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Sum rate analysis of multiple-access neuro-spike communication channel with dynamic spiking threshold

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Khan, T 
Akan, OB 

Abstract

© 2019 Elsevier B.V. The information from outside world is encoded into spikes by the sensory neurons. These spikes are further propagated to different brain regions through various neural pathways. In the cortical region, each neuron receives inputs from multiple neurons that change its membrane potential. If the accumulated change in the membrane potential is more than a threshold value, a spike is generated. According to various studies in neuroscience, this spiking threshold adapts with time depending on the previous spike. This causes short-term changes in the neural responses giving rise to short-term plasticity. Therefore, in this paper, we analyze a multiple-input single-output (MISO) neuro-spike communication channel and study the effects of dynamic spiking threshold on mutual information and maximum achievable sum rate of the channel. Since spike generation consumes a generous portion of the metabolic energy provided to the brain, we further put metabolic constraint in calculating the mutual information and find a trade-off between maximum achievable sum rate and metabolic energy consumed. Moreover, we analyze three types of neurons present in the cortical region, i.e., Regular spiking, Intrinsic bursting and Fast spiking neurons. We aim to characterize these neurons in terms of encoding/transmission rates and energy expenditure. It will provide a guideline for the practical implementation of bio-inspired nanonetworks as well as for the development of ICT-based diagnosis and treatment techniques for neural diseases.

Description

Keywords

Neuro-spike communication, Nanonetworks, Molecular communications, MISO neuro-spike communication channel, Channel capacity, Metabolic cost, Dynamic threshold

Journal Title

Nano Communication Networks

Conference Name

Journal ISSN

1878-7789
1878-7797

Volume Title

19

Publisher

Elsevier
Sponsorship
European Research Council (616922)
European Research Council (780645)
This work was supported in part by European Research Council (ERC) under grant ERC-2013-CoG 616922 (Project MINERVA) and ERC-2017-PoC 780645 (ERC Proof of Concept project MINRGRACE).