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PresentationsInfluence of bifurcations in the extended hodgkin-huxley model on the dynamics of the ensemble of neuro-glio-vascular unitsLomonosov Moscow State University, Faculty of Biology, Department of Biophysics, Russia, 119234, Moscow, Leninskie Gory, 1, Building 24, E-mail: superstas-s@mail.ru 1Kursk State University, Department of Physics and Nanotechnology, Russia, 305000, Kursk Region, Kursk, Radishcheva Street, 33 Mathematical modeling of the neural tissue is an important tool for predicting the behavior of the nervous system under various external conditions. In the functioning of the real brain, there is a large number of interactions between cells of different types, each having its own model. In order to fully cover the entire spectrum of possible modes of functioning in such a complex system, we must use the most detailed available description of the processes occurring within. To achieve this, we use various mathematical models of individual processes and combine them together. Based on the recent understanding of the structural organization of neural tissue in the form of domains, known as neuro-glio-vascular units (NGVE), models of individual components are developed that are integrated with each other. Taking into account experimental measurements related to the functioning of various neurotransmitters and their receptors, such as GABA, glutamate, and norepinephrine, extensive models of brain structures are created. Each new mechanism that needs to be considered adds complexity to the system of equations that describe the dynamics of neuronal membrane potential. Biophysically relevant models, such as the Hodgkin-Huxley model, already have complex dynamics in their original form. Adding variables increases the dimensionality of the model's parameter space and introduces new dynamic modes. Exploring the parameter space of complex models, including those with different mathematical implementations of individual mechanisms, is a challenging and non-trivial task. In this work, we investigated individual parameters related to the volumetric transmission of information in the NGVE, through the phenomenon of extrasynaptic release of neurotransmitters (spillover effect). We constructed bifurcation diagrams for individual neurons based on the physiological value ranges of the parameters according to literature, as well as qualitative diagrams of the NGVE ensemble's modes of operation. We demonstrated the relationship between the switching of neuronal firing modes and the network dynamics. We showed how the parameters related to the ensemble structure affect the modes of operation of the model neural tissue. These results can bring us closer to understanding the real bifurcations that occur in the brain in both normal and pathological conditions. To create these models, Python language was used as long as, the Jupyter Notebooks architecture, and the Brian2 software package.
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