Modeling signal propagation in nanomachine-to-neuron communications

Abstract Nanomachine communications are a promising paradigm for the large applications which can be envisaged especially in the medical field. As an example, many widespread neurological diseases such as Alzheimer and/or paralysis are associated to bad neuronal communication or to interruption of the pulse propagation across the nervous system due to irreversible damages across a human body area. In this context, nanomachines can be integrated into a neuronal network system to restore biological communications. To this purpose, a preliminary step is modeling all the phases of the communication among neurons through a block scheme where input/output relationships at each block are characterized in terms of transfer functions, gain and delay. In order to make the characterization realistic, we also consider the possibility to have multiple inputs along the surface of a neuron cell. The communication perspective being used can be useful to design nanomachines compatible with biological structures and able to interact with biological systems.

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