Journal of Medical Systems

, Volume 36, Issue 2, pp 957–963

Detection of Abnormalities for Diagnosing of Children with Autism Disorders Using of Quantitative Electroencephalography Analysis

  • Ali Sheikhani
  • Hamid Behnam
  • Mohammad Reza Mohammadi
  • Maryam Noroozian
  • Mohammad Mohammadi
ORIGINAL PAPER

Abstract

Quantitative electroencephalography (qEEG) has been used as a tool for neurophysiologic diagnostic. We used spectrogram and coherence values for evaluating qEEG in 17 children (13 boys and 4 girls aged between 6 and 11) with autism disorders (ASD) and 11 control children (7 boys and 4 girls with the same age range). Evaluation of qEEG with statistical analysis demonstrated that alpha frequency band (8–13 Hz) had the best distinction level of 96.4% in relaxed eye-opened condition using spectrogram criteria. The ASD group had significant lower spectrogram criteria values in left brain hemisphere, (p < 0.01) at F3 and T3 electrodes and (p < 0.05) at FP1, F7, C3, Cz and T5 electrodes. Coherence values at 171 pairs of EEG electrodes indicated that there are more abnormalities with higher values in the connectivity of temporal lobes with other lobes in gamma frequency band (36–44 Hz).

Keywords

Autism disorders Quantitative Electroencephalography (qEEG) Spectrogram Coherence 

References

  1. 1.
    Baird, G., Charman, T., Cox, A., Baron-Cohen, S., Swettenham, J., Wheelwright, S., et al., Screening and Surveillance for autism and pervasive developmental disorders. Arch. Dis. Child. 84:468–475, 2001.CrossRefGoogle Scholar
  2. 2.
    Charman, T., and Baird, G., Practitioner review: Diagnosis of autism spectrum disorder in 2- and 3-year-old children. J. Child Psychol. Psychiatry 43:289–305, 2002.CrossRefGoogle Scholar
  3. 3.
    Rogers, S., Dignosis of autism before the age of 3. International Review of Mental Retardation 23:1–31, 2001.CrossRefGoogle Scholar
  4. 4.
    Akhondzadeh, S., Erfani, S., Mohammadi, M. R., Taheri-Doost, M., Amini, H., Gudarzi, S. S., and Yasamyet, M. T., Cyproheptadine in the treatment of autistic disorder: A double-blind placebo-controlled trial. J. Clin. Pharm. Ther. 29:145–150, 2004.CrossRefGoogle Scholar
  5. 5.
    Blaxill, M. F., What’s going on? The question of time trends in autism. Public Health Rep. 119:536–551, 2004.CrossRefGoogle Scholar
  6. 6.
    Coben, R., Clarke, A. R., Hudspeth, W., and Barry, R. J., EEG power and coherence in autistic spectrum disorder. Clin. Neurophysiol. 119:1002–1009, 2008.CrossRefGoogle Scholar
  7. 7.
    Fombonne, E., The epidemiology of autism: A review. Psychol. Med. 29:769–786, 1999.CrossRefGoogle Scholar
  8. 8.
    Sarbadhikari, S. N., and Chakrabarty, K., Chaos in the brain: A short review alluding to epilepsy, depression, exercise and lateralization. Med. Eng. Phys. 23:447–457, 2001.CrossRefGoogle Scholar
  9. 9.
    Jeong, J., Chase, J. H., Kim, S. Y., and Han, S. H., Nonlinear dynamics analysis of EEG in patients with Alzheimer’s disease and vascular dementia. J. Clin. Neurophysiol. 18:58–67, 2001.CrossRefGoogle Scholar
  10. 10.
    Hudetz, A. G., Effects of volatile anesthetics on interhemisphemispheric EEG cross-approximate entropy in the rat. Brain Res. 954:123–131, 2002.CrossRefGoogle Scholar
  11. 11.
    Tong, S., Bezerianos, A., Paul, J., Zhu, Y., and Thakor, N. V., Nonextensive entropy measure of EEG following brain injury from cardiac arrest. Physica, A 305:619–628, 2002.MATHCrossRefGoogle Scholar
  12. 12.
    Chez, M. G., Chang, M., Krasne, V., Coughlan, C., Kominsky, M., and Schwartz, A., Frequency of epileptiform EEG abnormalities in a sequential screening of autistic patients with no known clinical epilepsy from 1996 to 2005. Epilepsy Behav. 8:267–271, 2006.CrossRefGoogle Scholar
  13. 13.
    Rossi, P. G., Parmeggiani, A., Bach, V., Santucci, M., and Visconti, P., EEG features and epilepsy in patients with autism. Brain Dev. 17:169–174, 1995.CrossRefGoogle Scholar
  14. 14.
    Bashina, V. M., Gorbachevskaia, N. L., Simashkova, N. V., Iznak, A. F., Kozhushko, L. F., and Iakupova, L. P., The clinical, neurophysiologial and differential diagnostic aspects in a study of severe forms of early childhood autism. Zh Nevropatol Psikhiatr Im S S Korsakova 94:68–71, 1994.Google Scholar
  15. 15.
    Orekhova, E. V., Stroganova, T. A., Nygren, G., Tsetlin, M. M., Posikera, I. N., Gillberg, C., and Elam, M., Excess of High Frequency Electroencephalogram oscillation in boys with autism. Biol. Psychiatry 62:1022–1029, 2007.CrossRefGoogle Scholar
  16. 16.
    Dawson, G., Klinger, L. G., Panagiotides, H., Lewy, A., and Castello, P., Subgroups of autistic children based on social behavior display distinct patterns of brain activity. J. Abnorm. Child Psychol. 23:569–583, 1995.CrossRefGoogle Scholar
  17. 17.
    Stroganova, T. A., Nygren, G., Tsetlin, M. M., Posikera, I. N., Gillberg, C., Elam, M., and Orekhova, E. V., Abnormal EEG lateralization in boys with autism. Clin. Neurophysiol. 118:1842–1854, 2007.CrossRefGoogle Scholar
  18. 18.
    Oberman, L. M., Hubbard, E. M., McCleery, J. P., Altschuler, E. L., Ramachandran, V. S., and Pineda, J. A., EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Cogn. Brain Res. 24(2):190–198, 2005.CrossRefGoogle Scholar
  19. 19.
    American Psychiatric Association, Task force on DSM-IV Diagnostic and statistical manual of mental disorders, DSM-IV-IR 4th ed. American Psychiatric Association, Washington, DC, 2000.Google Scholar
  20. 20.
    Wechsler, D., Whechsler Intelligence Scale for children-Third Edition (WISC-III). The Psychological Corporation, San Antonio, 1991.Google Scholar
  21. 21.
    Oldfield, R. C., The assessment and analysis of handedness the Edinburgh inventory. Neuropsychologia 9:97–113, 1971.CrossRefGoogle Scholar
  22. 22.
    Jasper, H. H., Report of committee on methods of clinical examination in electroencephalography. Electroencephalogr. Clin. Neurophysiol. 10:370–375, 1958.CrossRefGoogle Scholar
  23. 23.
    Herbert, M. R., Ziegler, D. A., Makris, N., Filipek, P. A., Kemper, T. L., Normandin, J. J., et al., Localization of white matter volume increase in autism and developmental language disorder. Ann. Neurol. 55:530–540, 2004.CrossRefGoogle Scholar
  24. 24.
    Nunez, P. L., and Srinvasan, R., Electric fields of the brain; The Neurophysics of EEG, 2nd edition. Oxford University Press, New York, 2006.CrossRefGoogle Scholar
  25. 25.
    Tokmakei, M., and Erdogan, N., Investigation of the arterial stiffness on renal artery Doppler sonograms. J. Med. Syst. 33:101–106, 2009.CrossRefGoogle Scholar
  26. 26.
    Diaz, M., Application of Fourier linear spectral analyses to the characterization of smooth muscle contractile signals. J. Biochem. Biophys. Meth. 70:803–808, 2007.CrossRefGoogle Scholar
  27. 27.
    Hardalac, F., Yildirin, H., and Serchatlioglu, S., Determination of carotid disease with the application of STFT and CWT methods. Comput. Biol. Med. 37:785–792, 2007.CrossRefGoogle Scholar
  28. 28.
    Subha, D. P., Joseph, P. K., Acharya, U. R., and Lim, C. M., EEG signal analysis: A survey. J. Med. Syst. 34:195–212, 2010.Google Scholar
  29. 29.
    Tauscher, J., Fischer, P., Neumeister, A., Rappelsberger, P., and Kasper, S., Low frontal electroencephalographic coherence in neuroleptic-free schizophrenic patients. Biol. Psychiatry 44:438–447, 1998.CrossRefGoogle Scholar
  30. 30.
    Weiss, S., and Rappelsberger, P., Long-range EEG synchronization during word encoding correlates with successful memory performance. Cogn. Brain Res. 9:299–312, 2000.CrossRefGoogle Scholar
  31. 31.
    Tuncel, D., Dizibuyuk, A., Kiymik, M. K., Time frequency band coherence analysis between EEG and EMG activities in fatigue duration. J. Med. Syst. 34:131–138, 2010.Google Scholar
  32. 32.
    Metz, C. E., Basic principles of ROC analysis. Semin. Nuc. Med. 5:283–298, 1978.CrossRefGoogle Scholar
  33. 33.
    Abasolo, D., Homero, R., Espino, P., Alvavez, D., and Poza, J., Entropy analysis of the EEG background activity in Alzheimer’s desease patients. Physiol. Meas. 27:241–253, 2006.CrossRefGoogle Scholar
  34. 34.
    Lotte, F., Congedo, M., Lecuyer, A., Lamarche, F. and Arnaldi, B., A review of classification algorithms for EEG-based brain-computer interfaces. J. Neural Eng. R1–R13, 2007.Google Scholar
  35. 35.
    Chandana, S. R., Behen, M. E., Juhasz, C., Muzik, O., Rothermel, R. D., and Manager, T. J., Significant of abnormalities trajectory and asymmetry of cortical serotonin synthesis in autism. Int. J. Dev. Neurosci. 23:171–182, 2005.CrossRefGoogle Scholar
  36. 36.
    Lazarev, V. V., Pontes, A., and deAzevedo, L. C., Right hemisphere deficit in EEG photic driving reactivity in childhood autism. Int. J. Psychophysiol. 4:54–79, 2004.Google Scholar
  37. 37.
    Sheikhani, A., Behnam, H., Noroozian, M., Mohammadi, M. R., and Mohammadi, M., Abnormalities of quantitative electroencephalography in children with Asperger disorder in various conditions. Research in Autism Spectrum Disorders 3:538–546, 2009.CrossRefGoogle Scholar
  38. 38.
    Klimesch, W., and Schack, B., The functional significance of theta and upper alpha oscillations. Exp. Psychol. 52:99–108, 2005.CrossRefGoogle Scholar
  39. 39.
    Boddaert, N., and Zilbovicius, M., Temporal lobe dysfunction in childhood.autism. Brain 123:1838–1844, 2000.CrossRefGoogle Scholar
  40. 40.
    Cherkassky, V. L., Kana, R. K., Keller, T. A., and Just, M. A., Functional connectivity in a baseline resting-state network in autism. NeuroReport 17:1687–1690, 2006.CrossRefGoogle Scholar
  41. 41.
    Murias, M., Webb, S. J., Greenson, J., and Dawson, G., Resting state cortical connectivity reflected in EEG coherence in individuals with autism. Biol. Psychiatry 62:270–273, 2006.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Ali Sheikhani
    • 1
  • Hamid Behnam
    • 2
  • Mohammad Reza Mohammadi
    • 3
  • Maryam Noroozian
    • 3
  • Mohammad Mohammadi
    • 4
  1. 1.Biomedical Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Electrical Engineering DepartmentIran University of Science & TechnologyTehranIran
  3. 3.Psychiatry and Psychology Research Centre (PPRC), Roozbeh HospitalTehran University of Medical ScienceTehranIran
  4. 4.Iranian Behavioral and Psychological Center for Children and AdolescentsTehranIran

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