Excitatory synaptic transmission in CNS

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The mechanisms involved in generation of excitatory synaptic currents, induced by glutamate receptor activation mediating transmission between neurons in the central nervous system, are not well understood. However, quantal size changes during long-term potentiation, which is a process usually considered as one of the best models for memory. The models of gating of a variety of channels including AMPA channels have now been described. How many states exist can be determined from the mean open and closed times estimated under steady-state conditions, and the correlations between adjacent events reveal how the states are inter-connected. The evaluation of mechanisms of generation of unitary currents (mEPSCs) however, requires more than just the model of gating of AMPA channels. It is a complex problem of diffusion in a restricted space with stochastic interactions of the glutamate molecules with postsynaptic AMPA receptors. As such it requires not only experimental but also theoretical approaches. I propose to examine both experimentally and theoretically what factors shape the unitary quantal events. Experimental part will follow the 'traditional' methods of whole-cell patch clamping of hippocampal neurons in hippocampus. Theoretical studies will start with Monte Carlo simulations, which will provide the assessment of the average behavior of the process of generation of mEPSCs, but also its variability. Molecular dynamics, which will follow will further advance our understanding of these processes by considering the complexities of shape of glutamate molecule, its charge, and its interactions (electrostatic and non-electrostatic) with water and membranes.The fluctuations of excitatory synaptic currents are generally non-stationary. Glutamate concentration changes rapidly, and the rates of their kinetic scheme of gating are concentration dependent. Moreover, the desensitization of AMPA receptors is fast and contributes to shaping the time course of unitary excitatory post-synaptic currents. Non-stationary current fluctuations can however be tracked using modern techniques of signal processing such as wavelet and Kalman-AR methods, even from individual mEPSCs. Given that the non-stationary fluctuations of excitatory synaptic currents are dynamically very rich, any difference of gating kinetics, glutamate release or diffusion constant will lead to mEPSCs whose overall properties (amplitude, time course and the current fluctuations) will differ in some respect from each other, rendering their evaluation not only feasible, but also accurate. I propose to develop methods that fit directly the system (particular kinetic model) and its input (glutamate concentration in the synaptic cleft), to synaptic currents: a) an all-connected, feed-forward neural network, b) fuzzy logic, and c) support vector machines. The methods will be tested first on Monte-Carlo simulated mEPSCs and use subsequently on experimentally recorded mEPSCs from rat hippocampus.