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Nanonetworking is a multidisciplinary field that draws researchers from diverse disciplines. By enabling communication between nano-machines we can expand the capabilities of a single nano-machine and achieve complicated tasks. Among the various techniques molecular communication is identified as the most promising approach for communication in nanonetworks. Neural network which is composed of neurons is an appropriate option for long range molecular communication.In this paper, we propose a multiplexing and buffering mechanism which utilizes neural delay lines for neural molecular communication. The performance of our model is evaluated by simulations and the results demonstrate significant improvements on the performance when neural delay lines are employed.

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Many neurodegenerative diseases arise from the malfunctioning neurons in the pathway where the signal is carried. In this paper, we propose neuron specific TDMA/multiplexing and demultiplexing mechanisms to convey the spikes of a receptor neuron over a neighboring path in case of an irreversible path fault existing in its original path. The multiplexing mechanism depends on neural delay box (NDB) which is composed of a relay unit and a buffering unit. The relay unit can be realized as a nanoelectronic device. The buffering unit can be implemented either via neural delay lines as employed in optical switching systems or via nanoelectronic delay lines, i.e., delay flip flops. Demultiplexing is realized by a demultiplexer unit according to the time slot assignment information. Besides, we propose the use of neural interfaces in the NDBs and the demultiplexer unit for detecting and stimulating the generation of spikes. The objective of the proposed mechanisms is to substitute a malfunctioning path, increase the number of spikes delivered and correctly deliver the spikes to the intended part of the somatosensory cortex. The results demonstrate that significant performance improvement on the successively delivered number of spikes is achievable when delay lines are employed as neural buffers in NDBs.