On the computation of a retina resistivity profile for applications in multi-scale modeling of electrical stimulation and absorption

Abstract

This study proposes a methodology for computationally estimating resistive properties of tissue in multi-scale computational models, used for studying the interaction of electromagnetic fields with neural tissue, with applications to both dosimetry and neuroprosthetics. Traditionally, models at bulk tissue- and cellular-level scales are solved independently, linking resulting voltage from existing resistive tissue-scale models as extracellular sources to cellular models. This allows for solving the effects that external electric fields have on cellular activity. There are two major limitations to this approach: first, the resistive properties of the tissue need to be chosen, of which there are contradicting measurements in literature; second, the measurements of resistivity themselves may be inaccurate, leading to the mentioned contradicting results found across different studies. Our proposed methodology allows for constructing computed resistivity profiles using knowledge of only the neural morphology within the multi-scale model, resulting in a practical implementation of the effective medium theory; this bypasses concerns regarding the choice of resistive properties and accuracy of measurement setups. A multi-scale model of retina is constructed with an external electrode to serve as a test bench for analyzing existing and resulting resistivity profiles, and validation is presented through the reconstruction of a published resistivity profile of retina tissue. Results include a computed resistivity profile of retina tissue for use with a retina multi-scale model used to analyze effects of external electric fields on neural activity.

Honeycomb-shaped electro-neural interface enables cellular-scale pixels in subretinal prosthesis

“…It is important to note that our model is based on the stimulation current densities from the literature, while the calculated trans-cellular voltage scales linearly with the retinal resistivity, for which there is no consensus in the literature 41–43 . We use the trans-cellular voltage only as a means for assessing the boundaries of the activation zone in tissue, relative to the stimulation threshold.…”

Increasing Electrical Stimulation Efficacy in Degenerated Retina: Stimulus Waveform Design in a Multiscale Computational Model

“…It was voxelized with a resolution of 10 μ m and discretized based on bulk tissue resistivity. For the inner band, including the ganglion cell layer, inner plexiform layer, and inner nuclear layer, the resistivity and layer thickness were given properties that were assigned using knowledge of the cellular morphology, applying values reported in [43]. In this method, the morphological data from the connectome dataset that was translated to a NEURON model for this study, as discussed in the next section, was voxelized and segmented into these three retina layers.…”

“…Morphological data for a neural network extracted from a connectome dataset of rabbit retina was converted into SWC format for importing to NEURON software [42] as a compartmentalized model, following the authors’ previous work [28], [43]. This connectome is basically a connectivity map originating from transmission electron microscopy (TEM) images of rabbit retina, that has been manually annotated to populate a dataset containing morphology, cell type, receptor distribution and type, etc.…”

“…Towards improving the efficacy of the electrical stimulation, we provide a simulation framework for understanding the response of degenerating retina to currently used electrical stimuli and for designing new electrode geometries and stimuli waveforms. This framework is based on a multiscale multiphysics platform, using the Admittance Method for computing the electric field within a model of tissue [41], and NEURON [42] for simulating the resulting response in a neural network, following the authors’ previous work [43]. Briefly, the Admittance Method is a quasi-static electromagnetic field solver.…”

Retinal Drug Delivery: Rethinking Outcomes for the Efficient Replication of Retinal Behavior

“…To understand the degenerate retinal response to electrical stimulation used and to develop new electrode geometries and stimulus waveforms, the authors provided a simulation framework for increasing the effectiveness of electrical stimulation. Based on previous work, the framework was developed as a multi-scale and multiphysics simulation platform where the Admittance Method is used to compute the electric field within a tissue model and NEURON is used to simulate the resulting response in a neural network [130]. The Admittance Method is assumed to be a quasi-static electromagnetic field solver, where a voxelized model that is discretized by tissue/material dielectric properties is constructed first.…”