CUED Publications database

Information Theoretical Analysis of Synaptic Communication for Nanonetworks

Ramezani, H and Khan, T and Akan, OB (2017) Information Theoretical Analysis of Synaptic Communication for Nanonetworks. In: IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, -- to -- pp. 2330-2338..

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© 2018 IEEE. Communication among neurons is the highly evolved and efficient nanoscale communication paradigm, hence the most promising technique for biocompatible nanonetworks. This necessitates the understanding of neuro-spike communication from information theoretical perspective to reach a reference model for nanonetworks. This would also contribute towards developing ICT-based diagnostics techniques for neuro-degenerative diseases. Thus, in this paper, we focus on the fundamental building block of neuro-spike communication, i.e., signal transmission over a synapse, to evaluate its information transfer rate. We aim to analyze a realistic synaptic communication model, which for the first time, encompasses the variation in vesicle release probability with time, synaptic geometry and the re-uptake of neurotransmitters by pre-synaptic terminal. To achieve this objective, we formulate the mutual information between input and output of the synapse. Then, since this communication paradigm has memory, we evaluate the average mutual information over multiple transmissions to find its overall capacity. We derive a closed-form expression for the capacity of the synaptic communication as well as calculate the capacity-achieving input probability distribution. Finally, we find the effects of variation in different synaptic parameters on the information capacity and prove that the diffusion process does not decrease the information a neural response carries about the stimulus in real scenario.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div B > Photonics
Depositing User: Cron Job
Date Deposited: 22 Nov 2018 01:20
Last Modified: 13 Apr 2021 09:32
DOI: 10.1109/INFOCOM.2018.8486255