Translational Modeling of Non-Invasive Electrical Stimulation

<p>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.</p> <p>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.</p>

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Biomedical Engineering

Year dc:date.available

2019

Author dc:creator

• Truong, Dennis Quangvinh

Contributors dc:contributor

• Marom Bikson

• tDCS
• FEM
• nVNS
• neuromodulation
• neural engineering
• stimulation
• Bioelectrical and Neuroengineering
• Neurosciences
• Translational Medical Research

Repository record dc:identifier

https://academicworks.cuny.edu/cc_etds_theses/774

OAI identifier oai:identifier

oai:academicworks.cuny.edu:cc_etds_theses-1824