Alteration of White Matter Integrity in Dyslexic Children: Case-Control Study

Sung-Yeol Park; Jae Hyun Yoo; Minhwa Yang; Bobae Kim; Bung Nyun Kim

doi:10.4306/jknpa.2019.58.2.146

Journal List > J Korean Neuropsychiatr Assoc > v.58(2) > 1126755

Go to TopGo to Top Go to BottomGo to Bottom

TOOLS

Park, Yoo, Yang, Kim, and Kim: Alteration of White Matter Integrity in Dyslexic Children: Case-Control Study

Original Article

Journal of Korean Neuropsychiatric Association 2019; 58(2): 146-150.

Published online: 31 May 2019

DOI: https://doi.org/10.4306/jknpa.2019.58.2.146

Alteration of White Matter Integrity in Dyslexic Children: Case-Control Study

Sung-Yeol Park, MD¹, Jae Hyun Yoo, MD, PhD², Minhwa Yang, PhD³, Bobae Kim, M.Ed³, Bung Nyun Kim, MD, PhD¹

¹Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea.

²Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.

³Department of Education, Kookmin University, Seoul, Korea.

Address for correspondence: Bung Nyun Kim, MD, PhD. Department of Psychiatry, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea. Tel +82-2-2072-3647, Fax +82-2-747-2471, Kbn1@snu.ac.kr

Received 30 April 2019 Revised 9 May 2019 Accepted 16 May 2019

Korean Neuropsychiatric Association

Abstract

Objectives

To compare the white matter microstructure of dyslexic children with normal children using diffusion tensor imaging.

Methods

Twenty one dyslexic children and 24 normal control children were recruited in the second and third grade of elementary school students. The fractional anisotropy (FA) values of 20 representative white matter tracts were estimated from the diffusion tensor imaging data of each subject using the Johns Hopkins University-white matter tractography atlas to determine the difference in white matter integrity between the dyslexic children and normal children.

Results

Compared to the normal control group, the FA values of the left inferior longitudinal fasciculus [F(1,39)=5.908, p<0.05] and temporal part of the right superior longitudinal fasciculus [F(1,39)=7.328, p=0.010] were significantly higher in the dyslexic group and there was no significant difference in the other tracts.

Conclusion

In dyslexic children, compensatory pathways develop in the left inferior longitudinal fasciculus and in the temporal part of the right superior longitudinal fasciculus.

Keywords: Dyslexia, White matter tract, Diffusion tensor imaging, Diffusion tractography, Left inferior longitudinal fasciculus, Right superior longitudinal fasciculus

Figures and Tables

Table 1

Demographic characteristics of the participants

SD : Standard deviation, IQ : Intelligence quotient

Table 2

FA of WM tracts by Johns Hopkins University-WM tractography atlas

^* : p<0.05. FA : Fractional anisotropy, WM : White matter, IFOF : Inferior fronto-occipital fasciculus, ILF : Inferior longitudinal fasciculus, SLF : Superior longitudinal fasciculus

Notes

^{Conflicts of Interest} The authors have no financial conflicts of interest.

References

1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental disorders, 5th edition (DSM-5®). . Washington, DC: APA Publishing;2013.

2. Shaywitz SE. Dyslexia. N Engl J Med. 1998; 338:307–312.

3. Shaywitz SE, Shaywitz BA. Dyslexia (specific reading disability). Biol Psychiatry. 2005; 57:1301–1309.

4. Kim YO, Byun CS, Kang OR, Woo JH. A study on developing a “Dyslexia Screening Checklist”. Korea J Learn Disabil. 2014; 11:99–128.

5. Lyon GR, Shaywitz SE, Shaywitz BA. A definition of dyslexia. Ann Dyslexia. 2003; 53:1–14.

6. Norton ES, Beach SD, Gabrieli JD. Neurobiology of dyslexia. Curr Opin Neurobiol. 2015; 30:73–78.

7. Shaywitz SE, Shaywitz BA. Paying attention to reading: the neurobiology of reading and dyslexia. Dev Psychopathol. 2008; 20:1329–1349.

8. Hoeft F, McCandliss BD, Black JM, Gantman A, Zakerani N, Hulme C, et al. Neural systems predicting long-term outcome in dyslexia. Proc Natl Acad Sci U S A. 2011; 108:361–366.

9. Shaywitz BA, Shaywitz SE, Pugh KR, Mencl WE, Fulbright RK, Skudlarski P, et al. Disruption of posterior brain systems for reading in children with developmental dyslexia. Biol Psychiatry. 2002; 52:101–110.

10. Glasser MF, Rilling JK. DTI tractography of the human brain's language pathways. Cereb Cortex. 2008; 18:2471–2482.

11. Caylak E. Neurobiological approaches on brains of children with dyslexia: review. Acad Radiol. 2009; 16:1003–1024.

12. Kim A, Kim U, Hwang M, Yoo H. Test of Reading Achievement and Reading Cognitive Processes Ability (RA-RCP). Seoul: Hakjisa;2014.

13. Kim A, Kim U, Kim J, Jung D. Who are students with learning disabilities, dyslexia, low achievement, and learning support needs? Is the current educational support all right? : the role and task of special education. Korean Journal of Special Education. 2018; 53:1–21.

14. Park K, Yoon J, Park H, Kwon K. Korean Educational Development Institute-Wechsler Intelligence scale for children (KEDI-WISC). Seoul: Korean Educational Development Institute;2002.

15. Park K, Yoon J, Park H, Park H, Kwon K. Development of KEDIWISC, individual intelligence test for Korean children. Seoul: Korean Educational Development Institute;1986.

16. Grant DA, Berg EA. A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-type card-sorting problem. J Exp Psychol. 1948; 38:404–411.

17. Heaton RK. Wisconsin card sorting test manual. Odessa, FL: Psychological Assessment Resources;1981. p. 5–57.

18. Yoo HI, Lee J, Kang SH, Park EH, Jung J, Kim BN, et al. Standardization of the comprehensive attention test for the Korean children and adolescents. J Korean Acad Child Adolesc Psychiatry. 2009; 20:68–75.

19. Mori S, Wakana S, Nagae-Poetscher LM, van Zijl PCM. MRI atlas of human white matter. Am J NeuroRadiol. 2005; 27:1384–1385.

20. Mori S, Wakana S, van Zijl PCM, Nagae-Poetscher LM. MRI atlas of human white matter. 1st ed. Amsterdam: Elsevier Science;2005.

21. JHU ICBM tracts maxprob thr25 1mm. 2016. 01. cited 2016 Jan 21. Available from: https://neurovault.org/images/1403/.

22. Gorgolewski KJ, Varoquaux G, Rivera G, Schwarz Y, Ghosh SS, Maumet C, et al. NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Front Neuroinform. 2015; 9:8.

23. Herbet G, Zemmoura I, Duffau H. Functional anatomy of the inferior longitudinal fasciculus: from historical reports to current hypotheses. Front Neuroanat. 2018; 12:77.

24. Schlaffke L, Leemans A, Schweizer LM, Ocklenburg S, Schmidt-Wilcke T. Learning Morse code alters microstructural properties in the inferior longitudinal fasciculus: a DTI study. Front Hum Neurosci. 2017; 11:383.

25. Mandonnet E, Nouet A, Gatignol P, Capelle L, Duffau H. Does the left inferior longitudinal fasciculus play a role in language? A brain stimulation study. Brain. 2007; 130:623–629.

26. Madhavan KM, McQueeny T, Howe SR, Shear P, Szaflarski J. Superior longitudinal fasciculus and language functioning in healthy aging. Brain Res. 2014; 1562:11–22.

27. Urger SE, De Bellis MD, Hooper SR, Woolley DP, Chen SD, Provenzale J. The superior longitudinal fasciculus in typically developing children and adolescents: diffusion tensor imaging and neuropsychological correlates. J Child Neurol. 2015; 30:9–20.

28. Klarborg B, Skak Madsen K, Vestergaard M, Skimminge A, Jernigan TL, Baaré WF. Sustained attention is associated with right superior longitudinal fasciculus and superior parietal white matter microstructure in children. Hum Brain Mapp. 2013; 34:3216–3232.

29. Wolfers T, Onnink AM, Zwiers MP, Arias-Vasquez A, Hoogman M, Mostert JC, et al. Lower white matter microstructure in the superior longitudinal fasciculus is associated with increased response time variability in adults with attention-deficit/hyperactivity disorder. J Psychiatry Neurosci. 2015; 40:344–351.

30. Žarić G, Timmers I, Gerretsen P, Fraga González G, Tijms J, van der Molen MW, et al. Atypical white matter connectivity in dyslexic readers of a fairly transparent orthography. Front Psychol. 2018; 9:1147.

31. Shaywitz SE, Escobar MD, Shaywitz BA, Fletcher JM, Makuch R. Evidence that dyslexia may represent the lower tail of a normal distribution of reading ability. N Engl J Med. 1992; 326:145–150.

TOOLS

Similar articles