IOP PUBLISHING JOURNAL OF NEURAL ENGINEERING
J. Neural Eng. 4 (2007) 107–119 doi:10.1088/1741-2560/4/2/011
Assessing the direct effects of deep brain
stimulation using embedded axon models
Stamatios N Sotiropoulos and Peter N Steinmetz
Brain Modeling Laboratory, Harrington Department of Bioengineering, Mail Code 9709,
ASU Main Campus, Tempe, AZ 85287, USA
E-mail: soti0003@umn.edu and Peter.Steinmetz@asu.edu
Received 7 August 2006
Accepted for publication 16 February 2007
Published 28 March 2007
Online at stacks.iop.org/JNE/4/107
Abstract
To better understand the spatial extent of the direct effects of deep brain stimulation (DBS) on
neurons, we implemented a geometrically realistic finite element electrical model
incorporating anisotropic and inhomogenous conductivities. The model included the
subthalamic nucleus (STN), substantia nigra (SN), zona incerta (ZI), fields of Forel H2 (FF),
internal capsule (IC) and Medtronic 3387/3389 electrode. To quantify the effects of
stimulation, we extended previous studies by using multi-compartment axon models with
geometry and orientation consistent with anatomical features of the brain regions of interest.
Simulation of axonal firing produced a map of relative changes in axonal activation.
Voltage-controlled stimulation, with clinically typical parameters at the dorso-lateral STN,
caused axon activation up to 4 mm from the target. This activation occurred within the FF, IC,
SN and ZI with current intensities close to the average injected during DBS (3 mA). A
sensitivity analysis of model parameters (fiber size, fiber orientation, degree of inhomogeneity,
degree of anisotropy, electrode configuration) revealed that the FF and IC were consistently
activated. Direct activation of axons outside the STN suggests that other brain regions may be
involved in the beneficial effects of DBS when treating Parkinsonian symptoms.
1. Introduction
Deep brain stimulation (DBS) of the subthalamic nucleus
(STN) has been used extensively for treatment of advanced
stages of Parkinson’s disease [1–3]. The mechanism by which
DBS produces clinical benefit, however, remains uncertain
[4]. Understanding the mechanism of DBS is an important
step to improving stimulator devices and also to applying
high frequency stimulation to other diseases [5, 6]. However,
the several types of neuronal effects that may be induced by
STN stimulation make understanding this mechanism difficult.
Neurons can be affected directly by the stimulating field or
can be indirectly affected trans-synaptically in the neuronal
network. Furthermore, both short-term [7] and long-term
effects [8] occur.
A key issue to gain insight into the mechanisms of DBS
is to determine which brain regions are directly immediately
affected by the electric stimulus and whether only the target
nucleus or other regions too are affected. Indirect effects will
then originate from these directly affected regions of the brain.
One approach to this issue is to apply physical principles to
model the effects of electric fields within the brain. These
effects are governed by the second spatial difference of the
field’s electric potential, known as the activating function
[9], which has been used in computer models to predict the
volume of activated tissue [10, 11]. However, coupling the
stimulation-evoked electric field to multi-compartment neuron
models provides a more precise prediction of activated neurons
[12, 13] and will be used throughout the models described here.
Multi-compartment models of whole cells can be implemented
and studied through computer simulations. However, the large
number of anatomical and electrophysiological parameters
needed for such models makes them difficult to constrain,
particularly given the limited number of ultrastructural and
physiological studies for the regions of interest in primates
[14–17]. Since axons are more excitable than cell bodies and
dendritic fields [18, 19], and are thought to be the main target
processes of DBS [20, 21], we focus here on the firing of axons
evoked by the electric field during DBS. Models of axons alone
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