The capacity of cognitive neuroscience to inform clinical practice has stimulated both excitement and controversy.1-5 Noninvasive brain imaging methods are providing unprecedented views of the structural and functional development and aging of an individual's brain or state of brain pathology. These exciting new views of maturing and aging brains or of brain pathology may provide novel information relevant to the enhancement of clinical practice. The implications of neuroscience for clinical practice, however, have raised some controversy because of speculative and potentially flawed interpretations created by associating animal experimentation with human medical practice.1 As a result, the relationship between clinical practice and neuroscience has been called "a bridge too far."6 Nonetheless, it is evident that the field of cognitive neuroscience holds promise to inform clinical practice. The promise lies in its potential to address critical issues such as:
- Understanding the neural processes underlying the development of essential skills, such as reading and numeracy, and the "healthy" decline of cognitive functions such as memory.
- Understanding the pathophysiology of various neuropsychiatric disorders.
- Assessment and prediction of interventional outcome.
- Early identification of persons at risk for neuropsychiatric disorders.
While the following discussion focuses mainly on reading skills and disabilities, similar arguments may be applied to clinical issues. We focus on recent findings from our laboratory that highlight the extent to which functional and structural neuroimaging techniques can serve as a clinically useful tool in predicting outcome.
Reading is a skill that is undeniably critical to success in modern society, yet the development of reading abilities in children is becoming a significant problem. Based on the National Assessment of Educational Progress,7 only 31% of the nation's fourth graders are performing at or above the proficient achievement level that demonstrates solid academic performance in reading. Furthermore, dyslexia, a developmental learning disability that is characterized by difficulty in reading in individuals who otherwise have the intelligence and necessary motivation for accurate and fluent reading,8 is prevalent in 5% to 17% of all children and 80% of children with learning disabilities.9
Reading First, an initiative under the No Child Left Behind Act of 2002, was enacted with the goal of achieving high reading proficiency by the end of the third grade by 2014. The initiative emphasizes early identification of children who are at risk for reading failure. Once they are identified, neuroscientifically proven reading programs, interventions, and strategies in the early grades are used to improve reading fluency.
Neuroscientific evidence from a number of brain imaging studies performed over the past decade has provided us with novel insights into our knowledge of normal and disturbed reading.10-13 These studies have demonstrated that reading activates a widely distributed set of areas in the occipitotemporal; posterior temporal to parietotemporal; precentral; and inferior frontal gyri, which sustain orthographic, semantic, and phonologic processing.14 It has also been shown that the left posterior superior temporal, parietotemporal, and occipitotemporal regions are dysfunctional--with abnormal increases in activation in the left frontal region--in dyslexic readers.15-18 These findings have implications for novel models of reading and the disabilities associated with it.
Recent studies have shown the effects of interventions on neural patterns in response to reading.19-22 These studies demonstrate normalization of brain activation in the left hemispheric regions, which is critical for reading and generally dysfunctional in persons with dyslexia. In addition, an increased activation in the homologous right hemispheric regions is found in dyslexic brains after intervention. These studies provide insights into plastic changes that could occur in regions related to normal reading as well as putative compensatory changes in response to successful intervention. If examined carefully and with a larger number of subjects, these studies have the potential to assign optimal intervention strategies to children with different behavioral and neural profiles.
Investigation of the extent to which neuroimaging techniques can serve as a clinically useful tool in predicting future reading skills is still in its infancy. There are only a few developmental studies predicting reading skills and language, all of which use event-related potentials.23-25 Another study examining brain morphology using voxel-based morphometry (VBM) predicted short-term learning of novel speech sounds in adults.26 While there have been no studies that used functional neuroimaging to predict outcome in reading, there are an increasing number of studies with functional imaging in disorders such as depression27-29 or Alzheimer disease.30-33
1. Bruer JT. Avoiding the pediatrician's error: how neuroscientists can help educators (and themselves). Nat Neurosci.2002;5(suppl):1031-1033.
2. Goswami U. Neuroscience and education: from research to practice? Nat Rev Neurosci. 2006;7:406-411.
3. Moats L. Relevance of neuroscience to effective education for students with reading and other learning disabilities. J Child Neurol. 2004;19:840-845.
4. Koizumi H. The concept of 'developing the brain': a new natural science for learning and education. Brain Dev. 2004;26:434-441.
5. Honey GD, Fletcher PC, Bullmore ET. Functional brain mapping of psychopathology. J Neurol Neurosurg Psychiatry. 2002;72:432-439.
6. Bruer JT. Education and the brain: a bridge too far. Ed Res. 1997;26:1-13.
7. Trial Urban District Assessment Reading 2005. National Assessment of Educational Progress. February 2006. Available at: http://nces.gov/nationsreportcard/pdf/dst2005/2006455r.pdf. Accessed August 8, 2006.
8. Lyon GR. Research initiatives in learning disabilities: contributions from scientists supported by the National Institute of Child Health and Human Development. J Child Neurol. 1995;10(suppl 1):S120- S126.
9. Shaywitz SE. Dyslexia. N Engl J Med. 1998;338: 307-312.
10. Price CJ, Mechelli A. Reading and reading disturbance. Curr Opin Neurobiol. 2005;15:231-238.
11. Demonet JF, Taylor MJ, Chaix Y. Developmental dyslexia. Lancet. 2004;363:1451-1460.
12. Habib M. The neurological basis of developmental dyslexia: an overview and working hypothesis. Brain. 2000;123:2373-2399.
13. Shaywitz SE, Shaywitz BA. Dyslexia (specific reading disability). Biol Psychiatry. 2005;57:1301-1309.
14. Turkeltaub PE, Eden GF, Jones KM, Zeffiro TA. Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. Neuroimage. 2002;16:765-780.
15. Shaywitz BA, Shaywitz SE, Pugh KR, et al. Disruption of posterior brain systems for reading in children with developmental dyslexia. Biol Psychiatry. 2002;52: 101-110.
16. Shaywitz SE, Shaywitz BA, Pugh KR, et al. Functional disruption in the organization of the brain for reading in dyslexia. Proc Natl Acad Sci U S A. 1998;95: 2636-2641.
17. Temple E, Poldrack RA, Protopapas A, et al. Disruption of the neural response to rapid acoustic stimuli in dyslexia: evidence from functional MRI. Proc Natl Acad Sci U S A. 2000;97:13907-13912.
18. Hoeft F, Hernandez A, McMillon G, et al. Neural basis of dyslexia: a comparison between dyslexic and non-dyslexic children equated for reading ability. J Neuroscience. In press.
19. Aylward EH, Richards TL, Berninger VW, et al. Instructional treatment associated with changes in brain activation in children with dyslexia. Neurology. 2003; 61:212-219.
20. Eden GF, Jones KM, Cappell K, et al. Neural changes following remediation in adult developmental dyslexia. Neuron. 2004;44:411-422.
21. Shaywitz BA, Shaywitz SE, Blachman BA, et al. Development of left occipitotemporal systems for skilled reading in children after a phonologically-based intervention. Biol Psychiatry. 2004;55:926-933.
22. Temple E, Deutsch GK, Poldrack RA, et al. Neural deficits in children with dyslexia ameliorated by behavioral remediation: evidence from functional MRI. Proc Natl Acad Sci U S A. 2003;100:2860-2865.
23. Lyytinen H, Ahonen T, Eklund K, et al. Early development of children at familial risk for dyslexia--follow-up from birth to school age. Dyslexia. 2004;10: 146-178.
24. Molfese VJ, Molfese DL, Modgline AA. Newborn and preschool predictors of second-grade reading scores: an evaluation of categorical and continuous scores. J Learn Disabil. 2001;34:545-554.
25. Espy KA, Molfese DL, Molfese VJ, Modglin A. Development of auditory event-related potentials in young children and relations to word-level reading abilities at age 8 years. Ann Dyslexia. 2004;54:9-38.
26. Golestani N, Paus T, Zatorre RJ. Anatomical correlates of learning novel speech sounds. Neuron. 2002; 35:997-1010.
27. Canli T, Cooney RE, Goldin P, et al. Amygdala reactivity to emotional faces predicts improvement in major depression. Neuroreport. 2005;16:1267-1270.
28. Davidson RJ, Irwin W, Anderle MJ, Kalin NH. The neural substrates of affective processing in depressed patients treated with venlafaxine. Am J Psychiatry. 2003; 160:64-75.
29. Siegle GJ, Carter CS, Thase ME. Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. Am J Psychiatry. 2006;163: 735-738.
30. Bookheimer SY, Strojwas MH, Cohen MS, et al. Patterns of brain activation in people at risk for Alzheimer's disease. N Engl J Med. 2000;343:450-456.
31. de Leon MJ, Convit A, Wolf OT, et al. Prediction of cognitive decline in normal elderly subjects with 2-[(18)F]fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proc Natl Acad Sci U S A. 2001; 98:10966-10971.
32. Mungas D, Harvey D, Reed BR, et al. Longitudinal volumetric MRI change and rate of cognitive decline. Neurology. 2005;65:565-571.
33. Apostolova LG, Dutton RA, Dinov ID, et al. Conversion of mild cognitive impairment to Alzheimer disease predicted by hippocampal atrophy maps. Arch Neurol. 2006;63:693-699.
34. Richardson MP, Strange BA, Thompson PJ, et al. Pre-operative verbal memory fMRI predicts post-operative memory decline after left temporal lobe resection. Brain. 2004;127:2419-2426.
35. Adams MJ. Beginning to Read: Thinking and Learning About Print. Cambridge, Mass: MIT Press; 1990.
36. Snow CE, Burns SM, Griffin P, eds. Preventing Reading Difficulties in Young Children. Washington, DC: National Academy Press; 1998.
37. Ehri LC, Robbins C. Beginners need some decoding skills to read by analogy. Reading Res Quart. 1992; 27:13-26.
38. Gough PB, Tunmer WE. Decoding, reading and reading disability. Remedial Special Ed. 1986;7:6-10.
39. Richardson E, DiBenedetto B, Adler A. Use of the decoding skills test to study differences between good and poor readers. Adv Learning Behav Disabil. 1982; 1:25-74.
40. Snowling MJ. Dyslexia: A Cognitive Developmental Perspective. Oxford, UK: Basil Blackwell; 1987.
41. Bradley L, Bryant PE. Categorizing sounds and learning to read: a causal connection. Nature. 1983;30: 419-421.
42. Juel C. Learning to read and write: a longitudinal study of 54 children from first through fourth grades. J Ed Psychol. 1988;80:437-447.
43. Lundberg I, Olofsson A, Wall S. Reading and spelling skills in the first school years predicted from phonemic awareness skills in kindergarten. Scand J Psychol. 1980;21:159-173.
44. Muter V, Hulme C, Snowling M, Taylor S. Segmentation, not rhyming, predicts early progress in leaming to read. J Child Psychol Psychiatry. 1997;35: 293-310.
45. Naslund JC, Schneider W. Kindergarten letter knowledge, phonological skills, and memory processes: relative effects on early literacy. J Exp Child Psychol. 1996; 62:30-59.
46. Hoeft F, Ueno T, Hernandez A, et al. Predicting children's later decoding skills using behavioral, functional and structual neuroimaging measures. J Cog Neurosci. 2006(suppl):P206.
47. Kobayashi N, Meyler A, Keller TA, et al. Neuroimaging measures can prospectively predict future reading skills. Poster to be presented at: Neuroscience 2006; October 14-18, 2006; Atlanta.
48. Gredler GR. Early childhood screening for developmental and educational problems. In: Bracken BA, ed. The Psychoeducational Assessment of Preschool Children. Boston: Allyn & Bacon; 2000:399-411.
49. Shaw P, Greenstein D, Lerch J, et al. Intellectual ability and cortical development in children and adolescents. Nature. 2006;440:676-679.