4.7 Article

Analysis of the Information Capacity of Neuronal Molecular Communications Under Demyelination and Remyelination

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2021.3137350

Keywords

Neurons; Encoding; Analytical models; Biological system modeling; Computational modeling; Media; Indexes; Re; Demyelination; Lysolecithin (LPC); Hodgkin-Huxley model; myelination index; molecular communications

Funding

  1. Science Foundation Ireland (SFI) [13/RC/2077]
  2. SFI Future Research Leader Award [16/FRL/3855]
  3. Irish Research Council (IRC) Postgraduate Scholarship [GOIPG/2018/2648]
  4. European Union [839553]
  5. Marie Curie Actions (MSCA) [839553] Funding Source: Marie Curie Actions (MSCA)
  6. Science Foundation Ireland (SFI) [16/FRL/3855] Funding Source: Science Foundation Ireland (SFI)

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The study proposes a hybrid experimental and simulation model to analyze the effects of demyelination on neuron communication. By inducing local demyelination and empirically estimating a myelination index from cell images, the model simulates the impact of demyelination on signal propagation along the axon. This approach can predict the degeneration severity and minimize the need for specialized laboratory equipment for single-cell communication analysis.
Demyelination of neurons can compromise the communication performance between the cells as the absence of myelin attenuates the action potential propagated through the axonal pathway. In this work, we propose a hybrid experimental and simulation model for analyzing the demyelination effects on neuron communication. The experiment involves locally induced demyelination using Lysolecithin and from this, a myelination index is empirically estimated from analysis of cell images. This index is then coupled with a modified Hodgkin-Huxley computational model to simulate the resulting impact that the de/myelination processes has on the signal propagation along the axon. The effects of signal degradation and transfer of neuronal information are simulated and quantified at multiple levels, and this includes (1) compartment per compartment of a single neuron, (2) bipartite synapse and the effects on the excitatory post-synaptic potential, and (3) a small network of neurons to understand how the impact of de/myelination has on the whole network. By using the myelination index in the simulation model, we can determine the level of attenuation of the action potential concerning the myelin quantity, as well as the analysis of internal signalling functions of the neurons and their impact on the overall spike firing rate. We believe that this hybrid experimental and in silico simulation model can result in a new analysis tool that can predict the gravity of the degeneration through the estimation of the spiking activity and vice-versa, which can minimize the need for specialised laboratory equipment needed for single-cell communication analysis.

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