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Volume 15   Issue 2   Year 2020
Ustinin M.N., Rykunov S.D., Boyko A.I.

Correlation of the Brain Compartments in the Attention Deficit and Hyperactivity Disorder Calculated by the Method of Virtual Electrodes from Magnetic Encephalography Data

Mathematical Biology & Bioinformatics. 2020;15(2):471-486.

doi: 10.17537/2020.15.471.

References

  1. Saad J.F., Griffiths K.R., Korgaonkar M.S. A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder. Front. Integr. Neurosci. 2020;14:31. doi: 10.3389/fnint.2020.00031
  2. Sato J.R., Hoexter M.Q., Castellanos X.F., Rohde L.A. Abnormal brain connectivity patterns in adults with ADHD: a coherence study. PLoS One. 2012;7(9):e45671. doi: 10.1371/journal.pone.0045671
  3. Brockwell P.J., Davis R.A. Time Series: Theory and Methods. 2nd edition. New York: Springer-Verlag, 1991.
  4. Sörös, P., Hoxhaj, E., Borel, P., Borel P., Sadohara C., Feige B., Matthies S., Müller H.H.O., Bachmann K., Schulze M., Philipsen A. Hyperactivity/restlessness is associated with increased functional connectivity in adults with ADHD: a dimensional analysis of resting state fMRI. BMC Psychiatry. 2019;19:43. doi: 10.1186/s12888-019-2031-9
  5. Sudre G., Szekely E., Sharp W., Kasparek S., Shaw P. Multimodal mapping of the brain’s functional connectivity and the adult outcome of attention deficit hyperactivity disorder. PNAS. 2017;114(44):11787–11792. doi: 10.1073/pnas.1705229114
  6. Robinson S.E., Vrba J. Functional neuroimaging by synthetic aperture magnetometry (SAM). In: Recent Advances in Biomagnetism: Proceedings of the 11th International Conference on Biomagnetism. Eds. Yoshimoto T., Kotani M., Kuriki S., Karibe H., Nakasato N. Sendai: Tohoku Univ. Press, 1998. P. 302–305.
  7. Litvak V., Eusebio A., Jha A., Oostenveld R., Barnes G.R., Penny W.D., Zrinzo L., Hariz M.I., Limousin P., Friston K.J. et al. Optimized beamforming for simultaneous MEG and intracranial local field potential recordings in deep brain stimulation patients. Neuroimage. 2010;50(4–3):1578–1588. doi: 10.1016/j.neuroimage.2009.12.115
  8. Glasser M., Smith S., Marcus D., Andersson J.L.R., Auerbach E.J., Behrens T.E.J., Coalson T.S., Harms M.P., Jenkinson M., Moeller S. et al. The Human Connectome Project's neuroimaging approach. Nat. Neurosci. 2016;19:1175–1187. doi: 10.1038/nn.4361
  9. Michelini G., Jurgiel J., Bakolis I., Cheung C.H.M., Asherson P., Loo S.K., Jonna Kuntsi J., Mohammad-Rezazadeh I. Atypical functional connectivity in adolescents and adults with persistent and remitted ADHD during a cognitive control task. Transl. Psychiatry. 2019;9:137. doi: 10.1038/s41398-019-0469-7
  10. Nunez P.L., Srinivasan R., Westdorp A.F., Wijesinghe R.S., Tucker D.M., Silberstein R.B., Cadusch P.J. EEG coherency. I: Statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. Electroencephalogr. Clin. Neurophysiol. 1997;103:499–515. doi: 10.1016/S0013-4694(97)00066-7
  11. Palva S., Palva J.M. Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs. Trends Cogn. Sci. 2012;16:219–230. doi: 10.1016/j.tics.2012.02.004
  12. Jang K.-M., Kim M.-S., Kim D.-W. The Dynamic Properties of a Brain Network During Spatial Working Memory Tasks in College Students With ADHD Traits. Front. Hum. Neurosci. 2020;14:580813. doi: 10.3389/fnhum.2020.580813
  13. Lachaux J.P., Rodriguez E., Martinerie J., Varela F.J. Measuring phase synchrony in brain signals. Hum. Brain Mapp. 1999;8:194–208. doi: 10.1002/(SICI)1097-0193(1999)8:4<194::AID-HBM4>3.0.CO;2-C
  14. Choi J.W., Jang K.M., Jung K.Y., Kim M.S., Kim K.H. Reduced theta-band power and phase synchrony during explicit verbal memory tasks in female, non-clinical individuals with schizotypal traits. PLoS One. 2016;11:e0148272. doi: 10.1371/journal.pone.0148272
  15. 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
  16. 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 and Bioinformatics. 2019;14(2):517–532. doi: 10.17537/2019.14.517
  17. 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
  18. Magnetism in medicine: a handbook. Eds. Andra W. and Nowak H. Wiley-VCH, 2007. 630 p. doi: 10.1002/9783527610174
  19. 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.
  20. 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.
  21. Llinás R.R., Ustinin M., Rykunov S., Walton K.D., Rabello G.M., Garcia J., Boyko A., and Sychev V. Noninvasive muscle activity imaging using magnetography. Proceedings of the National Academy of Sciences of the United States of America. 2020;117(9):4942–4947. doi: 10.1073/pnas.1913135117
  22. 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;8:43. doi: 10.3389/fncir.2014.00043
  23. 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;9:373. doi: 10.3389/fnins.2015.00373
  24. 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
  25. 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
  26. 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.
  27. 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
  28. 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.
  29. 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
  30. 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
  31. Rykunov S.D., Rykunova E.D., Boyko A.I., Ustinin M.N. VirtEl - Software for Magnetic Encephalography Data Analysis by the Method of Virtual Electrodes. Mathematical Biology and Bioinformatics. 2019;14(1):340–354. doi: 10.17537/2019.14.340
  32. Fischl B. Automatically Parcellating the Human Cerebral Cortex. Cereb. Cortex. 2004;14(1):11–22. doi: 10.1093/cercor/bhg087
  33. 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
  34. 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;23:69–84. doi: 10.1016/j.neuroimage.2004.07.016
Table of Contents
Original Article
Math. Biol. Bioinf.
2020;15(2):471-486
doi: 10.17537/2020.15.471
published in Russian

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

 
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