Utilizing Neurons for Digital Logic Circuits : A Molecular Communications Analysis

Adonias, Geoflly L. and Yastrebova, Anastasia and Barros, Michael Taynnan and Koucheryavy, Yevgeni and Cleary, Frances and Balasubramaniam, Sasitharan (2020) Utilizing Neurons for Digital Logic Circuits : A Molecular Communications Analysis. IEEE Transactions on Nanobioscience, 19 (2). pp. 224-236. ISSN 1536-1241

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With the advancement of synthetic biology, several new tools have been conceptualized over the years as alternative treatments for current medical procedures. As part of this work, we investigate how synthetically engineered neurons can operate as digital logic gates that can be used towards bio-computing inside the brain and its impact on epileptic seizure-like behaviour. We quantify the accuracy of logic gates under high firing rates amid a network of neurons and by how much it can smooth out uncontrolled neuronal firings. To test the efficacy of our method, simulations composed of computational models of neurons connected in a structure that represents a logic gate are performed. Our simulations demonstrate the accuracy of performing the correct logic operation, and how specific properties such as the firing rate can play an important role in the accuracy. As part of the analysis, the mean squared error is used to quantify the quality of our proposed model and predict the accurate operation of a gate based on different sampling frequencies. As an application, the logic gates were used to smooth out epileptic seizure-like activity in a biological neuronal network, where the results demonstrated the effectiveness of reducing its mean firing rate. Our proposed system has the potential to be used in future approaches to treating neurological conditions in the brain.

Item Type: Article
Additional Information: Funding Information: Manuscript received August 30, 2019; revised November 21, 2019; accepted February 16, 2020. Date of publication February 24, 2020; date of current version April 9, 2020. This work was supported in part by the Science Foundation Ireland (SFI) and in part by the European Regional Development Fund under Grant 13/RC/2077. The work of Michael Taynnan Barros was supported by the European Union’s Horizon 2020 Research and Innovation Programme through the Marie Skłodowska-Curie Grant under Agreement 839553. (Corresponding author: Geoflly L. Adonias.) Geoflly L. Adonias, Frances Cleary, and Sasitharan Balasubramaniam are with the Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, X91 K0EK Ireland (e-mail: gadonias@tssg.org; fcleary@tssg.org; sasib@tssg.org). Publisher Copyright: © 2002-2011 IEEE.
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1300/1305
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Depositing User: Admin SSL
Date Deposited: 19 Oct 2022 23:08
Last Modified: 14 Aug 2023 02:15
URI: http://repository-testing.wit.ie/id/eprint/4260

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