Skip to main content
Log in

Genetic Structure of Spatial and Verbal Working Memory

  • Published:
Behavior Genetics Aims and scope Submit manuscript

Abstract

Working memory (WM) encompasses both short-term memory (storage) and executive functions that play an essential role in all forms of cognition. In this study, the genetic structure of storage and executive functions engaged in both a spatial and verbal WM span task is investigated using a twin sample. The sample consists of 143 monozygotic (MZ) and 93 dizygotic (DZ) Japanese twin pairs, ages 16 to 29 years. In 155 (87 MZ, 62 DZ) of these pairs, cognitive ability scores from the Kyodai Japanese IQ test are also obtained. The phenotypic relationship between WM and cognitive ability is confirmed (r = 0.26−0.44). Individual differences in WM storage and executive functions are found to be significantly influenced by genes, with heritability estimates all moderately high (43%–49%), and estimates for cognitive ability comparable to previous studies (65%). A large part of the genetic variance in storage and executive functions in both spatial and verbal modalities is due to a common genetic factor that accounts for 11% to 43% of the variance. In the reduced sample, this common genetic factor accounts for 64% and 26% of the variance in spatial and verbal cognitive ability, respectively. Additional genetic variance in WM (7%–30%) is due to modality specific factors (spatial and verbal) and a storage specific factor that may be particularly important for the verbal modality. None of the variance in cognitive ability is accounted for by the modality and storage genetic factors, suggesting these may be specific to WM.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

REFERENCES

  • Alarcon, M., Plomin, R., Fulker, D. W., Corley, R., and DeFries, J. C. (1998). Multivariate path analysis of specific cognitive abilities data at 12 years old of age in the Colorado Adoption Project. Behav. Gen., 28: 255–264.

    Google Scholar 

  • Ando, J., Fukunaga, N., Kurahachi, J., Suto, T., Nakano, T., and Kage, M. (1992). A comparative study of the two EFL teaching methods: The communicative and grammatical approach. Jap. J. Edu. Psychol. 40: 247–256.

    Google Scholar 

  • Baddeley, A. D. (1986). Working memory. New York, Oxford University Press.

    Google Scholar 

  • Baddeley, A. D., and Hitch, G. J. (1974). Working memory. In G. H. Bower (ed.), The psychology of learning and motivation: Advances in research and theory. New York, Academic Press.

    Google Scholar 

  • Baddeley, A. D., Gathercole, S. E., and Papagno, C. (1998). The phonological loop as a language learning device. Psychol. Rev. 105: 158–173.

    Google Scholar 

  • Bentler, P. M. (1995). EQS structural equations program manual. Encino, Calif.: Multivariate Software (Vol. 8, pp. 47–89). New York, Academic Press.

    Google Scholar 

  • Bouchard, Jr. T. J., and McGue, M. (1981). Familial studies of intelligence: A review. Science 212: 1055–1059.

    Google Scholar 

  • Cardon, L. R., and Fulker, D. W. (1993). Genetics of specific cognitive abilities. In R. Plomin and G. E. McClearn (eds.), Nature, nurture, and psychology, Washington, DC, American Psychological Association, pp. 99–120.

    Google Scholar 

  • Carpenter, P. A., Just, M., and Shell, P. (1990). What one intelligence test measures: A theoretical account of the processing in the Raven Progressive Matrices test. Psychol. Rev. 97: 404–431.

    Google Scholar 

  • Chipuer, H. M., Rovine, M. J., and Plomin, R. (1990). LISREL modeling: Genetic and environmental influences on IQ revisited. Intelligence 14: 11–29.

    Google Scholar 

  • Courtney, S., Ungerleider, L. G., Keil, K., and Haxby, J. V. (1996). Object and spatial visual working memory activate separate neural systems in human cortex. Cereb. Cort. 6: 39–49.

    Google Scholar 

  • Cowan, N. (1999). An embedded-processes model of working memory. In A. Miyake and P. Shah (eds.), Models of working memory: Mechanisms of active maintenance and executive control, New York, Cambridge University Press, pp. 62–101.

    Google Scholar 

  • Daneman, M., and Carpenter, P. A. (1980). Individual differences in working memory and reading. J. Verb. Learn. Verb. Beh. 18: 450–466.

    Google Scholar 

  • Daneman, M., and Merikle, P. M. (1996). Working memory and language comprehension: A meta-analysis. Psychonom. Bull. Rev. 3: 422–433.

    Google Scholar 

  • Engle, R. W., Tuholski, S. W., Laughlin, J. E., and Conway, A. R. A. (1999). Working memory, short-term memory, and general fluid intelligence: A latent variable approach. J. Exp. Psychol. Gen. 128: 309–331.

    Google Scholar 

  • Finkel, D., and McGue, M. (1993). The origin of individual differences in memory among the elderly: A behavior genetic analysis. Psychol. Aging 8: 527–537.

    Google Scholar 

  • Finkel, D., and McGue, M. (1998). Age differences in the nature and origin of individual differences in memory: A behavior genetic analysis. Int. J. Aging Hum. Dev. 47: 217–239.

    Google Scholar 

  • Finkel, D., Pedersen, N., and McGue, M. (1995). Genetic influences on memory performance in adulthood: Comparison of Minnesota and Swedish twin data. Psychol. Aging 10: 437–446.

    Google Scholar 

  • Freidman, N. P., and Miyake, A. (2000). Differential roles for visuospatial and verbal working memory in situation model construction. J. Exper. Psychol. Gen. 129: 61–83.

    Google Scholar 

  • Kyllonen, P. C. (1996). Is working memory capacity Spearman' g? In I. Dennis and P. Tapsfield (eds.), Human abilities: Their nature and measurement Mahwah, NJ, Erlbaum, pp. 49–75.

    Google Scholar 

  • Loehlin, J. C. (1989). Partitioning environmental and genetic contributions to behavioral development. Am. Psycholog. 44: 1285–1292.

    Google Scholar 

  • McGue, M., and Bouchard, Jr. T. J., (1989). Genetic and environmental determinants of informational processing and special mental abilities. In R. J. Sternberg (ed.), Advances in the psychology of human intelligence. Vol. 5, Hillsdale, NJ: Erlbaum, pp. 7–45.

    Google Scholar 

  • Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., and Wagner, T. A. (2000). The unitary and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cog. Psychol. 41: 49–100.

    Google Scholar 

  • Miyake, A., and Shah, P. (1999a). Emerging general consensus, unresolved theoretical issues, and future research directions. In A. Miyake and P. Shah (eds.), p. 442–481. Models of working memory: Mechanisms of active maintenance and executive control. New York, Cambridge University Press.

    Google Scholar 

  • Miyake, A., and Shah, P. (1999b). Toward unified theories of working memory: Emerging general consensus, unresolved theoretical issues, and future research directions. In A. Miyake and P. Shah (eds.), Models of working memory: Mechanisms of active maintenance and executive control. New York, Cambridge University Press, pp. 442–481.

    Google Scholar 

  • Neale, M. C., Boker, S. M., Xie, G., and Maes, H. H. (1999). Mx: Statistical Modeling (5th ed.). Department of Psychiatry, VCU Box 900126, Richmond, VA 23298.

    Google Scholar 

  • Nichols, R. C. (1978). Twin study of ability, personality, and interests. Homo, 29: 158–173.

    Google Scholar 

  • Ono, Y., Ando, J., Onoda, N., Yoshimura, K., Kanba, S., Hirano, M., and Asai, M. (2000). Genetic structure of the five-factor model of personality in a Japanese twin population. Keio J. Med. 39: 152–158.

    Google Scholar 

  • Ooki, S., Yamada, K., and Asaka, A. (1991). Zygosity diagnosis of twins by questionnaire for twin' mothers. Shoni Hoken Kenkyu 50: 71–76.

    Google Scholar 

  • Osaka, R., and Umemoto, A. (1973). Shintei Kyodai NX 15 dai nihan [Kyoto university new NX15 intelligence test]. Tokyo: Taisei shuppan.

    Google Scholar 

  • Plomin, R., and DeFries, J. C. (1998). Genetics of cognitive abilities and disabilities. Scient. Am. 5: 62–69.

    Google Scholar 

  • Plomin, R., DeFries, J. C., McClearn, G. E., and McGuffin, P. (2000). Behavioral Genetics (4th ed.) New York, Worth Publishers and W.H. Freeman and Company.

    Google Scholar 

  • Pedersen, N. L., Plomin, R., Nesselroade, J. R., and McClearn, G. E. (1992). A quantitative genetic analysis of cognitive abilities during the second half of the life span. Psychol. Sci. 3: 346–353.

    Google Scholar 

  • Rep, M. R., Just, M. A., van-Dijl, J. M., Carpenter, P. A., Suda, K., Keller, T. A., Schatz, G., Eddy, W. F., and Thulborn, K. (1996). Brain activation modulated by sentence comprehension. Science 274: 114–116.

    Google Scholar 

  • Shah, P., and Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differencs approach. J. Exp. Psychol. Gen. 125: 4–27.

    Google Scholar 

  • Torgersen, S. (1979). The determination of twin zygosity by means of a mailed questionnaire. Acta Genet. Med. Gemellol. 28: 225–236.

    Google Scholar 

  • Turner, M. L., and Engle, R. W. (1989). Is working memory capacity task dependent? J. Mem. Lang. 28: 127–154.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ando, J., Ono, Y. & Wright, M.J. Genetic Structure of Spatial and Verbal Working Memory. Behav Genet 31, 615–624 (2001). https://doi.org/10.1023/A:1013353613591

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1013353613591

Navigation