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Том 18   Выпуск 2   Год 2023
Кондрахин П.Ю.1, Колпаков Ф.А.1,2,3

Многоуровневая математическая модель эпилептических припадков

Математическая биология и биоинформатика. 2023;18(2):479-516.

doi: 10.17537/2023.18.479.

Список литературы

  1. Devinsky O., Vezzani A., O’Brien T.J., Jette N., Scheffer I.E., de Curtis M., Perucca P. Epilepsy. Nature Reviews Disease Primers. 2018;4(1). doi: 10.1038/nrdp.2018.24
  2. Chen Z., Brodie M.J., Liew D., Kwan P. Treatment Outcomes in Patients With Newly Diagnosed Epilepsy Treated With Established and New Antiepileptic Drugs. JAMA Neurology. V. 2018;75(3):279. doi: 10.1001/jamaneurol.2017.3949
  3. Golomb. D., Amitai Y. Propagating Neuronal Discharges in Neocortical Slices: Computational and Experimental Study. Journal of Neurophysiology. 1997;78(3):1199–1211. doi: 10.1152/jn.1997.78.3.1199
  4. Compte A., Sanchez-Vives M.V., McCormick D.A., Wang X.-J. Cellular and Network Mechanisms of Slow Oscillatory Activity (<1 Hz) and Wave Propagations in a Cortical Network Model. Journal of Neurophysiology. 2003;89(5):2707–2725. doi: 10.1152/jn.00845.2002
  5. Bazhenov M., Timofeev I., Fröhlich F., Sejnowski T.J. Cellular and network mechanisms of electrographic seizures. Drug Discovery Today: Disease Models. 2008;5(1):45–57. doi: 10.1016/j.ddmod.2008.07.005
  6. Zhang H., Su J., Wang Q., Liu Y., Good L., Pascual J.M. Predicting seizure by modeling synaptic plasticity based on EEG signals - a case study of inherited epilepsy. Communications in Nonlinear Science and Numerical Simulation. 2018;56:330–343. doi: 10.1016/j.cnsns.2017.08.020
  7. Proix T., Bartolomei F., Guye M., Jirsa V.K. Individual brain structure and modelling predict seizure propagation. Brain. 2017;140(3):641–654. doi: 10.1093/brain/awx004
  8. Sanz L.P., Knock S.A., Woodman M.M., Domide L., Mersmann J., McIntosh A.R., Jirsa V.K. The Virtual Brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics. 2013;7(10). doi: 10.3389/fninf.2013.00010
  9. Makhalova J., Medina Villalon S., Wang H., Giusiano B., Woodman M., Bénar C., Guye M., Jirsa V., Bartolomei F. Virtual epileptic patient brain modeling: Relationships with seizure onset and surgical outcome. Epilepsia. 2022;63(8):1942–1955. doi: 10.1111/epi.17310
  10. Löscher W., Potschka H., Sisodiya S.M., Vezzani A. Drug Resistance in Epilepsy: Clinical Impact, Potential Mechanisms, and New Innovative Treatment Options. Pharmacological Reviews. 2020;72(3):606–638. doi: 10.1124/pr.120.019539
  11. Depannemaecker D., Ivanov A., Lillo D., Spek L., Bernard C., Jirsa V.K. A unified physiological framework of transitions between seizures, sustained ictal activity and depolarization block at the single neuron level. Journal of Computational Neuroscience. 2022;50(1):33–49. doi: 10.1007/s10827-022-00811-1
  12. Chizhov A.V., Zefirov A.V., Amakhin D.V., Smirnova E.Yu., Zaitsev A.V. Minimal model of interictal and ictal discharges "Epileptor-2". Computational Biology. 2018;14(5). doi: 10.1371/journal.pcbi.1006186
  13. Kutumova E., Kiselev I., Sharipov R., Lifshits G., Kolpakov F. Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease. Frontiers in Physiology. 2021;12. doi: 10.3389/fphys.2021.746300
  14. Akberdin I.R., Kiselev I.N., Pintus S.S., Sharipov R.N., Vertyshev A.Y., Vinogradova O.L. Popov D.V., Kolpakov F.A. A Modular Mathematical Model of Exercise-Induced Changes in Metabolism, Signaling, and Gene Expression in Human Skeletal Muscle. International Journal of Molecular Sciences. 2021;22(19):10353. doi: 10.3390/ijms221910353
  15. Afonyushkin V.N., Akberdin I.R., Kozlova Y.N., Schukin I.A., Mironova T.E., Bobikova A.S., Cherepushkina V.S., Donchenko N.A., Poletaeva Y.E., Kolpakov F.A. Multicompartmental Mathematical Model of SARS-CoV-2 Distribution in Human Organs and Their Treatment. Mathematics. 2022;10(11):1925. doi: 10.3390/math10111925
  16. Kutumova E.O., Kiselev I.N., Sharipov R.N., Lavrik I.N., Kolpakov F.A. A modular model of the apoptosis machinery. Advances in Experimental Medicine and Biology. 2012;736:235–245. doi: 10.1007/978-1-4419-7210-1_13
  17. Kolpakov F., Akberdin I., Kashapov T., Kiselev I., Kolmykov S., Kondrakhin Y., Kutumova E., Mandrik N., Pintus S., Ryabova A., Sharipov R., Yevshin I., Kel A. BioUML: an integrated environment for systems biology and collaborative analysis of biomedical data. Nucleic Acids Research. 2019;47(W1):W225–W233. doi: 10.1093/nar/gkz440
  18. Kolpakov F., Akberdin I., Kiselev I., Kolmykov S., Kondrakhin Y., Kulyashov M., Kutumova E., Pintus S., Ryabova A., Sharipov R., Yevshin I., Zhatchenko S., Kel A. BioUML–towards a universal research platform. Nucleic Acids Research. 2022;50(W1):W124–W131. doi: 10.1093/nar/gkac286
  19. Hindmarsh A.C., Brown P.N., Grant K.E., Lee S.L., Serban R., Shumaker D.E., Woodward C.S. SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers. ACM Transactions on Mathematical Software. 2005;31(3):363–396. doi: 10.1145/1089014.1089020
  20. Hairer E., Wanner G. Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems. Berlin: Springer-Verlag, 1996. 614 p. doi: 10.1007/978-3-642-05221-7
  21. Dormand J.R., Prince P.J. A family of embedded Runge-Kutta formulae. Journal of Computational and Applied Mathematics. 1980;6(1):19–26. doi: 10.1016/0771-050X(80)90013-3
  22. Novère N., Hucka M., Mi H., Moodie S., Schreiber F., Sorokin A., Demir E., Wegner K., Aladjem M.I., Wimalaratne S.M., Bergman F.T., Gauges R., Ghazal. P., Kawaji H., Li L., Matsuoka Y., Villéger A., Boyd S.E., Calzone L., Courtot M, Dogrusoz U., Freeman T.C., Funahashi A., Ghosh S., Jouraku A., Kim S., Kolpakov F., Luna A., Sahle S., Schmidt E., Watterson S., Wu G., Goryanin I., Kell D.B., Sander C., Sauro H., Snoep J.L., Kohn K., Kitano H. The Systems Biology Graphical Notation. Nature Biotechnology. 2009;27(8):735–741. doi: 10.1038/nbt.1558
  23. Hernández A.I., Le Rolle V., Defontaine A., Carrault G. A multiformalism and multiresolution modelling environment: application to the cardiovascular system and its regulation. Philosophical Transactions of the Royal Society. 2009;367(1908):4923–4940. doi: 10.1098/rsta.2009.0163
  24. Moosavi S.A., Jirsa V.K., Truccolo W., Critical dynamics in the spread of focal epileptic seizures: Network connectivity, neural excitability and phase transitions. PLOS ONE. 2022;17(8). doi: 10.1371/journal.pone.0272902
  25. 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
  26. Jirsa V.K., Stacey W.C., Quilichini P.P., Ivanov A.I., Bernard C. On the nature of seizure dynamics. Brain. 2014;137(8):2210–2230. doi: 10.1093/brain/awu133
  27. Jirsa V.K., Proix T., Perdikis D., Woodman M.M., Wang H., Gonzalez-Martinez J., Bernard C., Bénar C., Guye M., Chauvel P., Bartolomei F. The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread. NeuroImage. 2017;145:377–388. doi: 10.1016/j.neuroimage.2016.04.049
  28. Wei Y., Ullah G., Ingram J., Schiff S.J. Oxygen and seizure dynamics: II. Computational modeling. Journal of Neurophysiology. 2014;112(2):213–223. doi: 10.1152/jn.00541.2013
  29. Izhikevich E.M. Which model to use for cortical spiking neurons? IEEE Transactions on Neural Networks. 2004;15(5):1063–1070. doi: 10.1109/TNN.2004.832719
  30. Smirnova E.Y., Chizhov A.V., Zaitsev A.V. Presynaptic GABAB receptors underlie the antiepileptic effect of low-frequency electrical stimulation in the 4-aminopyridine model of epilepsy in brain slices of young rats. Brain Stimulation. 2020;13(5):1387–1395. doi: 10.1016/j.brs.2020.07.013
  31. Kapus G., Székely J.I., Durand J., Ruiz A., Tarnawa I. AMPA receptor antagonists, GYKI 52466 and NBQX, do not block the induction of long-term potentiation at therapeutically relevant concentrations. Brain Research Bulletin. 2000;52(6):511–517. doi: 10.1016/S0361-9230(00)00288-4
  32. Parada J., Czuczwar S.J., Turski W.A. NBQX does not affect learning and memory tasks in mice: a comparison with D-CPPene and ifenprodil. Cognitive Brain Research. 1992;1(1):67–71. doi: 10.1016/0926-6410(92)90006-D
  33. Pitsikas N., Rigamonti A.E., Cella S.G., Muller E.E. The non-NMDA receptor antagonist NBQX does not affect rats performance in the object recognition task. Pharmacological Research. 2002;45(1):43–46. doi: 10.1006/phrs.2001.0898
  34. Rogawski M.A. AMPA receptors as a molecular target in epilepsy therapy. Acta Neurologica Scandinavica. 2013;127:9–18. doi: 10.1111/ane.12099
  35. Earnshaw B.A., Bressloff P.C. Biophysical model of AMPA receptor trafficking and its regulation during long-term potentiation/long-term depression. Journal of Neuroscience. 2006;26(47):12362–12373. doi: 10.1523/JNEUROSCI.3601-06.2006
  36. Proix T., Bartolomei F., Chauvel P., Bernard C., Jirsa V.K. Permittivity Coupling across Brain Regions Determines Seizure Recruitment in Partial Epilepsy. Journal of Neuroscience. 2014;34(45):15009–15021. doi: 10.1523/JNEUROSCI.1570-14.2014
  37. Izhikevich E.M. Neural excitability, spiking and bursting. International Journal of Bifurcation and Chaos in Applied Sciences and Engineering. 2000;10(6):1171–1266. doi: 10.1142/S0218127400000840
  38. Jirsa V.K., Stacey W.C., Quilichini P.P., Ivanov A.I., Bernard C. On the nature of seizure dynamics. Brain. 2014;137(8):2210–2230. doi: 10.1093/brain/awu133
  39. Saggio M.L., Spiegler A., Bernard C., Jirsa V.K. Fast–Slow Bursters in the Unfolding of a High Codimension Singularity and the Ultra-slow Transitions of Classes. Journal of Mathematical Neuroscience. 2017;7(1). doi: 10.1186/s13408-017-0050-8
  40. Blenkinsop A., Valentin A., Richardson M.P., Terry J.R. The dynamic evolution of focal-onset epilepsies--combining theoretical and clinical observations. European Journal of Neuroscience. 2012;36(2):2188–2200. doi: 10.1111/j.1460-9568.2012.08082.x
  41. de Curtis M., Uva L., Gnatkovsky V., Librizzi L. Potassium dynamics and seizures: Why is potassium ictogenic? Epilepsy Research. 2018;143:50–59. doi: 10.1016/j.eplepsyres.2018.04.005
  42. Kofuji P., Newman E.A. Potassium buffering in the central nervous system. Neuroscience. 2004;129(4):1043–1054. doi: 10.1016/j.neuroscience.2004.06.008
  43. Traynelis S.F., Dingledine R. Potassium-induced spontaneous electrographic seizures in the rat hippocampal slice. Journal of Neurophysiology. 1988;59(1):259–276. doi: 10.1152/jn.1988.59.1.259
  44. Avoli M., D’Antuono M., Louvel J., Köhling R., Biagini G., Pumain R., D’Arcangelo G., Tancredi V. Network and pharmacological mechanisms leading to epileptiform synchronization in the limbic system in vitro. Progress in Neurobiology. 2002;68(3):167–207. doi: 10.1016/S0301-0082(02)00077-1
  45. Librizzi L., Losi G., Marcon, I., Sessolo M., Scalmani P., Carmignoto G., de Curtis M. Interneuronal Network Activity at the Onset of Seizure-Like Events in Entorhinal Cortex Slices. Journal of Neuroscience. 2017;37(43):10398–10407. doi: 10.1523/JNEUROSCI.3906-16.2017
  46. Antonio L.L., Anderson M.L., Angamo E.A., Gabriel S., Klaft Z.-J., Liotta A., Salar S., Sandow N., Heinemann U. In vitro seizure like events and changes in ionic concentration. Journal of Neuroscience Methods. 2016;260:33-44. doi: 10.1016/j.jneumeth.2015.08.014
  47. Raimondo J.V., Burman R.J., Katz A.A., Akerman C.J. Ion dynamics during seizures. Frontiers in Cellular Neuroscience. 2015;9. doi: 10.3389/fncel.2015.00419
  48. Hanada T. Ionotropic Glutamate Receptors in Epilepsy: A Review Focusing on AMPA and NMDA Receptors. Biomolecules. 2020;10(3):464–485. doi: 10.3390/biom10030464
  49. Nusser Z., Lujan R., Laube G., Roberts J., Molnar D.B., Somogyi P. Cell Type and Pathway Dependence of Synaptic AMPA Receptor Number and Variability in the Hippocampus. Neuron. 1998;21(3):545–559. doi: 10.1016/S0896-6273(00)80565-6
  50. Cottrell J.R., Dubé G.R., Egles C., Liu G. Distribution, Density, and Clustering of Functional Glutamate Receptors Before and After Synaptogenesis in Hippocampal Neurons. Journal of Neurophysiology. 2000;84(3):1573–1587. doi: 10.1152/jn.2000.84.3.1573
  51. Tanaka J., Matsuzaki M., Tarusawa E., Momiyama A., Molnar E., Kasai H., Shigemoto R. Number and Density of AMPA Receptors in Single Synapses in Immature Cerebellum. Journal of Neuroscie. 2005;25(4):799–807. doi: 10.1523/JNEUROSCI.4256-04.2005
  52. Petersen C.C., Malenka R.C., Nicoll R.A., Hopfield J.J. All-or-none potentiation at CA3-CA1 synapses. Proceedings of the National Academy of Sciences. 1998;95(8):4732–4737. doi: 10.1073/pnas.95.8.4732
  53. O’Connor D.H., Wittenberg G.M., Wang S.S.-H. Graded bidirectional synaptic plasticity is composed of switch-like unitary events. Proceedings of the National Academy of Sciences. 2005;102(27):9679–9687. doi: 10.1073/pnas.0502332102
  54. Bliss T.V., Lømo T. Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. Journal of Physiology. 1973;232(2):331–356. doi: 10.1113/jphysiol.1973.sp010273
  55. Hanse E., Gustafsson B. Postsynaptic, but not presynaptic, activity controls the early time course of long-term potentiation in the dentate gyrus. Journal of Neuroscience. 1992;12(8):3226–3240. doi: 10.1523/JNEUROSCI.12-08-03226.1992
  56. Dudek S.M., Bear M.F. Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-D-aspartate receptor blockade. Proceedings of the National Academy of Sciences. 1992;89(10):4363–4367. doi: 10.1073/pnas.89.10.4363
Содержание
Оригинальная статья
Мат. биол. и биоинф.
2023;18(2):479-516
doi: 10.17537/2023.18.479
опубликована на рус. яз.

Аннотация (рус.)
Аннотация (англ.)
Полный текст (рус., pdf)
Список литературы

 
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