Admittance Method for Estimating Local Field Potentials Generated in a Multi-Scale Neuron Model of the Hippocampus

Abstract

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the challenge of misalignment between current sources and mesh nodes in a finite-element or resistor-network method volume conduction model needs to be further investigated. Therefore, using a previously published and validated multi-scale model of the hippocampus, the authors have formulated an algorithm for LFP estimation, and by extension, bidirectional communication between discretized and numerically solved volume conduction models and biologically detailed neural circuit models constructed in NEURON. Development of this algorithm required that we assess meshes of (i) unstructured tetrahedral and grid-based hexahedral geometries as well as (ii) differing approaches for managing the spatial misalignment of current sources and mesh nodes. The resulting algorithm is validated through the comparison of Admittance Method predicted evoked potentials with analytically estimated LFPs. Establishing this method is a critical step toward closed-loop integration of volume conductor and NEURON models that could lead to substantial improvement of the predictive power of multi-scale stimulation models of cortical tissue. These models may be used to deepen our understanding of hippocampal pathologies and the identification of efficacious electroceutical treatments.

Color and cellular selectivity of retinal ganglion cell subtypes through frequency modulation of electrical stimulation

“…Admittance method/NEURON computational framework. In this work, we utilized our threedimensional Admittance Method (AM)/NEURON multi-scale computational modeling platform 12,[61][62][63][64][65][66][67][68][69][70][71][72][73] to predict the electric fields generated inside retinal tissue, coupled to multi-compartmental models of neurons in order to determine the activation of realistic RGCs. The Admittance Method linked with NEURON has proven a powerful approach not only for studies of field distribution inside the tissue due to electrical stimulation, but also providing a platform to analyze realistic representations of various cell types 12,61-73 . Admittance method: constructing the retina tissue and electrodes.…”

“…A linear interpolation function is used to obtain the voltage at the center of each neuronal compartment, which is utilized for the computation of the neural response using the NEURON simulator (v7.4; https ://neuro n.yale.edu/neuro n) 74 . Further details can be found in [61][62][63][64][65][66][67] . The AM-NEURON computational platform has been recently parallelized by our group and accommodates adaptive multiresolution meshing.…”

“…However, slower rate of increase in Figure 1. A2 and D1 realistic morphologies as implemented and coded in our multiscale Admittance Method/ NEURON computational platform [61][62][63][64][65][66][67][68][69][70][71][72][73] . Left: A2-monostratified RGC ramified in the inner part of inner plexiform layer and has a larger soma and dendritic field diameters.…”

“…The voltage at the center of each voxel was estimated using a linear interpolation function. Since the Admittance Method and NEURON use the same coordinates, a computational code was developed to superimpose the potential computed in the tissue volume into the NEURON model and apply it as an extracellular voltage, using the "extracellular" mechanism built into NEURON software, to each compartment in the Hodgkin-Huxley circuit in series with the membrane 12,[61][62][63][64][65][66][67][68][69][70][71] .…”

The Listening Zone of Human Electrocorticographic Field Potential Recordings

“…Not all neurons contribute to this electric field landscape at any given instant, and different patterns of neural activity may generate similar field potential measures depending on the distance and the density of recording sites. The neural tissue that comprises this electric field landscape is itself heterogenous, with conductivity and dielectric constants that vary based on cell packing density and cortical location (Bingham et al 2020;Howell and McIntyre 2016;Nunez and Srinivasan 2005). At the resolution currently provided by macroelectrodes used for human intracranial electroencephalographic (icEEG) recordings, the measured field potential activity is not a direct measure of the activity of local cell assemblies, but rather a larger-scale measure of activity conducted through neural space.…”