Skip to main content Accessibility help
×
  • Cited by 65
Publisher:
Cambridge University Press
Online publication date:
July 2017
Print publication year:
2016
Online ISBN:
9781316105771

Book description

This book introduces new and provocative neuroscience research that advances our understanding of intelligence and the brain. Compelling evidence shows that genetics plays a more important role than environment as intelligence develops from childhood, and that intelligence test scores correspond strongly to specific features of the brain assessed with neuroimaging. In understandable language, Richard J. Haier explains cutting-edge techniques based on genetics, DNA, and imaging of brain connectivity and function. He dispels common misconceptions, such as the belief that IQ tests are biased or meaningless, and debunks simple interventions alleged to increase intelligence. Readers will learn about the real possibility of dramatically enhancing intelligence based on neuroscience findings and the positive implications this could have for education and social policy. The text also explores potential controversies surrounding neuro-poverty, neuro-socioeconomic status, and the morality of enhancing intelligence for everyone. Online resources, including additional visuals, animations, questions and links, reinforce the material.

Reviews

'Forty years of Haier’s research and thinking about the neuroscience of intelligence have been condensed into this captivating book. He consistently gets it right, even with tricky issues like genetics. It is an intelligent and honest book.'

Robert Plomin - King’s College London

'An original, thought-provoking review of modern research on human intelligence from one of its pioneers.'

Aron K. Barbey - University of Illinois

'Deftly presenting the latest insights from genetics and neuroimaging, Haier provides a brilliant exposition of the recent scientific insights into the biology of intelligence. Highly timely, clearly written, certainly a must-read for anyone interested in the neuroscience of intelligence!'

Danielle Posthuma - Vrije Universiteit Amsterdam

'The trek through the maze of recent work using the modern tools of neuroscience and molecular genetics will whet the appetite of aspiring young researchers. The author's enthusiasm for the discoveries that lie ahead is infectious. Kudos!'

Thomas J. Bouchard Jr. - Emeritus Professor of Psychology, University of Minnesota

'Richard J. Haier invites us to a compelling journey across a century of highs and lows of intelligence research, settling old debates and fueling interesting questions for new generations to solve. From cognitive enhancement to models predicting IQ based on brain scans, the quest to define the neurobiological basis of human intelligence has never been more exciting.'

Emiliano Santarnecchi - Harvard Medical School

'Loud voices have dismissed and derided the measurement of human intelligence differences, their partial origins in genetics, and their associations with brain structure and function. If they respect data, Haier's book will quieten them. It's interesting to think how slim a book with the title The Neuroscience of Intelligence would have been not long ago, and how big it will be soon; Haier's lively book is a fingerpost showing the directions in which this important area is heading.'

Ian J. Deary - University of Edinburgh

'The biology of few psychological differences is as well understood as that of intelligence. Richard J. Haier pioneered the field of intelligence neuroscience and he is still at its forefront. This book summarizes the impressive state the field has reached, and foreshadows what it might become.'

Lars Penke - Georg-August-Universität, Göttingen, Germany

'… this text is welcome, needed and important to help those of us who wait for research findings to guide our clinical interventions.'

Laura Hill - Ohio State University

'This book was overdue: a highly readable and inspiring account of cutting-edge research in neuroscience of human intelligence. Penned by Richard J. Haier, the eminent founder of this research field, the book is an excellent introduction for beginners and a valuable source of information for experts.'

Aljoscha Neubauer - University of Graz, Austria

'This book is ‘A Personal Voyage through the Neuroscience of Intelligence’. Reading this wonderful volume ‘forces thinking,’ which can be said only about a very small fraction of books. Here the reader will find reasoned confidence on the exciting advances, waiting next door, regarding the neuroscience of intelligence and based on the author’s three basic laws: 1. No story about the brain is simple, 2. No one study is definitive, and 3. It takes many studies and many years to sort things out.'

Roberto Colom - Universidad Autonoma de Madrid

'Richard J. Haier’s The Neuroscience of Intelligence is an excellent summary of the major progress made in the fields of psychology, genetics and cognitive neuroscience, expanding upon the groundbreaking work of 'The Bell Curve.' He addresses the many misconceptions and myths that surround this important human capacity with a clear summary of the vast body of research now extending into the human brain and genome.'

Rex E. Jung - University of New Mexico

'The Neuroscience of Intelligence is a compelling text that addresses a complex body of research (intelligence research) that has often been misinterpreted and manipulated by secondary and tertiary sources. This book is a must read for psychology and other social science students. Given the broad range of misinformation about intelligence testing, despite the academic and clinical need for that testing, it would be beneficial for this text to be widely read. It would serve as a great learning tool to teach undergraduate students about intelligence also how science and politics interact.'

Robert B. Perna Source: PsycCRITIQUES

'… an exceptional resource for any individual interested in a technically thorough but easy-to-digest compilation of the neuroscience of intelligence.'

Source: CHOICE

'The Neuroscience of Intelligence melds a century’s worth of psychometrics with the most recent advances in genetics and neuroimaging to reveal the cutting edge of intelligence research. This book is an impressively broad review of the current state of the field that does not compromise on depth. It can serve as a crash course for budding researchers in the field while highlighting many exciting prospects for those already involved. … The book is inspiring and enjoyable to read, and it is structured in a way that 'forces thinking' while capturing the passion that Haier feels for this exciting field.'

Arseni Sitartchouk and Alan C. Evans Source: Intelligence

'Dr Haier has compiled an impressive collection of scientific findings and arguments …'

Nathaniel Barr Source: British Journal of Psychology

Refine List

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
×

Contents

References

Ackerman, P. L., Beier, M. E. & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131, 3060.
Alkire, M. T. & Haier, R. J. (2001). Correlating in vivo anaesthetic effects with ex vivo receptor density data supports a GABAergic mechanism of action for propofol, but not for isoflurane. British Journal of Anaesthesiology, 86, 618626.
Alkire, M. T., Haier, R. J., Barker, S. J., Shah, N. K., Wu, J. C. & Kao, Y. J. (1995). Cerebral metabolism during propofol anesthesia in humans studied with positron emission tomography. Anesthesiology, 82, 393403; discussion 27A.
Alkire, M. T., Haier, R. J. & Fallon, J. H. (2000). Toward a unified theory of narcosis: brain imaging evidence for a thalamocortical switch as the neurophysiologic basis of anesthetic-induced unconsciousness. Consciousness and Cognition, 9, 370386.
Alkire, M. T., Pomfrett, C. J. D., Haier, R. J., Gianzero, M. V., Chan, C. M., Jacobsen, B. P. & Fallon, J. H. (1999). Functional brain imaging during anesthesia in humans – effects of halothane on global and regional cerebral glucose metabolism. Anesthesiology, 90, 701709.
Anderson, D. J. (2012). Optogenetics, sex, and violence in the brain: implications for psychiatry. Biological Psychiatry, 71, 10811089.
Anderson, J. W., Johnstone, B. M. & Remley, D. T. (1999). Breast-feeding and cognitive development: a meta-analysis. American Journal of Clinical Nutrition, 70, 525535.
Andreasen, N. C., Flaum, M., Swayze, V., O’Leary, D. S., Alliger, R., Cohen, G., Ehrhardt, J. & Yuh, W. T. (1993). Intelligence and brain structure in normal individuals. American Journal of Psychiatry, 150, 130134.
Ángeles Quiroga, M., Escorial, S., Román, F. J., Morillo, D., Jarabo, A., Privado, J., Hernández, M., Gallego, B. & Colom, R. (2015). Can we reliably measure the general factor of intelligence (g) through commercial video games? Yes, we can! Intelligence, 53, 17.
Arden, R. (2003). An Arthurian romance. In Nyborg, H. (Ed.), The Scientific Study of General Intelligence, Oxford: Pergamon Press.
Arden, R., Chavez, R. S., Grazioplene, R. & Jung, R. E. (2010). Neuroimaging creativity: a psychometric view. Behavior and Brain Research, 214, 143156.
Arden, R., Luciano, M., Deary, I. J., Reynolds, C. A., Pedersen, N. L., Plassman, B. L., McGue, M., Christensen, K. & Visscher, P. M.(2015). The association between intelligence and lifespan is mostly genetic. International Journal of Epidemiology, 45, 178–185.
Asbury, K. & Plomin, R. (2014). G is for Genes: The Impact of Genetics on Education and Achievement, Chichester: Wiley-Blackwell.
Asbury, K., Wachs, T. D. & Plomin, R. (2005). Environmental moderators of genetic influence on verbal and nonverbal abilities in early childhood. Intelligence, 33, 643661.
Ashburner, J. & Friston, K. (1997). Multimodal image coregistration and partitioning – a unified framework. Neuroimage, 6, 209217.
Ashburner, J. & Friston, K. J. (2000). Voxel-based morphometry – the methods. Neuroimage, 11, 805821.
Aston-Jones, G. & Deisseroth, K. (2013). Recent advances in optogenetics and pharmacogenetics. Brain Research, 1511, 15.
Atherton, M., Zhuang, J. C., Bart, W. M., Hu, X. P. & He, S. (2003). A functional MRI study of high-level cognition. I. The game of chess. Cognitive Brain Research, 16, 2631.
Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M. & Jaeggi, S. M. (2015). Improving fluid intelligence with training on working memory: a meta-analysis. Psychonomic Bulletin and Review, 22, 366377.
Bagot, K. S. & Kaminer, Y. (2014). Efficacy of stimulants for cognitive enhancement in non-attention deficit hyperactivity disorder youth: a systematic review. Addiction, 109, 547557.
Barbey, A. K., Colom, R., Paul, E., Forbes, C., Krueger, F., Goldman, D. & Grafman, J. (2014). Preservation of general intelligence following traumatic brain injury: contributions of the Met66 brain-derived neurotrophic factor. PLoS ONE, 9, e88733.
Barnett, W. S. & Hustedt, J. T. (2005). Head start’s lasting benefits. Infants and Young Children, 18, 1624.
Bassett, D. S., Yang, M., Wymbs, N. F. & Grafton, S. T. (2015). Learning-induced autonomy of sensorimotor systems. Nature Neuroscience, 18, 744751.
Basso, A., De Renzi, E., Faglioni, P., Scotti, G. & Spinnler, H. (1973). Neuropsychological evidence for the existence of cerebral areas critical to the performance of intelligence tasks. Brain, 96, 715–28.
Basten, U., Hilger, K. & Fiebach, C. J. (2015). Where smart brains are different: a quantitative meta-analysis of functional and structural brain imaging studies on intelligence. Intelligence, 51, 1027.
Basten, U., Stelzel, C. & Fiebach, C. J. (2013). Intelligence is differentially related to neural effort in the task-positive and the task-negative brain network. Intelligence, 41, 517528.
Bates, T. C., Lewis, G. J. & Weiss, A. (2013). Childhood socioeconomic status amplifies genetic effects on adult intelligence. Psychological Science, 24, 21112116.
Batty, G. D., Deary, I. J. & Gottfredson, L. S. (2007). Premorbid (early life) IQ and later mortality risk: systematic review. Annals of Epidemiology, 17, 278288.
Beaty, R. E. (2015). The neuroscience of musical improvisation. Neuroscience and Biobehavioral Reviews, 51, 108117.
Bejjanki, V. R., Zhang, R., Li, R., Pouget, A., Green, C. S., Lu, Z. L. & Bavelier, D. (2014). Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy of Sciences of the United States of America, 111, 1696116966.
Bengtsson, S. L., Csikszentmihalyi, M. & Ullen, F. (2007). Cortical regions involved in the generation of musical structures during improvisation in pianists. Journal of Cognitive Neuroscience, 19, 830842.
Benyamin, B., Pourcain, B., Davis, O. S., Davies, G., Hansell, N. K., Brion, M. J., et al. (2014). Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Molecular Psychiatry, 19, 253258.
Berkowitz, A. L. & Ansari, D. (2010). Expertise-related deactivation of the right temporoparietal junction during musical improvisation. Neuroimage, 49, 712719.
Bishop, S. J., Fossella, J., Croucher, C. J. & Duncan, J. (2008). COMT val158met genotype affects recruitment of neural mechanisms supporting fluid intelligence. Cerebral Cortex, 18, 21322140.
Bogg, T. & Lasecki, L. (2015). Reliable gains? Evidence for substantially underpowered designs in studies of working memory training transfer to fluid intelligence. Frontiers in Psychology, 5, 1589.
Bohlken, M. M., Brouwer, R. M., Mandl, R. C., Van Haren, N. E., Brans, R. G., Van Baal, G. C., et al. (2014). Genes contributing to subcortical volumes and intellectual ability implicate the thalamus. Human Brain Mapping, 35, 26322642.
Boivin, M. J., Giordani, B., Berent, S., Amato, D. A., Lehtinen, S., Koeppe, R. A., Buchtel, H. A., Foster, N. L. & Kuhl, D. E. (1992). Verbal fluency and positron emission tomographic mapping of regional cerebral glucose metabolism. Cortex, 28, 231239.
Bouchard, T. J. (2009). Genetic influence on human intelligence (Spearman’s g): how much? Annals of Human Biology, 36, 527544.
Bouchard, T. J., Jr. (1998). Genetic and environmental influences on adult intelligence and special mental abilities. Human Biology, 70, 257279.
Bouchard, T. J., & McGue, M. (1981). Familial studies of intelligence: a review. Science, 212, 10551059.
Brans, R. G. H., Kahn, R. S., Schnack, H. G., Van Baal, G. C. M., Posthuma, D., Van Haren, N. E. M., et al. (2010). Brain plasticity and intellectual ability are influenced by shared genes. Journal of Neuroscience, 30, 55195524.
Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues, Leipzig: Barth.
Burgaleta, M. & Colom, R. (2008). Short-term storage and mental speed account for the relationship between working memory and fluid intelligence. Psicothema, 20, 780785.
Burgaleta, M., MacDonald, P. A., Martinez, K., Roman, F. J., Alvarez-Linera, J., Gonzalez, A. R., Karama, S. & Colom, R. (2014). Subcortical regional morphology correlates with fluid and spatial intelligence. Human Brain Mapping, 35, 19571968.
Burt, C. (1943). Ability and income. British Journal of Educational Psychology, 13, 8398.
Burt, C. (1955). The evidence for the concept of intelligence. British Journal of Educational Psychology, 25, 158177.
Burt, C. (1966). The genetic determination of differences in intelligence – a study of monozygotic twins reared together and apart. British Journal of Psychology, 57, 137153.
Cabeza, R. & Nyberg, L. (2000). Imaging cognition II: an empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 12, 147.
Cajal, R. S. (1924). Pensamientos Escogidos [Chosen Thoughts], Madrid: Cuadernos Literarios.
Campbell, F. A., Pungello, E., Miller-Johnson, S., Burchinal, M. & Ramey, C. T. (2001). The development of cognitive and academic abilities: growth curves from an early childhood educational experiment. Developmental Psychology, 37, 231242.
Cardoso-Leite, P. & Bavelier, D. (2014). Video game play, attention, and learning: how to shape the development of attention and influence learning? Current Opinions in Neurology, 27, 185191.
Cattell, R. B. (1971). Abilities: Their Structure, Growth, and Action, Boston: Houghton Mifflin.
Cattell, R. B. (1987). Intelligence: Its Structure, Growth, and Action, Amsterdam: Elsevier.
Ceci, S. J. (1991). How much does schooling influence general intelligence and its cognitive components – a reassessment of the evidence. Developmental Psychology, 27, 703722.
Ceci, S. J. & Williams, W. M. (1997). Schooling, intelligence, and income. American Psychologist, 52, 10511058.
Chabris, C. F. (1999). Prelude or requiem for the “Mozart effect”? Nature, 400, 826827.
Chabris, C. F., Hebert, B. M., Benjamin, D. J., Beauchamp, J., Cesarini, D., Van Der Loos, M., et al. (2012). Most reported genetic associations with general intelligence are probably false positives. Psychological Science, 23, 13141323.
Champagne, F. A. & Curley, J. P. (2009). Epigenetic mechanisms mediating the long-term effects of maternal care on development. Neuroscience and Biobehavioral Reviews, 33, 593600.
Chiang, M. C., Barysheva, M., McMahon, K. L., De Zubicaray, G. I., Johnson, K., Montgomery, G. W., et al. (2012). Gene network effects on brain microstructure and intellectual performance identified in 472 twins. Journal of Neuroscience, 32, 87328745.
Chiang, M. C., Barysheva, M., Shattuck, D. W., Lee, A. D., Madsen, S. K., Avedissian, C., et al. (2009). Genetics of brain fiber architecture and intellectual performance. Journal of Neuroscience, 29, 22122224.
Chiang, M. C., Barysheva, M., Toga, A. W., Medland, S. E., Hansell, N. K., James, M. R., et al. (2011a). BDNF gene effects on brain circuitry replicated in 455 twins. Neuroimage, 55, 448454.
Chiang, M. C., McMahon, K. L., De Zubicaray, G. I., Martin, N. G., Hickie, I., Toga, A. W., Wright, M. J. & Thompson, P. M. (2011b). Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage, 54, 23082317.
Choi, Y. Y., Shamosh, N. A., Cho, S. H., DeYoung, C. G., Lee, M. J., Lee, J. M., Kim, S. I., Cho, Z. H., Kim, K., Gray, J. R. & Lee, K. H. (2008). Multiple bases of human intelligence revealed by cortical thickness and neural activation. Journal of Neuroscience, 28, 1032310329.
Chooi, W. T. & Thompson, L. A. (2012). Working memory training does not improve intelligence in healthy young adults. Intelligence, 40, 531542.
Chugani, H. T., Phelps, M. E. & Mazziotta, J. C. (1987). Positron emission tomography study of human brain functional development. Annals of Neurology, 22, 487497.
Clark, V. P., Coffman, B. A., Mayer, A. R., Weisend, M. P., Lane, T. D., Calhoun, V. D., Raybourn, E. M., Garcia, C. M. & Wassermann, E. M. (2012). TDCS guided using fMRI significantly accelerates learning to identify concealed objects. Neuroimage, 59, 117128.
Coffman, B. A., Clark, V. P. & Parasuraman, R. (2014). Battery powered thought: enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation. Neuroimage, 85(Pt 3), 895908.
Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A. & Braver, T. S. (2012). Global connectivity of prefrontal cortex predicts cognitive control and intelligence. Journal of Neuroscience, 32, 89888999.
Colom, R., Abad, F. J., Quiroga, M. A., Shih, P. C. & Flores-Mendoza, C. (2008). Working memory and intelligence are highly related constructs, but why? Intelligence, 36, 584606.
Colom, R. & Flores-Mendoza, C. E. (2007). Intelligence predicts scholastic achievement irrespective of SES factors: evidence from Brazil. Intelligence, 35, 243251.
Colom, R., Jung, R. E. & Haier, R. J. (2006a). Distributed brain sites for the g-factor of intelligence. Neuroimage, 31, 13591365.
Colom, R., Jung, R. E. (2006b). Finding the g-factor in brain structure using the method of correlated vectors. Intelligence, 34, 561.
Colom, R., Jung, R. E. (2007). General intelligence and memory span: evidence for a common neuroanatomic framework. Cognitive Neuropsychology, 24, 867878.
Colom, R., Karama, S., Jung, R. E. & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in Clinical Neuroscience, 12, 489501.
Colom, R., Rebollo, I., Palacios, A., Juan-Espinosa, M. & Kyllonen, P. C. (2004). Working memory is (almost) perfectly predicted by g. Intelligence, 32, 277296.
Colom, R., Roman, F. J., Abad, F. J., Shih, P. C., Privado, J., Froufe, M., et al. (2013). Adaptive n-back training does not improve fluid intelligence at the construct level: gains on individual tests suggest that training may enhance visuospatial processing. Intelligence, 41, 712727.
Conway, A. R. A., Kane, M. J. & Engle, R. W. (2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences, 7, 547552.
Covington, H. E., 3rd, Lobo, M. K., Maze, I., Vialou, V., Hyman, J. M., Zaman, S., Laplant, Q., Mouzon, E., Ghose, S., Tamminga, C. A., Neve, R. L., Deisseroth, K. & Nestler, E. J. (2010). Antidepressant effect of optogenetic stimulation of the medial prefrontal cortex. Journal of Neuroscience, 30, 1608216090.
Crick, F. (1994). The Astonishing Hypothesis: The Scientific Search for the Soul, New York: Scribner, Maxwell Macmillan International.
Curlik, D. M., 2nd, Maeng, L. Y., Agarwal, P. R. & Shors, T. J. (2013). Physical skill training increases the number of surviving new cells in the adult hippocampus. PLoS ONE, 8, e55850.
Curlik, D. M., Curlik, D. M., 2nd & Shors, T. J. (2013). Training your brain: do mental and physical (MAP) training enhance cognition through the process of neurogenesis in the hippocampus? Neuropharmacology, 64, 506514.
Davies, G., Armstrong, N., Bis, J. C., Bressler, J., Chouraki, V., Giddaluru, S., et al. (2015). Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949). Molecular Psychiatry, 20, 183192.
Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., et al. (2011). Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry, 16, 9961005.
Davis, J. M., Searles, V. B., Anderson, N., Keeney, J., Raznahan, A., Horwood, L. J., Fergusson, D. M., Kennedy, M. A., Giedd, J. & Sikela, J. M. (2015). DUF1220 copy number is linearly associated with increased cognitive function as measured by total IQ and mathematical aptitude scores. Human Genetics, 134, 6775.
Deary, I. J. (2000). Looking Down on Human Intelligence: From Psychometrics to the Brain, Oxford: Oxford University Press.
Deary, I. J., Penke, L. & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience, 11, 201211.
Deary, I. J., Whiteman, M. C., Starr, J. M., Whalley, L. J. & Fox, H. C. (2004). The impact of childhood intelligence on later life: following up the Scottish Mental Surveys of 1932 and 1947. Journal of Personality and Social Psychology, 86, 130147.
Del Río, D., Cuesta, P., Bajo, R., García-Pacios, J., López-Higes, R., Del-Pozo, F. & Maestú, F. (2012). Efficiency at rest: magnetoencephalographic resting-state connectivity and individual differences in verbal working memory. International Journal of Psychophysiology, 86, 160167.
Der, G., Batty, G. D. & Deary, I. J. (2006). Effect of breast feeding on intelligence in children: prospective study, sibling pairs analysis, and meta-analysis. British Medical Journal, 333, 945.
Desrivieres, S., Lourdusamy, A., Tao, C., Toro, R., Jia, T., Loth, E., et al. (2015). Single nucleotide polymorphism in the neuroplastin locus associates with cortical thickness and intellectual ability in adolescents. Molecular Psychiatry, 20, 263274.
Detterman, D. K. (2014). Introduction to the intelligence special issue on the development of expertise: is ability necessary? Intelligence, 45, 15.
Dietrich, A. & Kanso, R. (2010). A review of EEG, ERP, and neuroimaging studies of creativity and insight. Psychological Bulletin, 136, 822848.
Donnay, G. F., Rankin, S. K., Lopez-Gonzalez, M., Jiradejvong, P. & Limb, C. J. (2014). Neural substrates of interactive musical improvisation: an FMRI study of ‘trading fours’ in jazz. PLoS ONE, 9, e88665.
Drury, S. S., Theall, K., Gleason, M. M., Smyke, A. T., De Vivo, I., Wong, J. Y., Fox, N. A., Zeanah, C. H. & Nelson, C. A. (2012). Telomere length and early severe social deprivation: linking early adversity and cellular aging. Molecular Psychiatry, 17, 719727.
Duncan, G. J. & Sojourner, A. J. (2013). Can intensive early childhood intervention programs eliminate income-based cognitive and achievement gaps? Journal of Human Resources, 48, 945968.
Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in Cognitive Sciences, 14, 172179.
Duncan, J., Burgess, P. & Emslie, H. (1995). Fluid intelligence after frontal lobe lesions. Neuropsychologia, 33, 261268.
Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., Newell, F. N. & Emslie, H. (2000). A neural basis for general intelligence. Science, 289, 457460.
Ericsson, K. A. (2014). Why expert performance is special and cannot be extrapolated from studies of performance in the general population: a response to criticisms. Intelligence, 45, 81103.
Esposito, G., Kirkby, B. S., Van Horn, J. D., Ellmore, T. M. & Berman, K. F. (1999). Context-dependent, neural system-specific neurophysiological concomitants of ageing: mapping PET correlates during cognitive activation. Brain, 122, 963979.
Ezkurdia, I., Juan, D., Rodriguez, J. M., Frankish, A., Diekhans, M., Harrow, J., Vazquez, J., Valencia, A. & Tress, M. L. (2014). Multiple evidence strands suggest that there may be as few as 19,000 human protein-coding genes. Human Molecular Genetics, 23, 58665878.
Falk, D., Lepore, F. E. & Noe, A. (2013). The cerebral cortex of Albert Einstein: a description and preliminary analysis of unpublished photographs. Brain, 136, 13041327.
Fangmeier, T., Knauff, M., Ruff, C. C. & Sloutsky, V. M. (2006). fMRI evidence for a three-stage model of deductive reasoning. Journal of Cognitive Neuroscience, 18, 320334.
Farah, M. J., Betancourt, L., Shera, D. M., Savage, J. H., Giannetta, J. M., Brodsky, N. L., Malmud, E. K. & Hurt, H. (2008). Environmental stimulation, parental nurturance and cognitive development in humans. Developmental Science, 11, 793801.
Farah, M. J., Smith, M. E., Ilieva, I. & Hamilton, R. H. (2014). Cognitive enhancement. Wiley Interdisciplinary Reviews – Cognitive Science, 5, 95103.
Ferrer, E., O’Hare, E. D. & Bunge, S. A. (2009). Fluid reasoning and the developing brain. Frontiers in Neuroscience, 3, 4651.
Fink, A., Grabner, R. H., Gebauer, D., Reishofer, G., Koschutnig, K. & Ebner, F. (2010). Enhancing creativity by means of cognitive stimulation: evidence from an fMRI study. Neuroimage, 52, 16871695.
Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., Papademetris, X. & Constable, R. T. (2015). Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature Neuroscience, 18, 16641671.
Firkowska, A., Ostrowska, A., Sokolowska, M., Stein, Z., Susser, M. & Wald, I. (1978). Cognitive development and social policy. Science, 200, 13571362.
Flashman, L. A., Andreasen, N. C., Flaum, M. & Swayze, V. W. (1997). Intelligence and regional brain volumes in normal controls. Intelligence, 25, 149160.
Flynn, J. R. (2013). The “Flynn Effect” and Flynn’s paradox. Intelligence, 41, 851857.
Frangou, S., Chitins, X. & Williams, S. C. R. (2004). Mapping IQ and gray matter density in healthy young people. Neuroimage, 23, 800805.
Fregnac, Y. & Laurent, G. (2014). Neuroscience: where is the brain in the Human Brain Project? Nature, 513, 2729.
Frey, M. C. & Detterman, D. K. (2004). Scholastic assessment or g? The relationship between the scholastic assessment test and general cognitive ability. Psychological Science, 15, 373378; erratum 15, 641.
Galaburda, A. M. (1999). Albert Einstein’s brain. Lancet, 354, 1821; author reply 1822.
Galton, F. (1869). Hereditary Genius: An Inquiry into its Laws and Consequences, London: Macmillan.
Galton, F. (2006). Hereditary Genius: An Inquiry into its Laws and Consequences, Amherst, NY: Prometheus Books.
Galton, F. & Prinzmetal, M. (1884). Hereditary Genius: An Inquiry into its Laws and Consequences, New York, NY: D. Appleton and Company.
Gardner, H. (1987). The theory of multiple intelligences. Annals of Dyslexia, 37, 1935.
Gardner, H. & Moran, S. (2006). The science of multiple intelligences theory: a response to Lynn Waterhouse. Educational Psychologist, 41, 227232.
Geake, J. (2008). Neuromythologies in education. Educational Research, 50, 123133.
Geake, J. (2011). Position statement on motivations, methodologies, and practical implications of educational neuroscience research: fMRI studies of the neural correlates of creative intelligence. Educational Philosophy and Theory, 43, 4347.
Geake, J. G. & Hansen, P. C. (2005). Neural correlates of intelligence as revealed by fMRI of fluid analogies. Neuroimage, 26, 555564.
Ghatan, P. H., Hsieh, J. C., Wirsén-Meurling, A., Wredling, R., Eriksson, L., Stone-Elander, S., Levander, S. & Ingvar, M. (1995). Brain activation-induced by the perceptual maze test: a PET study of cognitive performance. Neuroimage, 2, 112124.
Gignac, G. E. (2015). Raven’s is not a pure measure of general intelligence: implications for g factor theory and the brief measurement of g. Intelligence, 52, 7179.
Glascher, J., Rudrauf, D., Colom, R., Paul, L. K., Tranel, D., Damasio, H. & Adolphs, R. (2010). Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences of the United States of America, 107, 47054709.
Glascher, J., Tranel, D., Paul, L. K., Rudrauf, D., Rorden, C., Hornaday, A., Grabowski, T., Damasio, H. & Adolphs, R. (2009). Lesion mapping of cognitive abilities linked to intelligence. Neuron, 61, 681691.
Goel, V. & Dolan, R. J. (2004). Differential involvement of left prefrontal cortex in inductive and deductive reasoning. Cognition, 93, B109B121.
Goel, V., Gold, B., Kapur, S. & Houle, S. (1997). The seats of reason? An imaging study of deductive and inductive reasoning. Neuroreport, 8, 13051310.
Goel, V., Gold, B., Kapur, S. (1998). Neuroanatomical correlates of human reasoning. Journal of Cognitive Neuroscience, 10, 293302.
Gonen-Yaacovi, G., De Souza, L. C., Levy, R., Urbanski, M., Josse, G. & Volle, E. (2013). Rostral and caudal prefrontal contribution to creativity: a meta-analysis of functional imaging data. Frontiers in Human Neuroscience, 7, 465.
Gong, Q.-Y., Sluming, V., Mayes, A., Keller, S., Barrick, T., Cezayirli, E. & Roberts, N. (2005). Voxel-based morphometry and stereology provide convergent evidence of the importance of medial prefrontal cortex for fluid intelligence in healthy adults. Neuroimage, 25, 1175.
Gonzalez-Lima, F. & Barrett, D. W. (2014). Augmentation of cognitive brain functions with transcranial lasers. Frontiers in Systems Neuroscience, 8, 36.
Gottfredson, L. S. (1997a). Mainstream science on intelligence: an editorial with 52 signatories, history, and bibliography (reprinted from The Wall Street Journal, 1994). Intelligence, 24, 1323.
Gottfredson, L. S. (1997b). Why g matters: the complexity of everyday life. Intelligence, 24, 79132.
Gottfredson, L. S. (2002). Where and why g matters: not a mystery. Human Performance, 15, 2546.
Gottfredson, L. S. (2003a). Dissecting practical intelligence theory: its claims and evidence. Intelligence, 31, 343397.
Gottfredson, L. S. (2003b). g, jobs and life. In Nyborg, H. (Ed.), The Scientific Study of General Intelligence. New York, NY: Elsevier Science.
Gottfredson, L. S. (2005). Suppressing intelligence research: hurting those we intend to help. In Wright, R. C. & Cummings, N. A. (Eds.), Destructive Trends in Mental Health: The Well-intentioned Path to Harm. New York, NY: Routledge.
Gozli, D. G., Bavelier, D. & Pratt, J. (2014). The effect of action video game playing on sensorimotor learning: evidence from a movement tracking task. Human Movement Science, 38C, 152162.
Grabner, R. H. (2014). The role of intelligence for performance in the prototypical expertise domain of chess. Intelligence, 45, 2633.
Grabner, R. H., Stern, E. & Neubauer, A. C. (2007). Individual differences in chess expertise: a psychometric investigation. Acta Psychologica, 124, 398420.
Graham, S., Jiang, J., Manning, V., Nejad, A. B., Zhisheng, K., Salleh, S. R., Golay, X., Berne, Y. I. & McKenna, P. J. (2010). IQ-related fMRI differences during cognitive set shifting. Cerebral Cortex, 20, 641649.
Gray, J. R., Chabris, C. F. & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6, 316322.
Greely, H., Sahakian, B., Harris, J., Kessler, R. C., Gazzaniga, M., Campbell, P. & Farah, M. J. (2008). Towards responsible use of cognitive-enhancing drugs by the healthy. Nature, 456, 702705.
Green, A. E., Kraemer, D. J., Fugelsang, J. A., Gray, J. R. & Dunbar, K. N. (2012). Neural correlates of creativity in analogical reasoning. Journal of Experimental Psychology. Learning, Memory and Cognition, 38, 264272.
Gur, R. C., Ragland, J. D., Resnick, S. M., Skolnick, B. E., Jaggi, J., Muenz, L. & Gur, R. E. (1994). Lateralized increases in cerebral blood flow during performance of verbal and spatial tasks: relationship with performance-level. Brain and Cognition, 24, 244258.
Haasz, J., Westlye, E. T., Fjaer, S., Espeseth, T., Lundervold, A. & Lundervold, A. J. (2013). General fluid-type intelligence is related to indices of white matter structure in middle-aged and old adults. Neuroimage, 83, 372383.
Hackman, D. A., Farah, M. J. & Meaney, M. J. (2010). Socioeconomic status and the brain: mechanistic insights from human and animal research. Nature Reviews Neuroscience, 11, 651659.
Haggarty, P., Hoad, G., Harris, S. E., Starr, J. M., Fox, H. C., Deary, I. J. & Whalley, L. J. (2010). Human intelligence and polymorphisms in the DNA methyltransferase genes involved in epigenetic marking. PLoS ONE, 5, e11329.
Haier, R. J. (1990). The end of intelligence research. Intelligence, 14, 371374.
Haier, R. J. (2009a). Neuro-intelligence, neuro-metrics and the next phase of brain imaging studies. Intelligence, 37, 121123.
Haier, R. J. (2009b). What does a smart brain look like? Scientific American Mind, Nov/Dec, 2633.
Haier, R. J. (2013). The Intelligent Brain. The Great Courses Company.
Haier, R. J. (2014). Increased intelligence is a myth (so far). Frontiers in Systems Neuroscience, 8, 34.
Haier, R. J. & Benbow, C. P. (1995). Sex differences and lateralization in temporal lobe glucose metabolism during mathematical reasoning. Developmental Neuropsychology, 11, 405414.
Haier, R. J., Chueh, D., Touchette, P., Lott, I., et al. (1995) Brain size and cerebral glucose metabolic rate in nonspecific mental retardation and Down syndrome. Intelligence, 20, 191210.
Haier, R. J., Colom, R., Schroeder, D. H., Condon, C. A., Tang, C., Eaves, E. & Head, K. (2009). Gray matter and intelligence factors: is there a neuro-g? Intelligence, 37, 136144.
Haier, R. J., Jung, R. E., Yeo, R. A., Head, K. & Alkire, M. T. (2004). Structural brain variation and general intelligence. Neuroimage, 23, 425433.
Haier, R. J., Jung, R. E., Yeo, R. A., Head, K. & Alkire, M. T. (2005). The neuroanatomy of general intelligence: sex matters. Neuroimage, 25, 320327.
Haier, R. J. & Jung, R. E. (2007). Beautiful minds (i.e., brains) and the neural basis of intelligence. Behavioral and Brain Sciences, 30, 174178.
Haier, R. J. & Jung, R. E. (2008). Brain imaging studies of intelligence and creativity – what is the picture for education? Roeper Review, 30, 171180.
Haier, R. J., Robinson, D. L., Braden, W. & Williams, D. (1983). Electrical potentials of the cerebral cortex and psychometric intelligence. Personality & Individual Differences, 4, 591599.
Haier, R. J., Siegel, B., Tang, C., Abel, L. & Buchsbaum, M. S. (1992a). Intelligence and changes in regional cerebral glucose metabolic-rate following learning. Intelligence, 16, 415426.
Haier, R. J., Siegel, B. V., Jr., Crinella, F. M. & Buchsbaum, M. S. (1993). Biological and psychometric intelligence: testing an animal model in humans with positron emission tomography. In Douglas, Detterman, (Ed.), Individual Differences and Cognition. New York, NY: Ablex Publishing Corp.
Haier, R.J., Siegel, B.V., Jr., MacLachlan, A., Soderling, E., Lottenberg, S. & Buchsbaum, M. S. (1992b). Regional glucose metabolic changes after learning a complex visuospatial/motor task: a positron emission tomographic study. Brain Research, 570, 134143.
Haier, R. J., Siegel, B. V., Jr., Nuechterlein, K. H., Hazlett, E., Wu, J. C., Paek, J., Browning, H. L. & Buchsbaum, M. S. (1988). Cortical glucose metabolic rate correlates of abstract reasoning and attention studied with positron emission tomography. Intelligence, 12, 199217.
Haier, R. J., White, N. S. & Alkire, M. T. (2003). Individual differences in general intelligence correlate with brain function during nonreasoning tasks. Intelligence, 31, 429441.
Halpern, D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S. & Gernsbacher, M. A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest, 8, 151.
Halstead, W. C. (1947). Brain and Intelligence; A Quantitative Study of the Frontal Lobes, Chicago, IL: University of Chicago Press.
Hampshire, A., Thompson, R., Duncan, J. & Owen, A. M. (2011). Lateral prefrontal cortex subregions make dissociable contributions during fluid reasoning. Cerebral Cortex, 21, 110.
Hanscombe, K. B., Trzaskowski, M., Haworth, C. M. A., Davis, O. S. P., Dale, P. S. & Plomin, R. (2012). Socioeconomic status (SES) and children’s intelligence (IQ): in a UK-representative sample SES moderates the environmental, not genetic, effect on IQ. PloS ONE, 7, e30320.
Harrison, T. L., Shipstead, Z., Hicks, K. L., Hambrick, D. Z., Redick, T. S. & Engle, R. W. (2013). Working memory training may increase working memory capacity but not fluid intelligence. Psychological Science, 24, 24092419.
Hartshorne, J. K. & Germine, L. T. (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychological Science, 26, 433443.
Hawkins, J. & Blakeslee, S. (2004). On Intelligence, New York, NY: Times Books.
Haworth, C. M. A., Wright, M. J., Luciano, M., Martin, N. G., De Geus, E. J. C., Van Beijsterveldt, C. E. M., et al. (2010). The heritability of general cognitive ability increases linearly from childhood to young adulthood. Molecular Psychiatry, 15, 11121120.
Hayes, T. R., Petrov, A. A. & Sederberg, P. B. (2015). Do we really become smarter when our fluid-intelligence test scores improve? Intelligence, 48, 114.
Heishman, S. J., Kleykamp, B. A. & Singleton, E. G. (2010). Meta-analysis of the acute effects of nicotine and smoking on human performance. Psychopharmacology (Berlin), 210, 453469.
Herrnstein, R. J. (1973) I.Q. in the Meritocracy, Boston, MA: Little.
Herrnstein, R. J. & Murray, C. A. (1994). The Bell Curve: Intelligence and Class Structure in American Life, New York, NY: Free Press.
Heyward, F. D. & Sweatt, J. D. (2015). DNA methylation in memory formation: emerging insights. Neuroscientist, 24, 475489.
Hill, W. D., Davies, G., Van De Lagemaat, L. N., Christoforou, A., Marioni, R. E., Fernandes, C. P., et al. (2014). Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins. Translational Psychiatry, 4, e341.
Hines, T. (1998). Further on Einstein’s brain. Experimental Neurology, 150, 343344.
Hopkins, W. D., Russe, J. L. & Schaeffer, J. (2014). Chimpanzee intelligence is heritable. Current Biology, 24, 16491652.
Horvath, J. C., Forte, J. D. & Carter, O. (2015a). Evidence that transcranial direct current stimulation (tDCS) generates little-to-no reliable neurophysiologic effect beyond MEP amplitude modulation in healthy human subjects: a systematic review. Neuropsychologia, 66, 213236.
Horvath, J. C., Forte, J. D. (2015b). Quantitative review finds no evidence of cognitive effects in healthy populations from single-session transcranial direct current stimulation (tDCS). Brain Stimulation, 8, 535550.
Howard-Jones, P. A. (2014). Neuroscience and education: myths and messages. Nature Reviews Neuroscience, 15, 817824.
Hulshoff Pol, H. E., Schnack, H. G., Posthuma, D., Mandl, R. C. W., Baare, W. F., Van Oel, C., et al. (2006). Genetic contributions to human brain morphology and intelligence. Journal of Neuroscience, 26, 1023510242.
Hunt, E. B. (2011). Human Intelligence, Cambridge: Cambridge University Press.
Husain, M. & Mehta, M. A. (2011). Cognitive enhancement by drugs in health and disease. Trends in Cognitive Sciences, 15, 2836.
Huttenlocher, P. R. (1975). Synaptic and dendritic development and mental defect. In N. A. Buchwald & M. A. B. Brazier (Eds.), Brain Mechanisms in Mental Retardation: UCLA Forum in Medical Science, Number 18, 4th Edition, New York, NY: Academic Press.
Ilieva, I. P. & Farah, M. J. (2013). Enhancement stimulants: perceived motivational and cognitive advantages. Frontiers in Neuroscience, 7, 198.
Jacobs, B., Schall, M. & Scheibel, A. B. (1993). A quantitative dendritic analysis of Wernicke’s area in humans. II. Gender, hemispheric, and environmental factors. Journal of Comparative Neurology, 327, 97111.
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, 68296833.
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, 1008110086.
Jaeggi, S. M., Buschkuehl, M., Shah, P. & Jonides, J. (2014). The role of individual differences in cognitive training and transfer. Memory and Cognition, 42, 464480.
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, 625635.
Jaenisch, R. & Bird, A. (2003). Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature Genetics, 33(Suppl), 245254.
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, 312320.
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, 1123.
Jensen, A. R. (1974). Kinship correlations reported by Sir Cyril Burt. Behavior Genetics, 4, 128.
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, 223232.
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, 393416.
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, 95107.
Johnson, W., Jung, R. E., Colom, R. & Haier, R. J. (2008a). Cognitive abilities independent of IQ correlate with regional brain structure. Intelligence, 36, 1828.
Johnson, W., Te Nijenhuis, J. & Bouchard, T. J. (2008b). Still just 1 g: consistent results from five test batteries. Intelligence, 36, 8195.
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, 13751379.
Jung, R. E. & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and Brain Sciences, 30, 135154.
Jung, R. E. & Haier, R. J. (2013). Creativity and intelligence: brain networks that link and differentiate the expression of genius. In Vartanian, O., Bristol, A. S. & Kaufman, J. C., (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, 965972.
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, 33273331.
Kanai, R. & Rees, G. (2011). The structural basis of inter-individual differences in human behaviour and cognition. Nature Reviews Neuroscience, 12, 231242.
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, 637671.
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, 6671.
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, 145155.
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, 14431453.
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, 46124617.
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, 6787.
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, 8997.
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), 550556.
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, 49384953.
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, 20122019.
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, 198203.
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, 1185011857.
Kuhl, P. K. (2004). Early language acquisition: cracking the speech code. Nature Reviews Neuroscience, 5, 831843.
Kyllonen, P. C. & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity. Intelligence, 14, 389433.
Langer, N., Pedroni, A., Gianotti, L. R., Hanggi, J., Knoch, D. & Jancke, L. (2012). Functional brain network efficiency predicts intelligence. Human Brain Mapping, 33, 13931406.
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, 247255.
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, 578586.
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, 10621067.
Lerner, B. (1980). The war on testing – Detroit Edison in perspective. Personnel Psychology, 33, 1116.
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, 12851292.
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), 961970.
Lubinski, D. (2009). Cognitive epidemiology: with emphasis on untangling cognitive ability and socioeconomic status. Intelligence, 37, 625633.
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, 22172232.
Lubinski, D., Benbow, C. P., Webb, R. M. & Bleske-Rechek, A. (2006). Tracking exceptional human capital over two decades. Psychological Science, 17, 194199.
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, 443451.
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, 581592.
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, 314324.
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, 14571464.
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, 799800.
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, 527534.
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, 925933.
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, 582590.
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, 9095.
Maher, B. (2008). Poll results: look who’s doping. Nature, 452, 674675.
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, 8894.
Mardis, E. R. (2008). Next-generation DNA sequencing methods. Annual Review of Genomics and Humam Genetics, 9, 387402.
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, 2632.
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, 64236433.
Matzel, L. D. & Kolata, S. (2010). Selective attention, working memory, and animal intelligence. Neuroscience and Biobehavioral Reviews, 34, 2330.
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, 342348.
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, 167176.
McDaniel, M. A. (2005). Big-brained people are smarter: a meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33, 337346.
McGue, M., Bouchard, T. J., Iacono, W. G. & Lykken, D. T. (1993). Age effects on heritability of intelligence. In Plomin, R. & McClearn, G. E. (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, 129137.
Melby-Lervag, M. & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49, 270291.
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, 458463.
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, 978982.
Moody, D. E. (2009). Can intelligence be increased by training on a task of working memory? Intelligence, 37, 327328.
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, 119128.
Murray, C. (1995). The bell curve and its critics. Commentary, 99, 2330.
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, 490498.
Muzur, A., Pace-Schott, E. F. & Hobson, J. A. (2002). The prefrontal cortex in sleep. Trends in Cognitive Science, 6, 475481.
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, 77101.
Neubauer, A. C. & Fink, A. (2009). Intelligence and neural efficiency. Neuroscience and Biobehavioral Reviews, 33, 10041023.
Neville, H., Stevens, C., Pakulak, E. & Bell, T. A. (2013). Commentary: neurocognitive consequences of socioeconomic disparities. Developmental Science, 16, 708712.
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, 755760.
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, 130159.
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, 773778.
Pahor, A. & Jausovec, N. (2014). The effects of theta transcranial alternating current stimulation (tACS) on fluid intelligence. International Journal of Psychophysiology, 93, 322331.
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, 6576.
Parasuraman, R. & Jiang, Y. (2012). Individual differences in cognition, affect, and performance: behavioral, neuroimaging, and molecular genetic approaches. Neuroimage, 59, 7082.
Parks, R. W., Loewenstein, D. A., Dodrill, K. L., Barker, W. W., Yoshii, F., Chang, J. Y., Emran, A., Apicella, A., Sheramata, W. A. & Duara, R. (1988). Cerebral metabolic effects of a verbal fluency test – a PET scan study. Journal of Clinical and Experimental Neuropsychology, 10, 565575.
Pascoli, V., Turiault, M. & Luscher, C. (2012). Reversal of cocaine-evoked synaptic potentiation resets drug-induced adaptive behaviour. Nature, 481, 7175.
Pedersen, N. L., Plomin, R., Nesselroade, J. R. & McClearn, G. E. (1992). A quantitative genetic analysis of cognitive abilities during the 2nd half of the life span. Psychological Science, 3, 346353.
Penke, L., Maniega, S. M., Bastin, M. E., Hernandez, M. C. V., Murray, C., Royle, N. A., Starr, J. M., Wardlaw, J. M. & Deary, I. J. (2012). Brain white matter tract integrity as a neural foundation for general intelligence. Molecular Psychiatry, 17, 10261030.
Perfetti, B., Saggino, A., Ferretti, A., Caulo, M., Romani, G. L. & Onofrj, M. (2009). Differential patterns of cortical activation as a function of fluid reasoning complexity. Human Brain Mapping, 30, 497510.
Perobelli, S., Alessandrini, F., Zoccatelli, G., Nicolis, E., Beltramello, A., Assael, B. M. & Cipolli, M. (2015). Diffuse alterations in grey and white matter associated with cognitive impairment in Shwachman–Diamond syndrome: evidence from a multimodal approach. Neuroimage Clinics, 7, 721731.
Pesenti, M., Zago, L., Crivello, F., Mellet, E., Samson, D., Duroux, B., Seron, X., Mazoyer, B. & Tzourio-Mazoyer, N. (2001). Mental calculation in a prodigy is sustained by right prefrontal and medial temporal areas. Nature Neuroscience, 4, 103107.
Petrill, S. A. & Deater-Deckard, K. (2004). The heritability of general cognitive ability: a within-family adoption design. Intelligence, 32, 403409.
Pfleiderer, B., Ohrmann, P., Suslow, T., Wolgast, M., Gerlach, A. L., Heindel, W. & Michael, N. (2004). N-acetylaspartate levels of left frontal cortex are associated with verbal intelligence in women but not in men: a proton magnetic resonance spectroscopy study. Neuroscience, 123, 10531058.
Pietschnig, J., Voracek, M. & Formann, A. K. (2010). Mozart effect–Shmozart effect: a meta-analysis. Intelligence, 38, 314323.
Pineda-Pardo, J. A., Bruna, R., Woolrich, M., Marcos, A., Nobre, A. C., Maestu, F. & Vidaurre, D. (2014). Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of conditions of mild cognitive impairment. Neuroimage, 101, 765777.
Pinho, A. L., De Manzano, O., Fransson, P., Eriksson, H. & Ullen, F. (2014). Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. Journal of Neuroscience, 34, 61566163.
Pinker, S. (2002). The Blank Slate: The Modern Denial of Human Nature, New York, NY: Viking.
Plis, S. M., Weisend, M. P., Damaraju, E., Eichele, T., Mayer, A., Clark, V. P., Lane, T. & Calhoun, V. D. (2011). Effective connectivity analysis of fMRI and MEG data collected under identical paradigms. Computers in Biology and Medicine, 41, 11561165.
Plomin, R. (1999). Genetics and general cognitive ability. Nature, 402, C25C29.
Plomin, R. & Deary, I. J. (2015). Genetics and intelligence differences: five special findings. Molecular Psychiatry, 20, 98108.
Plomin, R. & Kosslyn, S. M. (2001). Genes, brain and cognition. Nature Neuroscience, 4, 11531154.
Plomin, R. & Petrill, S. A. (1997). Genetics and intelligence: what’s new? Intelligence, 24, 5377.
Plomin, R., Shakeshaft, N. G., McMillan, A. & Trzaskowski, M. (2014a). Nature, nurture, and expertise. Intelligence, 45, 4659.
Plomin, R., Shakeshaft, N. G., McMillan, A. & Trzaskowski, M. (2014b). Nature, nurture, and expertise: response to Ericsson. Intelligence, 45, 115117.
Pol, H. E. H., Posthuma, D., Baare, W. F. C., De Geus, E. J. C., Schnack, H. G., Van Haren, N. E. M., Van Oel, C. J., Kahn, R. S. & Boomsma, D. I. (2002). Twin–singleton differences in brain structure using structural equation modelling. Brain, 125, 384390.
Polderman, T. J., Benyamin, B., De Leeuw, C. A., Sullivan, P. F., Van Bochoven, A., Visscher, P. M. & Posthuma, D. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47, 702709.
Poldrack, R. A. (2015). Is “efficiency” a useful concept in cognitive neuroscience? Developmental and Cognitive Neuroscience, 11, 1217.
Posthuma, D., Baare, W. F. C., Pol, H. E. H., Kahn, R. S., Boomsma, D. I. & De Geus, E. J. C. (2003a). Genetic correlations between brain volumes and the WAIS-III dimensions of verbal comprehension, working memory, perceptual organization, and processing speed. Twin Research, 6, 131139.
Posthuma, D., De Geus, E. & Boomsma, D. (2003b). Genetic contributions to anatomical, behavioral, and neurophysiological indices of cognition. In Plomin, R., Defries, J., Craig, I. W. & McGuffin, P. (Eds.), Behavioral Genetics in the Postgenomic Era, Washington, DC: American Psychological Association.
Posthuma, D., De Geus, E. J., Baare, W. F., Hulshoff Pol, H. E., Kahn, R. S. & Boomsma, D. I. (2002). The association between brain volume and intelligence is of genetic origin. Nature Neuroscience, 5, 8384.
Posthuma, D. & De Geus, E. J. C. (2006). Progress in the molecular-genetic study of intelligence. Current Directions in Psychological Science, 15, 151155.
Prabhakaran, V., Smith, J. A., Desmond, J. E., Glover, G. H. & Gabrieli, J. D. (1997). Neural substrates of fluid reasoning: an fMRI study of neocortical activation during performance of the Raven’s Progressive Matrices Test. Cognitive Psychology, 33, 4363.
Prat, C. S., Mason, R. A. & Just, M. A. (2012). An fMRI investigation of analogical mapping in metaphor comprehension: the influence of context and individual cognitive capacities on processing demands. Journal of Experimental Psychology, Learning, Memory and Cognition, 38, 282294.
Preusse, F., Van Der Meer, E., Deshpande, G., Krueger, F. & Wartenburger, I. (2011). Frontiers: fluid intelligence allows flexible recruitment of the parieto-frontal network in analogical reasoning. Frontiers in Human Neuroscience, 5, 22.
Protzko, J., Aronson, J. & Blair, C. (2013). How to make a young child smarter: evidence from the database of raising intelligence. Perspectives on Psychological Science, 8, 2540.
Ramey, C. T. & Ramey, S. L. (2004). Early learning and school readiness: can early intervention make a difference? Merrill-Palmer Quarterly Journal of Developmental Psychology, 50, 471491.
Rankin, K. P., Liu, A. A., Howard, S., Slama, H., Hou, C. E., Shuster, K. & Miller, B. L. (2007). A case-controlled study of altered visual art production in Alzheimer’s and FTLD. Cognitive and Behavioral Neurology, 20, 4861.
Rauscher, F. H., Shaw, G. L. & Ky, K. N. (1993). Music and spatial task performance. Nature, 365, 611.
Redick, T. S. (2015). Working memory training and interpreting interactions in intelligence interventions. Intelligence, 50, 1420.
Redick, T. S., Shipstead, Z., Harrison, T. L., Hicks, K. L., Fried, D. E., Hambrick, D. Z., Kane, M. J. & Engle, R. W. (2013). No evidence of intelligence improvement after working memory training: a randomized, placebo-controlled study. Journal of Experimental Psychology – General, 142, 359379.
Ree, M. J. & Carretta, T. R. (1996). Central role of g in military pilot selection. International Journal of Aviation Psychology, 6, 111123.
Ree, M. J. & Earles, J. A. (1991). Predicting training success – not much more than g. Personnel Psychology, 44, 321332.
Reijneveld, J. C., Ponten, S. C., Berendse, H. W. & Stam, C. J. (2007). The application of graph theoretical analysis to complex networks in the brain. Clinical Neurophysiology, 118, 23172331.
Reverberi, C., Bonatti, L. L., Frackowiak, R. S., Paulesu, E., Cherubini, P. & Macaluso, E. (2012). Large scale brain activations predict reasoning profiles. Neuroimage, 59, 17521764.
Rhein, C., Muhle, C., Richter-Schmidinger, T., Alexopoulos, P., Doerfler, A. & Kornhuber, J. (2014). Neuroanatomical correlates of intelligence in healthy young adults: the role of basal ganglia volume. PLoS ONE, 9, e93623.
Ridley, M. (2003). Nature Via Nurture: Genes, Experience and What Makes Us Human, London: Fourth Estate.
Rietveld, C. A., Esko, T., Davies, G., Pers, T. H., Turley, P., Benyamin, B., et al. (2014). Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proceedings of the National Academy of Sciences of the United States of America, 111, 1379013794.
Ritchie, S. J., Booth, T., Valdés Hernández, M. D. C., Corley, J., Maniega, S. M., Gow, A. J., et al. (2015). Beyond a bigger brain: multivariable structural brain imaging and intelligence. Intelligence, 51, 4756.
Robertson, K. F., Smeets, S., Lubinski, D. & Benbow, C. P. (2010). Beyond the threshold hypothesis: even among the gifted and top math/science graduate students, cognitive abilities, vocational interests, and lifestyle preferences matter for career choice, performance, and persistence. Current Directions in Psychological Science, 19, 346351.
Sackett, P. R., Kuncel, N. R., Arneson, J. J., Cooper, S. R. & Waters, S. D. (2009). Does socioeconomic status explain the relationship between admissions tests and post-secondary academic performance? Psychological Bulletin, 135, 122.
Sahakian, B. & Morein-Zamir, S. (2007). Professor’s little helper. Nature, 450, 11571159.
Sander, J. D. & Joung, J. K. (2014). CRISPR-Cas systems for genome editing, regulation and targeting. Nature Biotechnology, 32, 347355.
Santarnecchi, E., Galli, G., Polizzotto, N. R., Rossi, A. & Rossi, S. (2014). Efficiency of weak brain connections support general cognitive functioning. Human Brain Mapping, 35, 45664582.
Santarnecchi, E., Polizzotto, N. R., Godone, M., Giovannelli, F., Feurra, M., Matzen, L., Rossi, A. & Rossi, S. (2013). Frequency-dependent enhancement of fluid intelligence induced by transcranial oscillatory potentials. Current Biology, 23, 14491453.
Santarnecchi, E., Rossi, S. & Rossi, A. (2015a). The smarter, the stronger: intelligence level correlates with brain resilience to systematic insults. Cortex, 64, 293309.
Santarnecchi, E., Tatti, E., Rossi, S., Serino, V. & Rossi, A. (2015b). Intelligence-related differences in the asymmetry of spontaneous cerebral activity. Human Brain Mapping, 36, 35863602.
Sauce, B. & Matzel, L. D. (2013). The causes of variation in learning and behavior: why individual differences matter. Frontiers in Psychology, 4, 395.
Sawyer, K. (2011). The cognitive neuroscience of creativity: a critical review. Creativity Research Journal, 23, 137154.
Schmidt, F. L. & Hunter, J. (2004). General mental ability in the world of work: occupational attainment and job performance. Journal of Personality and Social Psychology, 86, 162173.
Schmidt, F. L. & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262274.
Schmithorst, V. J. & Holland, S. K. (2006). Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls. Neuroimage, 31, 13661379.
Schmithorst, V. J., Wilke, M., Dardzinski, B. J. & Holland, S. K. (2005). Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MRI study. Human Brain Mapping, 26, 139147.
Schwaighofer, M., Fischer, F. & Buhner, M. (2015). Does working memory training transfer? A meta-analysis including training conditions as moderators. Educational Psychologist, 50, 138166.
Sellers, K. K., Mellin, J. M., Lustenberger, C. M., Boyle, M. R., Lee, W. H., Peterchev, A. V. & Frohlich, F. (2015). Transcranial direct current stimulation (tDCS) of frontal cortex decreases performance on the WAIS-IV intelligence test. Behavior and Brain Research, 290, 3244.
Shakeshaft, N. G., Trzaskowski, M., McMillan, A., Krapohl, E., Simpson, M. A., Reichenberg, A., Cederlof, M., Larsson, H., Lichtenstein, P. & Plomin, R. (2015). Thinking positively: the genetics of high intelligence. Intelligence, 48, 123132.
Shamay-Tsoory, S. G., Adler, N., Aharon-Peretz, J., Perry, D. & Mayseless, N. (2011). The origins of originality: the neural bases of creative thinking and originality. Neuropsychologia, 49, 178185.
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J. & Giedd, J. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440, 676679.
Shehzad, Z., Kelly, C., Reiss, P. T., Cameron Craddock, R., Emerson, J. W., McMahon, K., Copland, D. A., Castellanos, F. X. & Milham, M. P. (2014). A multivariate distance-based analytic framework for connectome-wide association studies. Neuroimage, 93(Pt 1), 7494.
Shipstead, Z., Redick, T. S. & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138, 628654.
Shonkoff, J. P., Phillips, D. & National Research Council (U.S.). Committee On Integrating The Science Of Early Childhood Development. (2000). From Neurons to Neighborhoods: The Science of Early Childhood Development, Washington, DC: National Academy Press.
Sigala, N. (2015). Effects of memory training or task design? A commentary on “Neural evidence for the use of digit-image mnemonic in a superior memorist: an fMRI study”. Frontiers in Human Neuroscience, 9, 183.
Sigman, M., Pena, M., Goldin, A. P. & Ribeiro, S. (2014). Neuroscience and education: prime time to build the bridge. Nature Neuroscience, 17, 497502.
Silverman, P. H. (2004). Rethinking genetic determinism. The Scientist, 18, 3233.
Simos, P. G., Rezaie, R., Papanicolaou, A. C. & Fletcher, J. M. (2014). Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study. Frontiers in Human Neuroscience, 7, 932.
Smith, M. E. & Farah, M. J. (2011). Are prescription stimulants “smart pills”? The epidemiology and cognitive neuroscience of prescription stimulant use by normal healthy individuals. Psychological Bulletin, 137, 717741.
Smith, S. M., Nichols, T. E., Vidaurre, D., Winkler, A. M., Behrens, T. E. J., Glasser, M. F., Ugurbil, K., Barch, D. M., Van Essen, D. C. & Miller, K. L. (2015). A positive–negative mode of population covariation links brain connectivity, demographics and behavior. Nature Neuroscience, 18, 15651567.
Snyderman, M. & Rothman, S. (1988). The IQ Controversy, The Media and Public Policy, New Brunswick, NJ: Transaction Books.
Song, M., Liu, Y., Zhou, Y., Wang, K., Yu, C. & Jiang, T. (2009). Default network and intelligence difference. Conference Proceedings of the IEEE Engineering in Medicine and Biology Society, 2009, 22122215.
Song, M., Zhou, Y., Li, J., Liu, Y., Tian, L., Yu, C. & Jiang, T. (2008). Brain spontaneous functional connectivity and intelligence. Neuroimage, 41, 11681176.
Spearman, C. (1904). General intelligence objectively determined and measured. American Journal of Psychology, 15, 201293.
Stam, C. J. & Reijneveld, J. C. (2007). Graph theoretical analysis of complex networks in the brain. Nonlinear Biomedical Physics, 1, 3.
Stanley, J., Keating, D. & Fox, L. H. (1974). Mathematical Talent: Discovery, Description, and Development, Baltimore, MD: The Johns Hopkins University Press.
Stein, J. L., Medland, S. E., Vasquez, A. A., Hibar, D. P., Senstad, R. E., Winkler, A. M., et al. (2012). Identification of common variants associated with human hippocampal and intracranial volumes. Nature Genetics, 44, 552561.
Sternberg, R. J. (2000). Practical Intelligence in Everyday Life, Cambridge: Cambridge University Press.
Sternberg, R. J. (2003). Our research program validating the triarchic theory of successful intelligence: reply to Gottfredson. Intelligence, 31, 399413.
Sternberg, R. J. (2008). Increasing fluid intelligence is possible after all. Proceedings of the National Academy of Sciences of the United States of America, 105, 67916792.
Strenze, T. (2007) Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence, 35, 401426.
Suthana, N. & Fried, I. (2014). Deep brain stimulation for enhancement of learning and memory. Neuroimage, 85(Pt 3), 9961002.
Tammet, D. (2007). Born on a Blue Day: Inside the Extraordinary Mind of an Autistic Savant: A Memoir, New York, NY: Free Press.
Tang, C. Y., Eaves, E. L., Ng, J. C., Carpenter, D. M., Mai, X., Schroeder, D. H., Condon, C. A., Colom, R. & Haier, R. J. (2010). Brain networks for working memory and factors of intelligence assessed in males and females with fMRI and DTI. Intelligence, 38, 293303.
Tang, Y. P., Shimizu, E., Dube, G. R., Rampon, C., Kerchner, G. A., Zhuo, M., Liu, G. S. & Tsien, J. Z. (1999). Genetic enhancement of learning and memory in mice. Nature, 401, 6369.
Te Nijenhuis, J., Jongeneel-Grimen, B. & Kirkegaard, E. O. W. (2014). Are Headstart gains on the g factor? A meta-analysis. Intelligence, 46, 209215.
Te Nijenhuis, J. & Van Der Flier, H. (2013). Is the Flynn effect on g? A meta-analysis. Intelligence, 41, 802807.
Terman, L. M. (1925). Genetic Studies of Genius, Stanford, CA: Stanford University Press.
Terman, L. M. (1954) Scientists and Nonscientists in a Group of 800 Gifted Men, Washington, DC: American Psychological Association.
Thoma, R. J., Yeo, R. A., Gangestad, S., Halgren, E., Davis, J., Paulson, K. M. & Lewine, J. D. (2006). Developmental instability and the neural dynamics of the speed–intelligence relationship. Neuroimage, 32, 14561464.
Thomas, P., Rammsayer, T., Schweizer, K. & Troche, S. (2015). Elucidating the functional relationship between working memory capacity and psychometric intelligence: a fixed-links modeling approach for experimental repeated-measures designs. Advances in Cognitive Psychology, 11, 313.
Thompson, P. M., Cannon, T. D., Narr, K. L., Van Erp, T., Poutanen, V. P., Huttunen, M., Lonnqvist, J., Standertskjold-Nordenstam, C. G., Kaprio, J., Khaledy, M., Dail, R., Zoumalan, C. I. & Toga, A. W. (2001). Genetic influences on brain structure. Nature Neuroscience, 4, 12531258.
Thompson, R., Crinella, F. M. & Yu, J. (1990). Brain Mechanisms in Problem Solving and Intelligence: A Survey of the Rat Brain, New York, NY: Plenum Press.
Thompson, T. W., Waskom, M. L., Garel, K. L., Cardenas-Iniguez, C., Reynolds, G. O., Winter, R., Chang, P., Pollard, K., Lala, N., Alvarez, G. A. & Gabrieli, J. D. (2013). Failure of working memory training to enhance cognition or intelligence. PLoS ONE, 8, e63614.
Thurstone, L. L. (1938). Primary Mental Abilities, Chicago, IL: University of Chicago Press.
Thurstone, L. L. & Thurstone, T. (1941). Factorial Studies of Intelligence, Chicago, IL: University of Chicago Press.
Tidwell, J. W., Dougherty, M. R., Chrabaszcz, J. R., Thomas, R. P. & Mendoza, J. L. (2014). What counts as evidence for working memory training? Problems with correlated gains and dichotomization. Psychonomic Bulletin and Review, 21, 620628.
Toga, A. W. & Thompson, P. M. (2005). Genetics of brain structure and intelligence. Annual Review of Neuroscience, 28, 123.
Tommasi, M., Pezzuti, L., Colom, R., Abad, F. J., Saggino, A. & Orsini, A. (2015). Increased educational level is related with higher IQ scores but lower g-variance: evidence from the standardization of the WAIS-R for Italy. Intelligence, 50, 6874.
Trahan, L. H., Stuebing, K. K., Fletcher, J. M. & Hiscock, M. (2014). The Flynn effect: a meta-analysis. Psychological Bulletin, 140, 13321360.
Trzaskowski, M., Davis, O. S. P., Defries, J. C., Yang, J., Visscher, P. M. & Plomin, R. (2013a). DNA evidence for strong genome-wide pleiotropy of cognitive and learning abilities. Behavior Genetics, 43, 267273.
Trzaskowski, M., Harlaar, N., Arden, R., Krapohl, E., Rimfeld, K., McMillan, A., Dale, P. S. & Plomin, R. (2014). Genetic influence on family socioeconomic status and children’s intelligence. Intelligence, 42, 8388.
Trzaskowski, M., Shakeshaft, N. G. & Plomin, R. (2013b). Intelligence indexes generalist genes for cognitive abilities. Intelligence, 41, 560565.
Turkheimer, E. (2000). Three laws of behavior genetics and what they mean. Current Directions in Psychological Science, 9, 160164.
Turkheimer, E., Haley, A., Waldron, M., D’Onofrio, B. & Gottesman, I. I. (2003). Socioeconomic status modifies heritability of IQ in young children. Psychological Sciences, 14, 623628.
Ukkola-Vuoti, L., Kanduri, C., Oikkonen, J., Buck, G., Blancher, C., Raijas, P., Karma, K., Lahdesmaki, H. & Jarvela, I. (2013). Genome-wide copy number variation analysis in extended families and unrelated individuals characterized for musical aptitude and creativity in music. PLoS ONE, 8, e56356.
Unsworth, N., Redick, T. S., McMillan, B. D., Hambrick, D. Z., Kane, M. J. & Engle, R. W. (2015). Is playing video games related to cognitive abilities? Psychological Sciences, 26, 759774.
Urban, D. J. & Roth, B. L. (2015). DREADDs (designer receptors exclusively activated by designer drugs): chemogenetic tools with therapeutic utility. Annual Review of Pharmacology and Toxicology, 55, 399417.
Utz, K. S., Dimova, V., Oppenlander, K. & Kerkhoff, G. (2010). Electrified minds: transcranial direct current stimulation (tDCS) and galvanic vestibular stimulation (GVS) as methods of non-invasive brain stimulation in neuropsychology – a review of current data and future implications. Neuropsychologia, 48, 27892810.
Vakhtin, A. A., Ryman, S. G., Flores, R. A. & Jung, R. E. (2014). Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence. Neuroimage, 103, 349354.
Van Den Heuvel, M. P., Kahn, R. S., Goni, J. & Sporns, O. (2012). High-cost, high-capacity backbone for global brain communication. Proceedings of the National Academy of Sciences of the United States of America, 109, 1137211377.
Van Den Heuvel, M. P. & Sporns, O. (2011). Rich-club organization of the human connectome. Journal of Neuroscience, 31, 1577515786.
Van Den Heuvel, M. P., Stam, C. J., Kahn, R. S. & Pol, H. E. (2009). Efficiency of functional brain networks and intellectual performance. Journal of Neuroscience, 29, 76197624.
Van Der Sluis, S., Willemsen, G., De Geus, E. J. C., Boomsma, D. I. & Posthuma, D. (2008). Gene–environment interaction in adults’ IQ scores: measures of past and present environment. Behavior Genetics, 38, 348360.
Van Leeuwen, M., Van Den Berg, S. M. & Boomsma, D. I. (2008). A twin-family study of general IQ. Learning and Individual Differences, 18, 7688.
Vardy, E., Robinson, J. E., Li, C., Olsen, R. H., Diberto, J. F., Giguere, P. M., et al. (2015). A new DREADD facilitates the multiplexed chemogenetic interrogation of behavior. Neuron, 86, 936946.
Vendetti, M. S. & Bunge, S. A. (2014). Evolutionary and developmental changes in the lateral frontoparietal network: a little goes a long way for higher-level cognition. Neuron, 84, 906917.
Vernon, P. A. (1983). Speed of information processing and general intelligence. Intelligence, 7, 5370.
Villarreal, M. F., Cerquetti, D., Caruso, S., Schwarcz Lopez Aranguren, V., Gerschcovich, E. R., Frega, A. L. & Leiguarda, R. C. (2013). Neural correlates of musical creativity: differences between high and low creative subjects. PLoS ONE, 8, e75427.
Von Bastian, C. C. & Oberauer, K. (2013). Distinct transfer effects of training different facets of working memory capacity. Journal of Memory and Language, 69, 3658.
Von Bastian, C. C. & Oberauer, K. (2014). Effects and mechanisms of working memory training: a review. Psychological Research – Psychologische Forschung, 78, 803820.
Von Stumm, S. & Deary, I. J. (2013). Intellect and cognitive performance in the Lothian Birth Cohort 1936. Psychology and Aging, 28, 680684.
Vuoksimaa, E., Panizzon, M. S., Chen, C. H., Fiecas, M., Eyler, L. T., Fennema-Notestine, C., et al. (2015). The genetic association between neocortical volume and general cognitive ability is driven by global surface area rather than thickness. Cerebral Cortex, 25, 21272137.
Wagner, T., Robaa, D., Sippl, W. & Jung, M. (2014). Mind the methyl: methyllysine binding proteins in epigenetic regulation. ChemMedChem, 9, 466483.
Wai, J., Lubinski, D. & Benbow, C. P. (2005). Creativity and occupational accomplishments among intellectually precocious youths: an age 13 to age 33 longitudinal study. Journal of Educational Psychology, 97, 484492.
Walfisch, A., Sermer, C., Cressman, A. & Koren, G. (2013). Breast milk and cognitive development – the role of confounders: a systematic review. BMJ Open, 3, e003259.
Wang, L., Wee, C. Y., Suk, H. I., Tang, X. & Shen, D. (2015). MRI-based intelligence quotient (IQ) estimation with sparse learning. PLoS ONE, 10, e0117295.
Waterhouse, L. (2006). Inadequate evidence for multiple intelligences, Mozart effect, and emotional intelligence theories. Educational Psychologist, 41, 247255.
Watson, J. B. (1930). Behaviorism, New York, NY: W.W. Norton & Company.
Weiss, D., Haier, R. & Keating, D. (1974). Personality characteristics of mathematically precocious boys. In Stanley, J. & Keating, D. (Eds.), Mathematical Talent: Discovery, Description, and Development. Baltimore, MD: The Johns Hopkins University Press.
Wendelken, C., Ferrer, E., Whitaker, K. J. & Bunge, S. A. (2016). Fronto-parietal network reconfiguration supports the development of reasoning ability. Cerebral Cortex, 26, 21782190.
Whalley, L. J. & Deary, I. J. (2001). Longitudinal cohort study of childhood IQ and survival up to age 76. British Medical Journal, 322, 819.
Wharton, C. M., Grafman, J., Flitman, S. S., Hansen, E. K., Brauner, J., Marks, A. & Honda, M. (2000). Toward neuroanatomical models of analogy: a positron emission tomography study of analogical mapping. Cognitive Psychology, 40, 173197.
Wilke, M., Sohn, J. H., Byars, A. W. & Holland, S. K. (2003). Bright spots: correlations of gray matter volume with IQ in a normal pediatric population. Neuroimage, 20, 202215.
Willerman, L., Schultz, R., Rutledge, J. N. & Bigler, E. D. (1991). In vivo brain size and intelligence. Intelligence, 15, 223228.
Wilson, E. O. (1975). Sociobiology; The New Synthesis, Cambridge, MA: Belknap Press of Harvard University Press.
Witelson, S. F., Beresh, H. & Kigar, D. L. (2006). Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. Brain, 129, 386398.
Witelson, S. F., Kigar, D. L. & Harvey, T. (1999). Albert Einstein’s brain – Reply. Lancet, 354, 1822.
Witelson, S. F., Kigar, D. L. & Harvey, T. (1999). The exceptional brain of Albert Einstein. Lancet, 353, 21492153.
Wolff, S. B., Grundemann, J., Tovote, P., Krabbe, S., Jacobson, G. A., Muller, C., Herry, C., Ehrlich, I., Friedrich, R. W., Letzkus, J. J. & Luthi, A. (2014). Amygdala interneuron subtypes control fear learning through disinhibition. Nature, 509, 453458.
Wu, X., Yang, W., Tong, D., Sun, J., Chen, Q., Wei, D., Zhang, Q., Zhang, M. & Qiu, J. (2015). A meta-analysis of neuroimaging studies on divergent thinking using activation likelihood estimation. Human Brain Mapping, 36, 27032718.
Yang, J. J., Yoon, U., Yun, H. J., Im, K., Choi, Y. Y., Lee, K. H., Park, H., Hough, M. G. & Lee, J. M. (2013). Prediction for human intelligence using morphometric characteristics of cortical surface: partial least square analysis. Neuroscience, 246, 351361.
Yin, L. J., Lou, Y. T., Fan, M. X., Wang, Z. X. & Hu, Y. (2015). Neural evidence for the use of digit-image mnemonic in a superior memorist: an fMRI study. Frontiers in Human Neuroscience, 9, 109.
Yu, C. C., Furukawa, M., Kobayashi, K., Shikishima, C., Cha, P. C., Sese, J., Sugawara, H., Iwamoto, K., Kato, T., Ando, J. & Toda, T. (2012). Genome-wide DNA methylation and gene expression analyses of monozygotic twins discordant for intelligence levels. Plos One, 7, e47081.
Zhao, M., Kong, L. & Qu, H. (2014). A systems biology approach to identify intelligence quotient score-related genomic regions, and pathways relevant to potential therapeutic treatments. Science Reports, 4, 4176.

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Book summary page views

Total views: 0 *
Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed.