Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/98871
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Type: Journal article
Title: A Digital Realization of Astrocyte and Neural Glial Interactions
Author: Hayati, M.
Nouri, M.
Haghiri, S.
Abbott, D.
Citation: IEEE Transactions on Biomedical Circuits and Systems, 2016; 10(2):518-529
Publisher: IEEE
Issue Date: 2016
ISSN: 1932-4545
1940-9990
Statement of
Responsibility: 
Mohsen Hayati, Moslem Nouri, Saeed Haghiri, Derek Abbott
Abstract: The implementation of biological neural networks is a key objective of the neuromorphic research field. Astrocytes are the largest cell population in the brain. With the discovery of calcium wave propagation through astrocyte networks, now it is more evident that neuronal networks alone may not explain functionality of the strongest natural computer, the brain. Models of cortical function must now account for astrocyte activities as well as their relationships with neurons in encoding and manipulation of sensory information. From an engineering viewpoint, astrocytes provide feedback to both presynaptic and postsynaptic neurons to regulate their signaling behaviors. This paper presents a modified neural glial interaction model that allows a convenient digital implementation. This model can reproduce relevant biological astrocyte behaviors, which provide appropriate feedback control in regulating neuronal activities in the central nervous system (CNS). Accordingly, we investigate the feasibility of a digital implementation for a single astrocyte constructed by connecting a two coupled FitzHugh Nagumo (FHN) neuron model to an implementation of the proposed astrocyte model using neuron-astrocyte interactions. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed neuron astrocyte model, with significantly low hardware cost, can mimic biological behavior such as the regulation of postsynaptic neuron activity and the synaptic transmission mechanisms.
Keywords: Analytical models; Biological system modeling; Calcium; Computational modeling; Field programmable gate arrays; Mathematical model; Neuron
Rights: © 2015 IEEE. Personal use is permitted, but republication/redi stribution requires IEEE permission.
RMID: 0030043230
DOI: 10.1109/TBCAS.2015.2450837
Appears in Collections:Mathematical Sciences publications

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