Russian version English version
Volume 14   Issue 2   Year 2019
Ustinin M.N., Rykunov S.D., Boyko A.I., Maslova O.A., Pankratova N.M.

Study of Attention Deficit and Hyperactivity Disorder Using the Method of Functional Tomography Based On Magnetic Encephalography Data

Mathematical Biology & Bioinformatics. 2019;14(2):517-532.

doi: 10.17537/2019.14.517.

References

 

  1. American academy of pediatrics. Clinical practical guideline: diagnosis and evaluation of the child with attention deficit / hyperactivity disorder. Pediatrics. 2000;105:1158–1170. doi: 10.1542/peds.105.5.1158
  2. Sáenz A., Villemonteix T., Isabelle Massat I. Structural and functional neuroimaging in attention-deficit/ hyperactivity disorder. Developmental Medicine & Child Neurology. 2019;61(4):399–405. doi: 10.1111/dmcn.14050
  3. Gorbachevskaia N.L., Zavadenko N.N., Iakupova L.P., Sorokin A.B., Suvorinova N.Iu., Grigor'eva N.V., Sokolova T.V. Fiziologiia cheloveka (Human Physiology). 1996;22(5):49–56 (in Russ.).
  4. Clarke A.R, Barry R.J, Johnstone S.J., McCarthy R., Selikowitz M. EEG development in Attention Deficit Hyperactivity Disorder: From child to adult. Clinical Neurophysiology. 2019;130:1256–1262. doi: 10.1016/j.clinph.2019.05.001
  5. American Psychiatric Association. In: Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Arlington, VA: American Psychiatric Publishing, 2013. P. 87–122.
  6. Pilina G.S., Shnayder N.A. Attention deficit hyperactivity disorder. Siberian Medical Review. 2017;1:107–114 (in Russ.). doi: 10.20333/2500136-2017-1-107-114
  7. Liechti M., Valko L., Muller U., Dohnert M., Drechsler R., Steinhausen H., Brandeis D. Diagnostic value of resting electroencephalogram in attention-deficit/ hyperactivity disorder across the lifespan. Brain Topogr. 2013;26:135–151. doi: 10.1007/s10548-012-0258-6
  8. Lau-Zhu A., Fritz A., McLoughlin G. Overlaps and distinctions between attention deficit/hyperactivity disorder and autism spectrum disorder in young adulthood: Systematic review and guiding framework for EEG-imaging research. Neuroscience and Biobehavioral Reviews. 2019;96:93–115. doi: 10.1016/j.neubiorev.2018.10.009
  9. Barry R., Clarke A., Johnstone S., McCarthy R., Selikowitz M. Electroencephalogram theta/beta ratio and arousal in AD/HD: evidence of independent processes. Biol. Psychiatry. 2009;66:398–401.
  10. Barry R., Clarke A., Johnstone S., McCarthy R., Selikowitz M., MacDonald B., Dupuy F. Caffeine effects on resting-state electrodermal levels in AD/HD suggest an anomalous arousal mechanism. Biol. Psychol. 2012;89:606–608.
  11. Clarke A.R., Barry R.J., McCarthy R., Selikowitz M., Magee C.A., Johnstone S.J., Croft R.J. Quantitative EEG in low IQ children with attention-deficit/hyperactivity disorder. Clin. Neurophysiol. 2006;117:1708–1714. doi: 10.1016/j.clinph.2006.04.015
  12. Lubar J. Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback Self Regul. 1991;16:201–225. doi: 10.1007/BF01000016
  13. Schulman J.J., Cancro R., Lowe S., Lu F., Walton K.D, Llinas R.R. Imaging of thalamocortical dysrhythmia in neuropsychiatry. Frontiers in Human Neuroscience. 2011;5. Article No. 69. doi: 10.3389/fnhum.2011.00069
  14. Pankratova N.M., Rykunov S.D., Boyko A.I., Molchanova D.A., Ustinin M.N. Localization of Encephalogram Spectral Features in Psychic Disorders. Mathematical Biology and Bioinformatics. 2018;13(2):322–336. doi: 10.17537/2018.13.322
  15. Llinás R.R., Ustinin M.N. Precise Frequency-Pattern Analysis to Decompose Complex Systems into Functionally Invariant Entities: U.S. Patent. US Patent App. Publ. 20160012011 A1. 01/14/2016.
  16. Llinás R.R., Ustinin M.N. Frequency-pattern functional tomography of magnetoencephalography data allows new approach to the study of human brain organization. Front. Neural Circuits. 2014;8. Article No. 43. doi: 10.3389/fncir.2014.00043
  17. Llinás R.R., Ustinin M.N., Rykunov S.D., Boyko A.I., Sychev V.V., Walton K.D., Rabello G.M., Garcia J. Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data. Front. Neurosci. 2015;9. Article No. 373. doi: 10.3389/fnins.2015.00373
  18. Llinás R., Ribary U., Jeanmonod D., Kronberg E., Mitra P. Thalamocortical dysrhythmia: A neurological and neuropsychiatric syndrome characterized by magnetoencephalography. Proceedings of the National Academy of Sciences of the United States of America. 1999;96:15222–15227. doi: 10.1073/pnas.96.26.15222
  19. Magnetism in medicine: a handbook. Eds. Andra W. and Nowak H. Wiley-VCH, 2007. 630 p. doi: 10.1002/9783527610174
  20. Cohen D., Schlapfer U., Ahlfors S., Hamalainen M., Halgren E. New Six-Layer Magnetically Shielded Room for MEG. In: Biomag 2002: Proceedings of 13th International Conference on Biomagnetism. Berlin, 2002. P. 919–921.
  21. Bork J., Hahlbohm H.D., Klein R., Schnabel A. The 8-layered magnetically shielded room of the PTB: Design and construction. In: Biomag 2000: Proceedings of the 12th International Conference on Biomagnetism. Springer, 2000.
  22. Ustinin M.N., Rykunov S.D., Boyko A.I., Maslova O.A., Walton K.D., Llinás R.R. Estimation of the Directions of Alpha Rhythm Elementary Sources Using the Method of Human Brain Functional Tomography Based On the Magnetic Encephalography Data. Mathematical Biology and Bioinformatics. 2018;13(2):426–436. doi: 10.17537/2018.13.426
  23. Sarvas J. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys. Med. Biol. 1987;32(1):11–22. doi: 10.1088/0031-9155/32/1/004
  24. Niso G., Rogers C., Moreau J.T., Chen L.Y., Madjar C., Das S., Bock E., Tadel F., Evans A., Jolicoeur P., Baillet S. OMEGA: The Open MEG Archive. Neuroimage. 2015;124:1182–1187. doi: 10.1016/j.neuroimage.2015.04.028
  25. Coffey E.B.J., Herholz S.C., Scala S., Zatorre R.J. Montreal Music History Questionnaire: a tool for the assessment of music-related experience. In: Presented at the The Neurosciences and Music IV: Learning and Memory Conference. Edinburgh, UK, 2011.
  26. Ustinin M.N., Sychev V.V., Walton K.D., Llinás R.R. New Methodology for the Analysis and Representation of Human Brain Function: MEGMRIAn. Mathematical Biology and Bioinformatics. 2014;9(2):464–481. doi: 10.17537/2014.9.464
  27. McCubbin J., Vrba J., Spear P., McKenzie D., Willis R., Loewen R., Robinson S.E., Fife A.A. Advanced electronics for the CTF MEG system. Neurol. Clin. Neurophysiol. 2004;2004:69.
  28. Frigo M., Johnson S.G. The Design and Implementation of FFTW3. Proceedings of the IEEE. 2005;93(2):216–231. doi: 10.1109/JPROC.2004.840301
  29. Belouchrani A., Abed-Meraim K., Cardoso J.-F., Moulines E. A blind source separation technique using second-order statistics. IEEE Trans. Signal Processing. 1997;45:434–444. doi: 10.1109/78.554307
  30. Rykunov S.D., Ustinin M.N., Polyanin A.G., Sychev V.V., Llinás R.R. Software for the Partial Spectroscopy of Human Brain. Mathematical Biology and Bioinformatics. 2016;11(1):127–140. doi: 10.17537/2016.11.127
  31. Fischl B. Automatically Parcellating the Human Cerebral Cortex. Cereb. Cortex. 2004;14(1):11–22. doi: 10.1093/cercor/bhg087
  32. Desikan R.S., Ségonne F., Fischl B., Quinn B.T., Dickerson B.C., Blacker D., Buckner R.L., Dale A.M., Maguire R.P., Hyman B.T., Albert M.S., Killiany R.J. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31(3):968–980. doi: 10.1016/j.neuroimage.2006.01.021
  33. Fischl B., Salat D.H., Van Der Kouwe A.J.W., Makris N., Ségonne F., Quinn B.T., Dale A.M. Sequence-independent segmentation of magnetic resonance images. Neuroimage. 2004;23(1):69–84. doi: 10.1016/j.neuroimage.2004.07.016
Table of Contents Original Article
Math. Biol. Bioinf.
2019;14(2):517-532
doi: 10.17537/2019.14.517
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)
References

 

  Copyright IMPB RAS © 2005-2022