V. F. Sazonov – Ph.D. (Biol.), Associate Professor, Department of Biology and Its Teaching Methods, Ryazan State University named after S.A. Esenin (Ryazan, Russia)
E-mail: kineziolog@mail.ru
I. V. Sazonov – Director, “Tri-W” Ltd. (Ryazan, Russia)
E-mail: mail@3w-site.ru
A. V. Grishaev – Post-graduate Student, Department of Ecology and Resource Using, Ryazan State University named after S.A. Esenin (Ryazan, Russia)
E-mail: ecology.ag@yandex.ru
In the article two different approaches to the analysis of changes in neuronal activity were counter opposed: structural and functional. The authors associate the structural approach with the concept of “plasticity” and the functional one with the concept of “regimity”. The conclusion is that the functional specification and neural network modeling and neural states of interneuron interactions make it possible to limit the functional approach to regime, abstracting from plastic structural rearrangements. The proposed regimity-functional approach is implemented in a series of computer programs “Impulsation” and “Neuroimpulsation”. These programs simulate interneuron relationships and visualise dynamics of neurons. The regimes of neurons and synapses thus systematized and described can be included in the terms of reference for developers of neurosimulators. Therefore, we set a task of studying the neurophysiological correspondence between the simulated virtual modes of “quasineurons” in computer models, and the actual neurons in the nervous system. Thus, we can assume that the use of the threshold principle in neuromodeling, supplemented by the mode of operation of neurons and synapses, can even more closely approximate the activity of imitation virtual “quasineuron” models of small neural networks to the work of real neural structures. The correctness, adequacy and relevance of neuromodels will be the higher, the more accurately they reproduce all the basic modes of operation of neurons and synapses and, in particular, those that are presented and described in this article.
Sazonov V.F., Sazonov I.V., Grishaev A.V. The concept of regimity in neuron work as a functional alternative to the structural plasticity in the computer simulation of interneuronal interactions. Neurocomputers. 2020. Vol. 22. No. 5. P. 43–53. DOI: 10.18127/j19998554-202005-04. (in Russian)
- Antoshkin V.A., Sazonov V.F., Prolygina A.A. Interaktivnaya komp'yuternaya model' mezhnejronnykh vzaimodejstvij. Mezhvuz. sb. nauch. trudov «Informatika i prikladnaya matematika». 2014. № 20. S. 3–5. (in Russian)
- Antoshkin V.A., Sazonov V.F. Komp'yuternaya model' mezhnejronnykh vzaimodejstvij. Materialy nauch.-praktich. konf. prepodavatelej RGU imeni S.A. Esenina po itogam 2014/15 ucheb. goda «Ryazanskij gosudarstvennyj universitet imeni S.A. Esenina: vekovaya istoriya kak fundament dal'nejshego razvitiya (100-letnemu yubileyu RGU imeni S.A. Esenina posvyashchaetsya)». Otv. redaktor M.N. Makhmudov. Ryazan': Ryazanskij gosudarstvennyj universitet imeni S.A. Esenina. 2015. S. 448–454. (in Russian)
- Antoshkin V.A., Sazonov V.F., Plaksin O.Yu. Razrabotka komp'yuternoj modeli mezhnejronnykh vzaimodejstvij v srede Qt. Mezhvuz. sb. nauch. trudov «Informatika i prikladnaya matematika». 2015. № 21. S. 7–11. (in Russian)
- Balaban P.M., Korshunova T.A. Setevye, kletochnye i molekulyarnye mekhanizmy plastichnosti v prostykh nervnykh sistemakh. Uspekhi fiziologicheskikh nauk. 2011. T. 42. № 4. S. 3–19. (in Russian)
- Kotel'nikov V.A. O propusknoj sposobnosti «efira» i provoloki v elektrosvyazi. Uspekhi fizicheskikh nauk. 2006. № 7. S. 762–770.
- Nikitin E.S., Balaban P.M. Kompartmentalizatsiya nesinapticheskoj plastichnosti v nejronakh na subkletochnom urovne. Zhurnal vysshej nervnoj deyatel'nosti. 2013. T. 63. № 3. S. 295–302. (in Russian)
- Sazonov V.F. Impul'satsiya [Elektronnyj resurs]. Kineziolog. 2009–2017: [sajt]. Data obnovleniya: 06.03.2017. URL: http://kineziolog.su/ content/impulsatsiya. (in Russian)
- Sazonov V.F. Impul'satsiya – komp'yuternaya uchebnaya model' nervnogo tsentra (nejroseti) [Elektronnyj resurs]. Kineziolog, 2009–2017: [sajt]. Data obnovleniya: 06.03.2017. URL: http://kineziolog.su/content/%C2%ABimpulsatsiya%C2%BB-kompyute rnaya-uchebnaya-model-nervnogo-tsentra-neiroseti. (in Russian)
- Sazonov V.F., Sazonov I.V., V'yal' D.V. Interaktivnoe dinamicheskoe vizualizirovannoe modelirovanie dvizheniya nervnogo vozbuzhdeniya v nejronnoj seti s pomoshch'yu komp'yuternoj programmy «Impul'satsiya». Trudy 7-j Mezhdunar. mezhdistsiplinarnogo kongressa «Nejronauka dlya meditsiny i psikhologii». Pod red. E.V. Losevoj, N.A. Loginovoj. M.: MAKS Press. 2011. S. 369–370. (in Russian)
- Sazonov V.F., Sazonov I.V., V'yal' D.V. Modelirovanie mezhnejronnykh otnoshenij v rezhime onlajn s pomoshch'yu Web-versii komp'yuternoj programmy-simulyatora nejrosetej «Impul'satsiya-3w». Trudy 7-j Mezhdunar. mezhdistsiplinarnogo kongressa «Nejronauka dlya meditsiny i psikhologii». Pod red. E.V. Losevoj, N.A. Loginovoj. M.: MAKS Press. 2012. S. 352–353. (in Russian)
- Sazonov V.F., Sazonov I.V., V'yal' D.V. Nejrofiziologicheskie postulaty dlya komp'yuternogo modelirovaniya plastichnosti nervnoj sistemy. Nejrokomp'yutery: razrabotka, primenenie. 2014. № 7. S. 46–52. (in Russian)
- Sazonov V.F., Sazonov I.V., V'yal' D.V. Nejrofiziologicheskie printsipy v komp'yuternom modelirovanii samoorganizuyushchejsya samoobuchayushchejsya samoreguliruyushchejsya sistemy. Materialy XXI S''ezda Fiziologicheskogo obshchestva im. I.P. Pavlova. M.-Kaluga. 2010. S. 534. (in Russian)
- Sazonov V.F., Sazonov I.V., V'yal' D.V. Pachechnaya impul'satsiya kak forma plastichnosti v mezhnejronnykh vzaimodejstviyakh. Nauchnye trudy IV s''ezda fiziologov SNG. 2014. S. 253–254. (in Russian)
- Sazonov V.F. Sovremennaya kontseptsiya nejrofiziologii. Proceedings of 1st European Conference on Biology and Medical Sciences (May 22, 2014). Vienna, OR: «East West» Association for Advanced Studies and Higher Education GmbH, Vienna. 2014. P. 66–73. (in Russian)
- Svidetel'stvo o gosudarstvennoj registratsii programmy dlya EVM № 2015616965. Nejroimpul'satsiya 1.0. V.A. Antoshkin, V.F. Sazonov. Data gos. registratsii v Reestre programm dlya EVM 26.06.2015. (in Russian)
- Sitnikova E.Yu. Strukturno-funktsional'naya organizatsiya somatosensornoj sistemy v norme i pri absansepilep-sii: Avtoref. diss. ... dokt. biol. nauk. M. 2014. (in Russian)
- Cherepanov F.M. Issledovatel'skij simulyator nejronnykh setej, obzor ego prilozhenij i vozmozhnosti primeneniya dlya sozdaniya sistemy diagnostiki zabolevanij serdechno-sosudistoj sistemy. Sovremennye problemy nauki i obrazovaniya. 2013. № 1. URL: https://science-education.ru/ru/article/view?id=8392 (data obrashcheniya: 14.02.2017). (in Russian)
- Shennon K. Raboty po teorii informatsii i kibernetike. M.: Izd-vo inostrannoj literatury. 1963. (in Russian)
- Bean B.P. The action potential in mammalian central neurons. Nature Reviews. Neuroscience. 2007. V. 8. № 6. P. 451–465. DOI: 10.1038/nrn2148.
- Fox D., Rotstein H.G., Farzan N. Bursting in neurons and small networks. In Encyclopedia of computational neuroscience. Ed. D. Jaeger, R. Jung. Springer reference. Springer-Verlag Berlin Heidelberg. 2014.
- Hawkins R.D., Kandel E.R., Bailey C.H. Molecular mechanisms of memory storage in Aplysia. The Biological Bulletin. 2006. V. 210. № 3. P. 174–191. DOI: 10.2307/4134556.
- Larkum M. A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends in Neurosciences. 2013. V. 36. № 3. P. 141–151.
- Larkum M., Zhu J.J., Sakmann B. A new cellular mechanism for coupling inputs arriving at different cortical layers. Nature. 1999. V. 398. P. 338–341.
- Larkum M.E., Nevian T. Synaptic clustering by dendritic signaling mechanisms. Current Opinion in Neurobiology. 2008. V. 18. P. 321–331.
- Lisman J. Burst as a unit of neural information making unreliable synapses reliable. TINS. 1997. V. 20. № 1. P. 38–43.
- Steriade M. Neocortical cell classes are flexible entities. Nature Reviews Neuroscience. 2004. V. 5. P. 121–134.
- Steriade M., McCarley R.W. Brainstem control of wakefulness and sleep. New York: Springer. 1990.
- Thompson A.M., Bannister P. Interlaminar connections in the neocortex. Cerebral Cortex. 2003. V. 13. P. 5–14.
- Thompson A.M., Lamy C. Functional maps of neocortical local circuitry. Frontiers in Neuroscience. 2007. V. 1. № 1. P. 19–42.
- Womack M., Khodakhah K. Active contribution of dendrites to the tonic and trimodal patterns of activity in cerebellar Purkinje neurons. The Journal of Neuroscience. 2002. V. 22. № 24. P. 10603–10612.