Behavior Genetics

, Volume 39, Issue 4, pp 350–358 | Cite as

Exceptional Cognitive Ability: The Phenotype

  • David LubinskiEmail author
Original Research


Characterizing the outcomes related to the phenotype of exceptional cognitive abilities has been feasible in recent years due to the availability of large samples of intellectually precocious adolescents identified by modern talent searches that have been followed-up longitudinally over multiple decades. The level and pattern of cognitive abilities, even among participants within the top 1% of general intellectual ability, are related to differential developmental trajectories and important life accomplishments: The likelihood of earning a doctorate, earning exceptional compensation, publishing novels, securing patents, and earning tenure at a top university (and the academic disciplines within which tenure is most likely to occur) all vary as a function of individual differences in cognitive abilities assessed decades earlier. Individual differences that distinguish the able (top 1 in 100) from the exceptionally able (top 1 in 10,000) during early adolescence matter in life, and, given the heritability of general intelligence, they suggest that understanding the genetic and environmental origins of exceptional abilities should be a high priority for behavior genetic research, especially because the results for extreme groups could differ from the rest of the population. In addition to enhancing our understanding of the etiology of general intelligence at the extreme, such inquiry may also reveal fundamental determinants of specific abilities, like mathematical versus verbal reasoning, and the distinctive phenotypes that contrasting ability patterns are most likely to eventuate in at extraordinary levels.


Exceptional cognitive abilities Intellectual talent Talent searches Talent development 



Support for this article was provided by a Research and Training Grant from the Templeton Foundation and National Institute of Child Health and Development Grant P30 HD 15051 to the Vanderbilt Kennedy Center for Research on Human Development. Earlier versions of this article benefited from comments from Kimberley Ferriman, Gregory Park, and Jonathan Wai.


  1. Benbow CP (1992) Academic achievement in math and science between ages 13 and 23: are there differences in the top one percent of ability? J Educ Psychol 84:51–61. doi: 10.1037/0022-0663.84.1.51 CrossRefGoogle Scholar
  2. Benbow CP, Stanley JC (1996) Inequity in equity: how “equity” can lead to inequity for high-potential students. Psychol Public Policy Law 2:249–292. doi: 10.1037/1076-8971.2.2.249 CrossRefGoogle Scholar
  3. Benbow CP, Lubinski D, Shea DL, Eftekhari-Sanjani H (2000) Sex differences in mathematical reasoning ability: their status 20 years later. Psychol Sci 11:474–480. doi: 10.1111/1467-9280.00291 PubMedCrossRefGoogle Scholar
  4. Bleske-Rechek A, Lubinski D, Benbow CP (2004) Meeting the educational needs of special populations: advanced placement’s role in developing exceptional human capital. Psychol Sci 15:217–224. doi: 10.1111/j.0956-7976.2004.00655.x PubMedCrossRefGoogle Scholar
  5. Carroll JB (1993) Human cognitive abilities: a survey of factor-analytic studies. Cambridge University Press, CambridgeGoogle Scholar
  6. Ceci SJ, Papierno PB (2005) The rhetoric and reality of gap closing: when the “have nots” gain but the “haves” gain even more. Am Psychol 60:149–160. doi: 10.1037/0003-066X.60.2.149 PubMedCrossRefGoogle Scholar
  7. Colangelo N, Assouline SG, Gross MUM (eds) (2004) A nation deceived: how schools hold back America’s brightest students. University of Iowa, Iowa CityGoogle Scholar
  8. Corno L, Cronbach LJ et al (eds) (2002) Remaking the concept of aptitude: extending the legacy of Richard E. Snow. Earlbaum, MahwahGoogle Scholar
  9. Eisner EW (1999) The use and limits of performance assessment. Phi Delta Kappan 80:658–660Google Scholar
  10. Ericsson KA et al (eds) (2006) The Cambridge handbook of expertise and expert performance. Cambridge University Press, CambridgeGoogle Scholar
  11. Eysenck HJ (1995) Genius: the natural history of creativity. Cambridge University Press, CambridgeGoogle Scholar
  12. Frey MC, Detterman DK (2004) Scholastic assessment or g?: The relationship between the scholastic assessment test and general cognitive ability. Psychol Sci 15:373–378. doi: 10.1111/j.0956-7976.2004.00687.x PubMedCrossRefGoogle Scholar
  13. Fuchs LS, Fuchs D, Karns K, Hamlett CL, Katzaroff M (1999) Mathematics performance assessment in the classroom: effects on teacher planning and student learning. Am Educ Res J 36:609–646Google Scholar
  14. Fuchs D, Fuchs LS, Thompson A, Al Otaiba S, Yen L, Yang N, Braun M, O’Connor RE (2001) Is reading important in reading-readiness programs? A randomized field trial with teachers as program implementers. J Educ Psychol 93:251–267. doi: 10.1037/0022-0663.93.2.251 CrossRefGoogle Scholar
  15. Gagne F (2005) From noncompetence to exceptional talent: exploring the range of academic achievement within and between grade levels. Gift Child Q 49:139–153. doi: 10.1177/001698620504900204 CrossRefGoogle Scholar
  16. Gladwell M (2008) Outliers: the story of success. Little Brown, New YorkGoogle Scholar
  17. Gohm CL, Humphreys LG, Yao G (1998) Underachievement among spatially gifted students. Am Educ Res J 35:515–531Google Scholar
  18. Gottfredson LS (1997) Intelligence and social policy (special issue). Intelligence 24:(#1 whole issue)Google Scholar
  19. Gottfredson LS (2003) The challenge and promise of cognitive career assessment. J Career Assess 11:115–135. doi: 10.1177/1069072703011002001 CrossRefGoogle Scholar
  20. Gottfredson LS (2004) Intelligence: is it the epidemiologists’ elusive “fundamental cause” of social class inequalities in health. J Pers Soc Psychol 86:174–199. doi: 10.1037/0022-3514.86.1.174 PubMedCrossRefGoogle Scholar
  21. Haier RJ (2009) Neuro-intelligence: neuro-metrics and the next phase of brain imaging studies. Intelligence (in press)Google Scholar
  22. Jensen AR (1991) Spearman’s g and the problem of educational equality. Oxford Rev Educ 17:169–187CrossRefGoogle Scholar
  23. Jensen AJ (1996) Giftedness and genius: crucial differences. In: Benbow CP, Lubinski D (eds) Intellectual talent: psychometric and social issues. Johns Hopkins University Press, Baltimore, pp 393–411Google Scholar
  24. Jensen AR (1998) The g factor. Praeger, WestportGoogle Scholar
  25. Jung R, Haier RJ (2007) The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav Brain Sci 30:135–154. doi: 10.1017/S0140525X07001185 PubMedCrossRefGoogle Scholar
  26. Keating DP, Stanley JC (1972) Extreme measures for the exceptionally gifted in mathematics and science. Educ Res 1:3–7Google Scholar
  27. Kenny DA (1975) A quasi-experimental approach to assessing treatment effects in the nonequivalent control group design. Psychol Bull 82:345–362. doi: 10.1037/0033-2909.82.3.345 CrossRefGoogle Scholar
  28. Kuncel NR, Hezlett SA (2007) Standardized tests predict graduate student success. Science 315:1080–1081. doi: 10.1126/science.1136618 PubMedCrossRefGoogle Scholar
  29. Kuncel NR, Hezlett SA, Ones DS (2001) A comprehensive meta-analysis of the predictive validity of the graduate record examinations: implications for graduate student selection and performance. Psychol Bull 127:162–181. doi: 10.1037/0033-2909.127.1.162 PubMedCrossRefGoogle Scholar
  30. Lubinski D (2004) Introduction to the special section on cognitive abilities: 100 years after Spearman’s (1904) “‘General intelligence’, objectively determined and measured. J Pers Soc Psychol 86:96–111. doi: 10.1037/0022-3514.86.1.96 PubMedCrossRefGoogle Scholar
  31. Lubinski D, Benbow CP (2006) Study of mathematically precocious youth after 35 years: uncovering antecedents for the development of math-science expertise. Perspect Psychol Sci 1:316–345Google Scholar
  32. Lubinski D, Humphreys LG (1992) Some bodily and medical correlates of mathematical giftedness and commensurate levels of socioeconomic status. Intelligence 16:99–115. doi: 10.1016/0160-2896(92)90027-O CrossRefGoogle Scholar
  33. Lubinski D, Humphreys LG (1997) Incorporating general intelligence into epidemiology and the social sciences. Intelligence 24:159–201. doi: 10.1016/S0160-2896(97)90016-7 CrossRefGoogle Scholar
  34. Lubinski D, Benbow CP, Shea DL, Eftekhari-Sanjani H, Halvorson MBJ (2001a) Men and women at promise for scientific excellence: similarity not dissimilarity. Psychol Sci 12:309–317PubMedCrossRefGoogle Scholar
  35. Lubinski D, Webb RM, Morelock MJ, Benbow CP (2001b) Top 1 in 10,000: a 10-year follow-up of the profoundly gifted. J Appl Psychol 86:718–729. doi: 10.1037/0021-9010.86.4.718 PubMedCrossRefGoogle Scholar
  36. Lubinski D, Benbow CP, Webb RM, Bleske-Rechek A (2006) Tracking exceptional human capital over two decades. Psychol Sci 17:194–199. doi: 10.1111/j.1467-9280.2006.01685.x PubMedCrossRefGoogle Scholar
  37. Muratori MC, Stanley JC, Gross MUM, Ng L, Tao T, Ng J, Tao B (2006) Insights from SMPY’s greatest former prodigies: Drs. Terence (“Terry”) Tao and Lenhard (“Lenny”) Ng reflect on their talent development. Gift Child Q 50:307–324. doi: 10.1177/001698620605000404 CrossRefGoogle Scholar
  38. Murray C (1998) Income inequality, and IQ. American Enterprise Institute, WashingtonGoogle Scholar
  39. Park G, Lubinski D, Benbow CP (2007) Contrasting intellectual patterns for creativity in the arts and sciences: tracking intellectually precocious youth over 25 years. Psychol Sci 18:948–952. doi: 10.1111/j.1467-9280.2007.02007.x PubMedCrossRefGoogle Scholar
  40. Park G, Lubinski D, Benbow CP (2008) Ability differences among people who have commensurate degrees matter for scientific creativity. Psychol Sci 19:957–961. doi: 10.1111/j.1467-9280.2008.02182.x PubMedCrossRefGoogle Scholar
  41. Plomin R (2003) Behavior genetics in the postgenomic era. American Psychological Association, WashingtonCrossRefGoogle Scholar
  42. Plomin R, Kovas Y (2005) Generalist genes and learning disabilities. Psychol Bull 131:592–617. doi: 10.1037/0033-2909.131.4.592 PubMedCrossRefGoogle Scholar
  43. Pressey SL (1946) Acceleration: disgrace or challenge? Science 104:215–219. doi: 10.1126/science.104.2697.215 PubMedCrossRefGoogle Scholar
  44. Pressey SL (1955) Concerning the nature and nurture of genius. Sci Mon 81:123–129Google Scholar
  45. Putallaz MBJ et al (2005) The Duke talent identification program. High Abil Stud 16:41–54. doi: 10.1080/13598130500115221 CrossRefGoogle Scholar
  46. Robinson NM, Abbott RD, Berninger VW, Busse J (1996) The structure of abilities in mathematically precocious young children: gender similarities and differences. J Educ Psychol 88:341–352. doi: 10.1037/0022-0663.88.2.341 CrossRefGoogle Scholar
  47. Robinson NM, Abbott RD, Berninger VW, Busse J, Mukhopadhyah S (1997) Developmental changes in mathematically precocious young children. Gift Child Q 41:145–158. doi: 10.1177/001698629704100404 CrossRefGoogle Scholar
  48. Sackett PR, Kuncel NR, Arneson JJ, Cooper SR, Waters SD (2009) Does socioeconomic status explain the relationship between admissions tests and post-secondary academic performance? Psychol Bull 135:1–22. doi: 10.1037/a0013978 PubMedCrossRefGoogle Scholar
  49. Schmidt FL, Hunter JE (1998) The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings. Psychol Bull 124:262–274. doi: 10.1037/0033-2909.124.2.262 CrossRefGoogle Scholar
  50. Seashore CE (1922) The gifted student and research. Science 56:641–648. doi: 10.1126/science.56.1458.641 PubMedCrossRefGoogle Scholar
  51. Shea DL, Lubinski D, Benbow CP (2001) Importance of assessing spatial ability in intellectually talented young adolescents: a 20-year longitudinal study. J Educ Psychol 93:604–614. doi: 10.1037/0022-0663.93.3.604 CrossRefGoogle Scholar
  52. Simonton DK (1994) Greatness: who makes history and why. Guilford Press, NYGoogle Scholar
  53. Snow RE, Lohman DF (1989) Implications of cognitive psychology for educational measurement. In: Linn RL (ed) Educational measurement, 3rd edn. Collier, New York, pp 263–331Google Scholar
  54. Snow RE, Corno L, Jackson DIII (1996) Individual differences in affective and conative functions. In: Berliner DC, Calfee RC (eds) Handbook of educational psychology. MacMillan, New York, pp 243–310Google Scholar
  55. Spearman C (1927) The abilities of man: their nature and measurement. Macmillan, New YorkGoogle Scholar
  56. Spearman C, Jones L (1950) Human ability. Macmillan, LondonGoogle Scholar
  57. Stanley JC (1996) SMPY in the beginning. In: Benbow CP, Lubinski D (eds) Intellectual talent. Johns Hopkins University Press, Baltimore, pp 225–235Google Scholar
  58. Stanley JC (2000) Helping students learn only what they don’t already know. Psychol Public Policy Law 6:216–222. doi: 10.1037/1076-8971.6.1.216 CrossRefGoogle Scholar
  59. Terman LM (1925) Genetic studies of genius: vol. 1. Stanford University Press, StanfordGoogle Scholar
  60. Terman LM (1954) The discovery and encouragement of exceptional talent. Am Psychol 9:221–230. doi: 10.1037/h0060516 CrossRefGoogle Scholar
  61. Thorndike EL (1911) Individuality. Houghton & Miffin, Co, New YorkGoogle Scholar
  62. Thurstone LL (1948) Psychological implications of factor analysis. Am Psychol 3:402–408. doi: 10.1037/h0058069 PubMedCrossRefGoogle Scholar
  63. Wai J, Lubinski D, Benbow CP (2005) Creativity and occupational accomplishments among intellectually precocious youth: an age 13 to age 33 longitudinal study. J Educ Psychol 97:484–492 CrossRefGoogle Scholar
  64. Wai J, Lubinski D, Benbow CP (2009) Spatial ability for STEM domains: aligning over fifty years of cumulative psychological knowledge solidifies its importance. J Educ Psychol 101Google Scholar
  65. Webb RM, Lubinski D, Benbow CP (2002) Mathematically facile adolescents with math-science aspirations: new perspectives on their educational and vocational development. J Educ Psychol 94:785–794. doi: 10.1037/0022-0663.94.4.785 CrossRefGoogle Scholar
  66. Webb RM, Lubinski D, Benbow CP (2007) Spatial ability: a neglected dimension in talent searches for intellectually precocious youth. J Educ Psychol 99:397–420. doi: 10.1037/0022-0663.99.2.397 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Psychology and Human DevelopmentVanderbilt UniversityNashvilleUSA

Personalised recommendations