Translational Modeling of Non-Invasive Electrical Stimulation

Author

Dennis Quangvinh Truong, CUNY City CollegeFollow

Date of Award

2019

Document Type

Dissertation

Department

Biomedical Engineering

First Advisor

Marom Bikson

Keywords

tDCS, FEM, nVNS, neuromodulation, neural engineering, stimulation

Abstract

Seminal work in the early 2000’s demonstrated the effect of low amplitude non-invasive electrical stimulation in people using neurophysiological measures (motor evoked potentials, MEPs). Clinical applications of transcranial Direct Current Stimulation (tDCS) have since proliferated, though the mechanisms are not fully understood. Efforts to refine the technique to improve results are on-going as are mechanistic studies both in vivo and in vitro. Volume conduction models are being applied to these areas of research, especially in the design and analysis of clinical montages. However, additional research on the parameterization of models remains.

In this dissertation, Finite Element Method (FEM) models of current flow were developed for clinical applications. The first image-derived models of obese subjects were developed to assess the relative impact of fat delineation from skin. Body mass index and more broadly inter-individual differences were considered. The effect of incorporating the meninges was predicted from CAD-based (Computer Aided Design) models before being translated into image-derived head models as an “emulated” CSF conductivity. These predictions were tested in a recently validated database of head models. Multi-scale models of transcutaneous vagus nerve stimulation (tVNS) were developed by coupling image-derived volume conduction models with physiological compartment modeling. The impact of local tissue inhomogeneities on fiber activation were considered.

Recommended Citation

Truong, Dennis Quangvinh, "Translational Modeling of Non-Invasive Electrical Stimulation" (2019). CUNY Academic Works.
https://academicworks.cuny.edu/cc_etds_theses/774