A physical channel model and analysis of nanoscale neuro-spike communication

Balevi, Eren
Nanoscale communication is appealing domain in nanotechnology. There are many existing nanoscale communication methods. In addition to these, novel techniques can be derived depending on the naturally existing phenomena such as molecular communication. It uses molecules as an information carrier such as molecular motors, pheromones and neurotransmitters for neuro-spike communication. Among them, neuro-spike communication is a vastly unexplored area. The ultimate goal of this thesis is to accurately investigate it by obtaining a realistic physical channel model. This model can be exploited in different disciplines. Furthermore, the model can help designing novel artificial nanoscale communication paradigms. The modeled channel is analyzed regarding the error probability of detecting spikes depending on channel parameters. Moreover, channel delay is characterized and information theoretical analysis of packet release mechanism in the channel is performed. The modeled channel is extended to multi-input single output terminal. In this case, input neurons can simultaneously send information through the same synapse leading to interference. However, there is an interference repressing technique in these synapses called automatic gain control. It decreases the interference level observed on weaker signal. The first aim for this case is to define the interference channel at synapse having automatic gain control. The second aim is to analyze the achievable rate region of this channel. The analysis shows that gain control mechanism prevents the decrease in achievable rate region because of the weaker signal. Moreover, power, firing rate and number of stronger inputs do not affect the achievable rate region.


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Citation Formats
E. Balevi, “A physical channel model and analysis of nanoscale neuro-spike communication,” M.S. - Master of Science, Middle East Technical University, 2010.