Impact of the angle of implantation of transverse intrafascicular multichannel electrodes on axon activation

Kolbl, Florian; 莫娟,; Sepúlveda, Francisco

doi:10.1109/biocas.2016.7833837

Cited by 7 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different approaches for implementing the FEM model have been attempted. Macroscale models developed in literature used the FEM simulation software Comsol Multiphysics, but other FEM modeling environments can be considered, such as FEniCS or Ansys [87], [88].…”

Section: Simulation On Stimulation Techniquesmentioning

confidence: 99%

A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review

Stefano

Cordella

Loppini

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

Electrical nerve fiber stimulation is a technique widely used in prosthetics and rehabilitation, and its study from a computational point of view can be a useful instrument to support experimental tests. In the last years, there was an increasing interest in computational modeling of neural cells and numerical simulations on nerve fibers stimulation because of its usefulness in forecasting the effect of electrical current stimuli delivered to tissues through implanted electrodes, in the design of optimal stimulus waveforms based on the specific application (i.e., inducing limb movements, sensory feedback or physiological function restoring), and in the evaluation of the current stimuli properties according to the characteristics of the nerves surrounding tissue. Therefore, a review study on the main modeling and computational frameworks adopted to investigate peripheral nerve stimulation is an important instrument to support and drive future research works. To this aim, this paper deals with mathematical models of neural cells with a detailed description of ion channels and numerical simulations using finite element methods to describe the dynamics of electrical stimulation by implanted electrodes in peripheral nerve fibers. In particular, we evaluate different nerve cell models considering different ion channels present in neurons and provide a guideline on multiscale numerical simulations of electrical nerve fibers stimulation.

show abstract

Section: Simulation On Stimulation Techniquesmentioning

confidence: 99%

A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review

Stefano

Cordella

Loppini

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

show abstract

“…Notice that the challenge of this research also brings the benefits not only for the theoretical research but also for the neural applications. Based on the presented characterisation, the interaction can be analysed using the numerical approach and the performance of the neural applications can be enhanced, such as neural prosthesis design and development [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Neural Membrane Mutual Coupling Characterisation Using Entropy-Based Iterative Learning Identification

et al. 2020

View full text Add to dashboard Cite

This paper investigates the interaction phenomena of the coupled axons while the mutual coupling factor is presented as a pairwise description. Based on the Hodgkin-Huxley model and the coupling factor matrix, the membrane potentials of the coupled myelinated/unmyelinated axons are quantified which implies that the neural coupling can be characterised by the presented coupling factor. Meanwhile the equivalent electric circuit is supplied to illustrate the physical meaning of this extended model. In order to estimate the coupling factor, a data-based iterative learning identification algorithm is presented where the Rényi entropy of the estimation error has been minimised. The convergence of the presented algorithm is analysed and the learning rate is designed. To verified the presented model and the algorithm, the numerical simulation results indicate the correctness and the effectiveness. Furthermore, the statistical description of the neural coupling, the approximation using ordinary differential equation, the measurement and the conduction of the nerve signals are discussed respectively as advanced topics. The novelties can be summarised as follows: 1) the Hodgkin-Huxley model has been extended considering the mutual interaction between the neural axon membranes, 2) the iterative learning approach has been developed for factor identification using entropy criterion, and 3) the theoretical framework has been established for this class of system identification problems with convergence analysis.

show abstract

Entropy-based Axon-to-Axon Mutual Interaction Characterization via Iterative Learning Identification

Zhang

Sepúlveda

2017

IFMBE Proceedings

View full text Add to dashboard Cite

Impact of the angle of implantation of transverse intrafascicular multichannel electrodes on axon activation

Cited by 7 publications

References 9 publications

A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review

A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review

Neural Membrane Mutual Coupling Characterisation Using Entropy-Based Iterative Learning Identification

Entropy-based Axon-to-Axon Mutual Interaction Characterization via Iterative Learning Identification

Contact Info

Product

Resources

About