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Ionic Imbalances and Coupling in Synchronization of Responses in Neurons

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  • Seyed-Ali Sadegh-Zadeh

    (School of Engineering and Computer Science, University of Hull, Cottingham Rd, Hull, HU6 7RX, UK)

  • Chandrasekhar Kambhampati

    (School of Engineering and Computer Science, University of Hull, Cottingham Rd, Hull, HU6 7RX, UK)

  • Darryl N. Davis

    (School of Engineering and Computer Science, University of Hull, Cottingham Rd, Hull, HU6 7RX, UK)

Abstract

Most neurodegenerative diseases (NDD) are a result of changes in the chemical composition of neurons. For example, Alzheimer’s disease (AD) is the product of Aβ peptide deposition which results in changes in the ion concentration. These changes in ion concentration affect the responses of the neuron to stimuli and often result in inducing excessive excitation or inhibition. This paper investigates the dynamics of a single neuron as ion changes occur. These changes are incorporated using the Nernst equation. Within the central and peripheral nervous system, signals and hence rhythms, are propagated through the coupling of the neurons. It was found that under certain conditions the coupling strength between two neurons could mitigate changes in ion concentration. By defining the state of perfect synchrony, it was shown that the effect of ion imbalance in coupled neurons was reduced while in uncoupled neurons these changes had a more significant impact on the neuronal behavior.

Suggested Citation

  • Seyed-Ali Sadegh-Zadeh & Chandrasekhar Kambhampati & Darryl N. Davis, 2019. "Ionic Imbalances and Coupling in Synchronization of Responses in Neurons," J, MDPI, vol. 2(1), pages 1-24, January.
    • Handle: RePEc:gam:jjopen:v:2:y:2019:i:1:p:3-40:d:196716
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    References listed on IDEAS

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    1. P. N. Steinmetz & A. Roy & P. J. Fitzgerald & S. S. Hsiao & K. O. Johnson & E. Niebur, 2000. "Attention modulates synchronized neuronal firing in primate somatosensory cortex," Nature, Nature, vol. 404(6774), pages 187-190, March.
    2. Edward A. Stern & Dieter Jaeger & Charles J. Wilson, 1998. "Membrane potential synchrony of simultaneously recorded striatal spiny neurons in vivo," Nature, Nature, vol. 394(6692), pages 475-478, July.
    3. Mark Stopfer & Seetha Bhagavan & Brian H. Smith & Gilles Laurent, 1997. "Impaired odour discrimination on desynchronization of odour-encoding neural assemblies," Nature, Nature, vol. 390(6655), pages 70-74, November.
    4. Wolf Singer, 1999. "Striving for coherence," Nature, Nature, vol. 397(6718), pages 391-393, February.
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