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(NAS Colloquium) Neuroimaging of Human Brain Function (1998)
National Academy of Sciences (NAS)

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. "The neural development and organization of letter recognition: Evidence from functional neuroimaging, computational modeling, and behavioral studies." (NAS Colloquium) Neuroimaging of Human Brain Function. Washington, DC: The National Academies Press, 1998.

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Colloquium on Neuroimaging of Human Brain Function

letters and letter-among-digits conditions). The sorters were, however, faster than controls, presumably because of their extensive experience with speeded tasks. So, to ensure that these results were not the result of a floor effect, we excluded the three slowest postal worker controls (out of 16) for one analysis and used college graduates whose response times were faster for another. In both cases, the control group showed a larger category effect than the sorters even though both groups were faster than the sorters in the letter-among-digits condition. These cross-over interactions eliminate any obvious interpretations based on scaling artifacts and confirm the prediction of the co-occurrence hypothesis.

DISCUSSION

Letters and digits are distinguished, not by any obvious physical features, but solely by cultural conventions. Furthermore, the ability to recognize them is not innate. Nevertheless, we found evidence that the neural substrates underlying letter recognition are segregated from those underlying digit recognition in most normal subjects. The fact that letter and digit recognition depend on different neural substrates therefore suggests that the environment can lead to qualitative changes in the brain’s functional organization. How might that happen? We have shown that a robust statistical property of the environment (the co-occurrence of letters), in conjunction with simple and widely accepted assumptions about the computational properties of cortex (correlation-based learning and lateral interactions), will lead to the segregation of such arbitrary and noninnate categories. We also have confirmed a critical prediction of this hypothesis, namely, that subjects exposed to a visual environment in which letters and digits occur together rather than separately would show less behavioral evidence of processing the two stimulus categories separately.

The co-occurrence hypothesis also may explain other counterintuitive examples of functional localization, such as the localization of musical processing and handwriting. Just as letters co-occur in text, musical sounds occur together in music and written characters occur together in writing. Indeed, even at the level of writing cursive vs. print, co-occurrence of stimuli is satisfied.

The point is not that the processing of any stimuli that co-occur in the environment will necessarily come to be localized in cortex. The hypothesis assumes both that the neural processing is local and that the relevant neural representations reflect the statistics of the environment (that is, the neural representations themselves co-occur). Complex stimuli with widely distributed representations presumably would not satisfy these constraints. Nevertheless, the co-occurrence hypothesis does offer a plausible new explanation for the localization of a number of arbitrary categories for which there is evidence of cortical specialization.

1. Alexander, M.P., Fischer, R.S. & Friedman, R. (1992) Arch. Neurol. 49, 246–251.

2. Hanley, J.R. & Peters, S. (1996) Cortex 32, 737–745.

3. Peretz, I., Kolinsky, R., Tramo, M., Labrecque, R., Hublet, C., Demeurisse, G. & Belleville, S. (1994) Brain 117, 1283–1301.

4. Gardner, H. (1974) J. Psycholinguistic Res. 3, 133–149.

5. Allison, T., McCarthy, G., Nobre, A., Puce, A. & Belger, A. (1994) Cereb. Cortex 4, 544–554.

6. Hebb, D.O. (1949) The Organization of Behavior: A Neuropsy-chological Theory. (Wiley, New York).

7. Polk, T.A. & Farah, M.J. (1995) Proc. Natl. Acad. Sci. USA 92, 12370–12373.

8. von der Malsburg, C. (1973) Kybernetik 14, 85–100.

9. von der Malsburg, C. (1979) Biol. Cybern. 32, 49–62.

10. Goodhill, G.J. (1992) Ph.D. thesis (University of Sussex, Brighton, U.K.).

11. Cottrell, M. & Fort, J.C. (1986) Biol. Cybern. 53, 405–411.

12. Durbin, R. & Mitchison, G. (1990) Nature (London) 343, 644– 647 .

13. Linsker, R. (1986) Proc. Natl. Acad. Sci. USA 83, 7508–7512.

14. Linsker, R. (1986) Proc. Natl. Acad. Sci. USA 83, 8390–8394.

15. Linsker, R. (1986) Proc. Natl. Acad. Sci. USA 83, 8779–8783.

16. Miller, K.D., Keller, J.B. & Stryker, M.P. (1989) Science 245, 605–615.

17. Ritter, H. (1990) Psychol. Res. 52, 128–136.

18. Kohonen, T. (1988) Self-Organization and Associative Memory (Springer, New York), 2nd Ed.

19. Foldiak, P. (1991) Neural Computat. 3, 194–200.

20. Duncan, J. (1980) Psychol. Rev. 87, 272–300.

21. Duncan, J. (1983) Percept. Psychophys. 33, 533–547.

22. Egeth, H., Jonides, J. & Wall, S. (1972) Cognit. Psychol. 3, 674–698.

23. Jonides, J. & Gleitman, H. (1972) Percept. Psychophys. 12, 457–460.

24. Merikle, P.M. (1980) J. Exp. Psychol. Gen. 109, 279–295.

25. Schneider, W. & Shiffrin, R.M. (1977) Psychol. Rev. 84, 1–66.

26. von Wright, J.M. (1972) Scand. J. Psychol. 13, 159–171.

27. Polk, T.A. & Farah, M.J. (1995) Nature (London) 376, 648–649.

Page
90
Front Matter (R1-R6)
Contents (R7-R8)
The neuroimaging of human brain function (1-2)
Behind the scenes of functional brain imaging: A historical and physiological perspective (3-10)
Event-related functional MRI: Past, present, and future (11-18)
Event-related brain potentials in the study of visual selective attention (19-25)
Functional and structural mapping of human cerebral cortex: Solutions are in the surfaces (26-33)
Imaging neuroscience: Principles or maps? (34-40)
Spatially independent activity patterns in functional MRI data during the Stroop color-naming task (41-48)
Functional analysis of primary visual cortex (V1) in humans (49-55)
The representation of the ipsilateral visual field in human cerebral cortex (56-62)
On the role of selective attention in visual perception (63-68)
Frontoparietal cortical networks for directing attention and the eye to visual locations: Identical, independent, or overlapping neural systems? (69-76)
Neural components of topographical representation (77-84)
The neural development and organization of letter recognition: Evidence from functional neuroimaging, computational modeling, and behavioral studies (85-90)
The effects of practice on the functional anatomy of task performance (91-98)
The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex (99-106)
Rapidly induced auditory plasticity: The ventriloquism aftereffect (107-113)
Components of verbal working memory: Evidence from neuroimaging (114-120)
A neural system for human visual working memory (121-128)
Functional neuroimaging studies of encoding, priming, and explicit memory retrieval (129-136)
Anatomy of word and sentence meaning (137-143)
The role of left prefrontal corex in language and memory (144-151)
Neuroimaging studies of word reading (152-159)
Cerebral organization for langague in deaf and hearing subjects: Biological constraints and effects of experience (160-167)