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Control of neurotransmitters in brain neurons using soft-switching sliding mode control

In this paper we propose a mathematical model to describe the dynamics of neurotransmitter's active, available and reprocessed states. A set of nonlinear differential equations is obtained from neurophysiological and biochemical reasoning. To solve a tracking control problem, we study cellular feedback mechanisms that regulate the amount of neurotransmitters at distinct states. The neurotransmitters are the information carriers, and we control the amount of neurotransmitters at the active state. The cellular feedback mechanisms are examined and prototyped utilizing a sound analog control methodology. Though modeling and control problems are formulated and solved by using a number of hypotheses, the reported results have a direct impact on the envisioned bioinspired data/signal processing and cognitive information processing platforms. These processing platforms are expected to be designed using an information-theoretic paradigm and fluidic/solid molecular electronics hardware solutions