NDLI: Statistical multiplexing for neural nanonetworks in case of neuron specific faults

Content Provider	IEEE Xplore Digital Library
Author	Tezcan, H. Oktug, S. Kok, F.N.
Copyright Year	2014
Description	Author affiliation: Fac. of Mol. Biol. & Genetics, Istanbul Tech. Univ., Istanbul, Turkey (Kok, F.N.) \|\| Fac. of Comput. & Inf., Istanbul Tech. Univ., Istanbul, Turkey (Tezcan, H.; Oktug, S.)
Abstract	Although nanonetworking is in its infancy, a wide range of appealing application areas especially in human healthcare field draws the attention of both the medical and scientific communities. Many neurological diseases like paralysis are caused by the interruption of spike propagation due to the malfunctioning neurons in the signaling pathway where the spikes are carried. In this paper, we propose a neuron specific statistical multiplexing scheme to substitute a faulty sensory neural pathway with a neighboring functional one. Since the spikes are stereotyped events and they have no addressing information, we developed an addressing scheme utilizing the spikes themselves. The performance achieved by the proposed technique is analyzed in terms of the percentage of the spikes transmitted under various scenarios. We also compared the results obtained with the previously proposed TDMA based multiplexing schemes. The proposed statistical multiplexing based technique has lower implementation complexity than the previously introduced TDMA based techniques. Additionally, we evaluated the performance of the proposed technique when a priority mechanism is employed. The concept of multiplexing spikes to substitute a faulty neural pathway with a functional pathway reveals new opportunities in neuronal communication and may pave the way to the real healthcare applications of nanonetworking in the near future.
Starting Page	254
Ending Page	259
File Size	645694
Page Count	6
File Format	PDF
ISBN	9781479952915
ISSN	21570221
DOI	10.1109/ICUMT.2014.7002111
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-06
Publisher Place	Russia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiplexing Time division multiple access Neuron Neurons Nanonetworks Molecular communication Neural pathways Delay lines Statistical multiplexing Nanobioscience Biological neural networks
Content Type	Text
Resource Type	Article

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