The ultimate goal of our research is to reveal common mechanism and principles behind activity of complex biological systems, from cancer cell populations to brain neuronal networks, in normal and pathological states, and to develop clinical interventions that may prevent the development of pathologies. To achieve these goals, we apply a variety of methods – quantitative experimental techniques, sophisticated mathematical analysis and large-scale computer modeling – to a variety of problems to reveal common features across different biological systems. Our research is deeply collaborative; it involves interaction with experimental and clinical labs as well as collaboration with mathematicians and physicists.
Our work focuses on the following main areas: (1) Role of sleep in memory and learning. During sleep, the cortex is decoupled from sensory inputs, and can be devoted to consolidating previously acquired labile memories into stable memories. The goal of our research is to combine animal, human and computational works to explain mechanisms of sleep rhythm generation and how sleep rhythms contribute to memory consolidation. (2) Cellular and network mechanisms underlying the transformation of normal brain oscillations to electrographic seizures. The goal of this research is to design approaches that could be further developed to treat humans with trauma-induced epilepsy in clinical settings. (3) The role of neuronal oscillations and synchrony in olfactory coding — this project is targeted to discover the general principles and the neural circuitry involved in the encoding of sensory information in the brain. In collaboration with experimentalists, we construct detailed biophysical models of insect and vertebrate olfactory systems to study odor encoding, processing and learning. (4) Cancer treatment is complicated by drug resistance, drug efficacy, and relapse. The primary objective of our research on cancer is to use mathematical models to understand cancer cell dynamics, mechanisms of growth, and optimal treatment strategies.
Chen JY, Marachlian M, Assisi C, Huerta R, SmithBH, Locatelli F, Bazhenov M. 2015. Learning modifies odor mixture processing to improve detection of relevant components, Journal of Neuroscience, Jan 7;35(1):179-97.
Krishnan GP, Filatov G, Shilnikov A, Bazhenov M. 2015. Electrogenic properties of the Na+/K+ ATPase controls transitions between normal and pathological brain states, Journal of Neurophysiology, May 1;113(9):3356-74.
Moldakarimov S, Bazhenov M, Sejnowski TJ. 2015. Feedback connections stabilize spike propagation in multilayer neural networks, PNAS, 2015 Feb 24;112(8):2545-50.
Chistiakova M, Bannon NM, Chen JY, Bazhenov M, Volgushev M. 2015. Homeostatic role of heterosynaptic plasticity: Models and experiments, Frontiers in Computational Neuroscience, Jul 13;9:89.
Gonzalez OC, Krishnan, GP, Chauvette S, Timofeev I, Sejnowski T, Bazhenov M. 2015. Modeling of age-dependent epileptogenesis by differential homeostatic synaptic scaling, Journal of Neuroscience, Sep 30;35(39):13448-62.
Kee T, Sanda P, Gupta N, Stopfer M, Bazhenov M. 2015. Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit, PLoS Computational Biology, Oct 12;11(10):e1004531.
Niknazar M, Krishnan GP, Bazhenov M, Mednick S. 2015. Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans, PLoS ONE, Dec 15;10(12):e0144720.
Sanda P, Kee T, Gupta N, Stopfer M, Bazhenov M. 2016 Classification of odorants across layers in locust olfactory pathway, Journal of Neurophysiology, May 1;115(5):2303-16.
Wei Y, Krishnan GP, Bazhenov M. 2016. Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations, Journal of Neuroscience, Apr 13;36(15):4231-47.
Malerba P, Krishnan GP, Fellous JM, Bazhenov M. 2016. Hippocampal CA1 Ripples as Inhibitory Transients, PLoS Computational Biology, Apr 19;12(4):e1004880.