Article | Published:

Neural mechanisms of general fluid intelligence

Abstract

We used an individual-differences approach to test whether general fluid intelligence (gF) is mediated by brain regions that support attentional (executive) control, including subregions of the prefrontal cortex. Forty-eight participants first completed a standard measure of gF (Raven's Advanced Progressive Matrices). They then performed verbal and nonverbal versions of a challenging working-memory task (three-back) while their brain activity was measured using functional magnetic resonance imaging (fMRI). Trials within the three-back task varied greatly in the demand for attentional control because of differences in trial-to-trial interference. On high-interference trials specifically, participants with higher gF were more accurate and had greater event-related neural activity in several brain regions. Multiple regression analyses indicated that lateral prefrontal and parietal regions may mediate the relation between ability (gF) and performance (accuracy despite interference), providing constraints on the neural mechanisms that support gF.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1

    Kosslyn, S.M. et al. Bridging psychology and biology: the analysis of individuals in groups. Am. Psychol. 57, 341–351 (2002).

  2. 2

    Cattell, R.B. Abilities: Their Structure, Growth and Action (Houghton Mifflin, Boston, 1971).

  3. 3

    Sternberg, R.J. The holey grail of general intelligence. Science 289, 399–401 (2000).

  4. 4

    Kane, M.J. & Engle, R.W. The role of prefrontal cortex in working-memory capacity, executive attention and general fluid intelligence: an individual-differences perspective. Psychonom. Bull. Rev. (in press).

  5. 5

    Deary, I.J. Looking Down on Human Intelligence (Oxford Univ. Press, New York, 2000).

  6. 6

    Sternberg, R.J. Beyond IQ: a Triarchic Theory of Human Intelligence (Cambridge Univ. Press, Cambridge, 1985).

  7. 7

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

  8. 8

    Engle, R.W., Kane, M.J. & Tuholski, S.W. Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. in Models of Working Memory (eds. Miyake, A. & Shah, P.) 102–134 (Cambridge University Press, New York, 1999).

  9. 9

    Kyllonen, P.C. & Christal, R.E. Reasoning ability is (little more than) working memory capacity?! Intelligence 14, 389–433 (1990).

  10. 10

    Conway, A.R.A., Cowan, N., Bunting, M.F., Therriault, D.J. & Minkoff, S.R.B. A latent variable analysis of working memory capacity, short term memory capacity, processing speed and general fluid intelligence. Intelligence 30, 163–183 (2002).

  11. 11

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

  12. 12

    Prabhakaran, V., Smith, J.A.L., Desmond, J.E., Glover, G.H. & Gabrieli, J.D.E. Neuronal substrates of fluid reasoning: an fMRI study of neocortical activation during performance of the Raven's Progressive Matrices Test. Cogn. Psychol. 33, 43–63 (1997).

  13. 13

    Thompson, P.M. et al. Genetic influences on brain structure. Nat. Neurosci. 4, 1253–1258 (2001).

  14. 14

    Fritsch, G. & Hitzig, E. Ueber die elektrische Erregbarkeit des Grosshirns. Archiv Anatomie Physiologie Wissenschaftliche Medicin 37, 300–332 (1870).

  15. 15

    Markowitsch, H.J. & Kessler, J. Massive impairment in executive functions with partial preservation of other cognitive functions: the case of a young patient with severe degeneration of the prefrontal cortex. Exp. Brain Res. 133, 94–102 (2000).

  16. 16

    Duncan, J. et al. A neural basis for general intelligence. Science 289, 457–460 (2000).

  17. 17

    Petersen, S.E., van Mier, H., Fiez, J.A. & Raichle, M.E. The effects of practice on the functional anatomy of task performance. Proc. Natl. Acad. Sci. USA 95, 853–860 (1998).

  18. 18

    Braver, T.S. et al. A parametric study of prefrontal cortex involvement in human working memory. Neuroimage 5, 49–62 (1997).

  19. 19

    Cabeza, R. & Nyberg, L. Imaging cognition II: an empirical review of 275 PET and fMRI studies. J. Cogn. Neurosci. 12, 1–47 (2000).

  20. 20

    D'Esposito, M., Postle, B.R., Jonides, J. & Smith, E.E. The neural substrate and temporal dynamics of interference effects in working memory as revealed by event-related functional MRI. Proc. Natl. Acad. Sci. USA 96, 7514–7519 (1999).

  21. 21

    Jonides, J., Smith, E., Marshuetz, C., Koeppe, R. & Reuter-Lorenz, P.A. Inhibition in verbal working memory revealed by brain activation. Proc. Natl. Acad. Sci. USA 95, 8410–8413 (1998).

  22. 22

    MacDonald, A.W., Cohen, J.D., Stenger, V.A. & Carter, C.S. Dissociating the role of the dorsolateral prefrontal cortex and anterior cingulate cortex in cognitive control. Science 288, 1835–1838 (2000).

  23. 23

    Carter, C.S. et al. Anterior cingulate cortex, error detection and the online monitoring of performance. Science 280, 747–749 (1998).

  24. 24

    Paus, T., Koski, L., Caramanos, Z. & Westbury, C. Regional differences in the effects of task difficulty and motor output on blood flow response in the human anterior cingulate cortex: a review of 107 PET activation studies. NeuroReport 9, R37–R47 (1998).

  25. 25

    Posner, M.I. & Petersen, S.E. The attention system of the human brain. Annu. Rev. Neurosci. 13, 25–42 (1990).

  26. 26

    Schmahmann, J. & Sherman, J. The cerebellar cognitive affective syndrome. Brain 121, 561–579 (1998).

  27. 27

    Gruber, O. Effects of domain-specific interference on brain activation associated with verbal working memory task performance. Cereb. Cortex 11, 1047–1055 (2001).

  28. 28

    Bischoff-Grethe, A., Ivry, R.B. & Grafton, S.T. Cerebellar involvement in response reassignment rather than attention. J. Neurosci. 22, 546–553 (2002).

  29. 29

    Donaldson, D.I., Petersen, S.E., Ollinger, J.M. & Buckner, R.L. Dissociating item and state components of recognition memory using fMRI. Neuroimage 13, 129–142 (2001).

  30. 30

    Baron, R.M. & Kenny, D.A. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173–1182 (1986).

  31. 31

    Botvinick, M.M., Braver, T.S., Barch, D.M., Carter, C.S. & Cohen, J.C. Conflict monitoring and cognitive control. Psychol. Rev. 108, 624–652 (2001).

  32. 32

    Braver, T.S., Barch, D.M., Gray, J.R., Molfese, D.L. & Snyder, A. Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cereb. Cortex 11, 825–836 (2001).

  33. 33

    Koechlin, E., Basso, G., Pietrini, P., Panzer, S. & Grafman, J. The role of the anterior prefrontal cortex in human cognition. Nature 399, 148–151 (1999).

  34. 34

    Cronbach, L.J. The two disciplines of scientific psychology. Am. Psychol. 12, 671–684 (1957).

  35. 35

    Brodmann, K. Ergebnisse über die vergleichende histologische lokalisation der grosshirnrinde mit besonderer berücksichtigung des stirnhirns. Anatomischer Anzeiger 41 (Suppl.), 157–216 (1912).

  36. 36

    Ceci, S.J. How much does schooling influence general intelligence and its cognitive components? A reassessment of the evidence. Dev. Psychol. 27, 703–722 (1991).

  37. 37

    Ceci, S.J. & Williams, W.M. Schooling, intelligence and income. Am. Psychol. 52, 1051–1058 (1997).

  38. 38

    Neisser, U. (ed.) The Rising Curve: Long-term Gains in IQ and Related Measures (American Psychological Association, Washington, DC, 1998).

  39. 39

    Raven, J., Raven, J.C. & Court, J.H. Manual for Raven's Progressive Matrices and Vocabulary Scales (Oxford Psychologists Press, Oxford, UK, 1998).

  40. 40

    Cohen, J., MacWhinney, B., Flatt, M. & Provost, J. PsyScope: an interactive graphic system for designing and controlling experiments in the psychology laboratory using Macintosh computers. Behav. Res. Methods Instr. Comput. 25, 257–271 (1993).

  41. 41

    Gray, J.R., Braver, T.S. & Raichle, M.E. Integration of emotion and cognition in the lateral prefrontal cortex. Proc. Natl. Acad. Sci. USA 99, 4115–4120 (2002).

  42. 42

    Talairach, J. & Tournoux, P. Co-planar Stereotaxic Atlas of the Human Brain (Thieme, New York, 1988).

  43. 43

    Gray, J.R. & Braver, T.S. Personality predicts working memory related activation in the caudal anterior cingulate cortex. Cogn. Affect. Behav. Neurosci. 2, 64–75 (2002).

  44. 44

    Boynton, G.M., Engel, S.A., Glover, G.H. & Heeger, D.J. Linear systems analysis of functional magnetic resonance imaging in human V1. J. Neurosci. 16, 4207–4221 (1996).

  45. 45

    McAvoy, M.P., Ollinger, J.M. & Buckner, R.L. Cluster size thresholds for assessment of significant activation in fMRI. Neuroimage 13, S198 (2001).

  46. 46

    Price, C.J. & Friston, K.J. Cognitive conjunction: a new approach to brain activation experiments. Neuroimage 5, 261–270 (1997).

  47. 47

    Cohen, J. & Cohen, P. Applied Multiple Regression/correlation Analysis for the Behavioral Sciences (L. Erlbaum, Hillsdale, New Jersey, 1983).

  48. 48

    Van Essen, D.C. Windows on the brain. The emerging role of atlases and databases in neuroscience. Curr. Opin. Neurobiol. 12, 574–579 (2002).

Download references

Acknowledgements

This material is based on work supported by the National Science Foundation (grant 0001908). C.F.C. was supported by a Director of Central Intelligence postdoctoral fellowship. The authors thank D.M. Barch, R.W. Engle, A.R.A. Conway, G.C. Burgess, M. Storandt, M.E. Glickman, G.E. Miller, S.J. Ceci, C.M. Hoyer and J.M. Zelensky.

Author information

Competing interests

The authors declare no competing financial interests.

Correspondence to Todd S. Braver.

Rights and permissions

Reprints and Permissions

About this article

Further reading

Figure 1: Behavioral protocol, three-back task.
Figure 2: Three-back task performance (n = 58).
Figure 3: Regions in which gF predicted lure-trial activity, using a priori (red) and whole-brain (yellow) search criteria, shown on the folded surface of a standard brain48.
Figure 4: Region-level relations between gF and brain activity in left lateral PFC (BA 46/45, 21 voxels from whole brain search, n = 48).