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A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations
Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca(2+) signals. Consequently, hardware realization of astrocytes is important for developin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6794439/ https://www.ncbi.nlm.nih.gov/pubmed/31649494 http://dx.doi.org/10.3389/fnins.2019.00998 |
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author | Faramarzi, Farnaz Azad, Fatemeh Amiri, Mahmood Linares-Barranco, Bernabé |
author_facet | Faramarzi, Farnaz Azad, Fatemeh Amiri, Mahmood Linares-Barranco, Bernabé |
author_sort | Faramarzi, Farnaz |
collection | PubMed |
description | Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca(2+) signals. Consequently, hardware realization of astrocytes is important for developing the next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and neuronal firing dynamics are presented by De Pittà and IF (Integrated & Fire) models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiplication (SCM) techniques are employed for efficient hardware execution while maintaining the dynamic of the original models. This low-cost hardware architecture for the astrocyte model is able to show the essential features of different types of Ca(2+) modulation such as amplitude modulation (AM), frequency modulation (FM), or both modes (AFM). To show good agreement between the results of original models simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative, and qualitative analyses including phase plane are done. This new neuromorphic circuit of astrocyte is able to successfully demonstrate AM/FM/AFM calcium signaling in its real operation on FPGA and has applications in self-repairing systems. It also can be employed as a subsystem for linking biological cells to artificial neuronal networks using astrocytic calcium oscillations in future research. |
format | Online Article Text |
id | pubmed-6794439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67944392019-10-24 A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations Faramarzi, Farnaz Azad, Fatemeh Amiri, Mahmood Linares-Barranco, Bernabé Front Neurosci Neuroscience Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca(2+) signals. Consequently, hardware realization of astrocytes is important for developing the next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and neuronal firing dynamics are presented by De Pittà and IF (Integrated & Fire) models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiplication (SCM) techniques are employed for efficient hardware execution while maintaining the dynamic of the original models. This low-cost hardware architecture for the astrocyte model is able to show the essential features of different types of Ca(2+) modulation such as amplitude modulation (AM), frequency modulation (FM), or both modes (AFM). To show good agreement between the results of original models simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative, and qualitative analyses including phase plane are done. This new neuromorphic circuit of astrocyte is able to successfully demonstrate AM/FM/AFM calcium signaling in its real operation on FPGA and has applications in self-repairing systems. It also can be employed as a subsystem for linking biological cells to artificial neuronal networks using astrocytic calcium oscillations in future research. Frontiers Media S.A. 2019-10-09 /pmc/articles/PMC6794439/ /pubmed/31649494 http://dx.doi.org/10.3389/fnins.2019.00998 Text en Copyright © 2019 Faramarzi, Azad, Amiri and Linares-Barranco. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Faramarzi, Farnaz Azad, Fatemeh Amiri, Mahmood Linares-Barranco, Bernabé A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title | A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title_full | A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title_fullStr | A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title_full_unstemmed | A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title_short | A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations |
title_sort | neuromorphic digital circuit for neuronal information encoding using astrocytic calcium oscillations |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6794439/ https://www.ncbi.nlm.nih.gov/pubmed/31649494 http://dx.doi.org/10.3389/fnins.2019.00998 |
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