reviews, 34, 23–30.
Matzel, L. D., Sauce, B. & Wass, C. (2013). The architecture of intelligence: converging evidence from studies of humans and animals. Current Directions in Psychological Science, 22, 342–348.
Mayseless, N. & Shamay-Tsoory, S. G. (2015). Enhancing verbal creativity: modulating creativity by altering the balance between right and left inferior frontal gyrus with tDCS. Neuroscience, 291, 167–176.
McDaniel, M. A. (2005). Big-brained people are smarter: a meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33, 337–346.
McGue, M., Bouchard, T. J., Iacono, W. G. & Lykken, D. T. (1993). Age effects on heritability of intelligence. In R. Plomin & G. E. McClearn (Eds.), Nature, Nurture, and Psychology, Washington, DC: American Psychological Association.
McKinley, R. A., Bridges, N., Walters, C. M. & Nelson, J. (2012). Modulating the brain at work using noninvasive transcranial stimulation. Neuroimage, 59, 129–137.
Melby-Lervag, M. & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49, 270–291.
Miller, B. L., Boone, K., Cummings, J. L., Read, S. L. & Mishkin, F. (2000). Functional correlates of musical and visual ability in frontotemporal dementia. British Journal of Psychiatry, 176, 458–463.
Miller, B. L., Cummings, J., Mishkin, F., Boone, K., Prince, F., Ponton, M. & Cotman, C. (1998). Emergence of artistic talent in frontotemporal dementia. Neurology, 51, 978–982.
Moody, D. E. (2009). Can intelligence be increased by training on a task of working memory? Intelligence, 37, 327–328.
Muetzel, R. L., Mous, S. E., Van Der Ende, J., Blanken, L. M., Van Der Lugt, A., Jaddoe, V. W., Verhulst, F. C., Tiemeier, H. & White, T. (2015). White matter integrity and cognitive performance in school-age children: a population-based neuroimaging study. Neuroimage, 119, 119–128.
Murray, C. (1995). The bell curve and its critics. Commentary, 99, 23–30.
Murray, C., Pattie, A., Starr, J. M. & Deary, I. J. (2012) Does cognitive ability predict mortality in the ninth decade? The Lothian Birth Cohort 1921. Intelligence, 40, 490–498.
Muzur, A., Pace-Schott, E. F. & Ho
bson, J. A. (2002). The prefrontal cortex in sleep. Trends in Cognitive Science, 6, 475–481.
Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci, S. J., Halpern, D. F., Loehlin, J. C., Perloff, R., Sternberg, R. J. & Urbina, S. (1996). Intelligence: knowns and unknowns. American Psychologist, 51, 77–101.
Neubauer, A. C. & Fink, A. (2009). Intelligence and neural efficiency. Neuroscience and Biobehavioral Reviews, 33, 1004–1023.
Neville, H., Stevens, C., Pakulak, E. & Bell, T. A. (2013). Commentary: neurocognitive consequences of socioeconomic disparities. Developmental Science, 16, 708–712.
Newman, S. D. & Just, M. A. (2005). The neural bases of intelligence: a perspective based on functional neuroimaging. In Cognition and Intelligence: Identifying the Mechanisms of the Mind. New York, NY: Cambridge University Press.
Nihongaki, Y., Kawano, F., Nakajima, T. & Sato, M. (2015). Photoactivatable CRISPR-Cas9 for optogenetic genome editing. Nature Biotechnology, 33, 755–760.
Nisbett, R. E. (2009). Intelligence and How To Get It: Why Schools and Cultures Count, New York, NY: W.W. Norton & Co.
Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F. & Turkheimer, E. (2012). Intelligence: new findings and theoretical developments. American Psychologist, 67, 130–159.
Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kan, E., Kuperman, J. M., et al. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18, 773–778.
Pahor, A. & Jausovec, N. (2014). The effects of theta transcranial alternating current stimulation (tACS) on fluid intelligence. International Journal of Psychophysiology, 93, 322–331.
Panizzon, M. S., Vuoksimaa, E., Spoon, K. M., Jacobson, K. C., Lyons, M. J., Franz, C. E., Xian, H., Vasilopoulos, T. & Kremen, W. S. (2014). Genetic and environmental influences of general cognitive ability: is g a valid latent construct? Intelligence, 43, 65–76.
Parasuraman, R. & Jiang, Y. (2012). Individual differences in cognition, affect, and performance: behavioral, neuroimaging, and molecular genetic approaches. Neuroimage, 59, 70–82.
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