Despite the clinical success of deep brain stimulation (DBS) for the treatment of movement disorders, many questions remain about its effects on the nervous system. We have developed a methodology to predict the volume of tissue activated (VTA) by DBS on a patient-specific basis. Our goals are to identify the intersection between the VTA and surrounding anatomical structures and to compare activation of these structures with clinical outcomes. The model system consists of three fundamental components: 1) a 3D anatomical model of the subcortical nuclei and DBS electrode position in the brain, each derived from magnetic resonance imaging (MRI); 2) a finite element model of the DBS electrode and electric field transmitted to the brain, with tissue conductivity properties derived from diffusion tensor MRI; 3) VTA prediction derived from the response of myelinated axons to the applied electric field, which is a function of the stimulation parameters (contact, impedance, voltage, pulse width, frequency). We used this model system to analyze the effects of subthalamic nucleus (STN) DBS in a patient with Parkinson's disease. Quantitative measurements of bradykinesia, rigidity, and corticospinal tract (CST) motor thresholds were evaluated over a range of stimulation parameter settings. Our model predictions showed good agreement with CST thresholds. Additionally, stimulation through electrode contacts that improved bradykinesia and rigidity generated VTAs that overlapped the zona incerta / fields of Forel (ZI/H2). Application of DBS technology to various neurological disorders has preceded scientific characterization of the volume of tissue directly affected by the stimulation. Synergistic integration of clinical analysis, neuroimaging, neuroanatomy, and neurostimulation modeling provides the opportunity to address wide ranging questions on the factors linked with the therapeutic benefits and side effects of DBS.

DBS has rapidly emerged as an effective treatment for movement disorders; however, little is known about the VTA during therapeutic stimulation. In addition, the influence of tissue and electrode capacitance has been largely ignored in previous models of neural stimulation. The results and methodology of this study provide the foundation for the quantitative analysis of the VTA during clinical neurostimulation.

Objective-Clinical impedance measurements for deep brain stimulation (DBS) electrodes in human patients are normally in the range 500-1500 Ω. DBS devices utilize voltage-controlled stimulation; therefore, the current delivered to the tissue is inversely proportional to the impedance. The goals of this study were to evaluate the effects of various electrical properties of the tissue medium and electrode-tissue interface on the impedance and to determine the impact of clinically relevant impedance variability on the volume of tissue activated (VTA) during DBS.Methods-Axisymmetric finite-element models (FEM) of the DBS system were constructed with explicit representation of encapsulation layers around the electrode and implanted pulse generator. Impedance was calculated by dividing the stimulation voltage by the integrated current density along the active electrode contact. The models utilized a Fourier FEM solver that accounted for the capacitive components of the electrode-tissue interface during voltagecontrolled stimulation. The resulting time-and space-dependent voltage waveforms generated in the tissue medium were superimposed onto cable model axons to calculate the VTA.Results-The primary determinants of electrode impedance were the thickness and conductivity of the encapsulation layer around the electrode contact and the conductivity of the bulk tissue medium. The difference in the VTA between our low (790 Ω) and high (1244 Ω) impedance models with typical DBS settings (−3 V, 90 μs, 130 Hz pulse train) was 121 mm 3 , representing a 52% volume reduction.Conclusions-Electrode impedance has a substantial effect on the VTA and accurate representation of electrode impedance should be an explicit component of computational models of voltage-controlled DBS.Significance-Impedance is often used to identify broken leads (for values >2000 Ω) or short circuits in the hardware (for values <50 Ω); however, clinical impedance values also represent an important parameter in defining the spread of stimulation during DBS.

The subthalamic nucleus (STN) is the most common target for the treatment of Parkinson's disease (PD) with deep brain stimulation (DBS). DBS of the globus pallidus internus (GPi) is also effective in the treatment of PD. The output fibers of the GPi that form the lenticular fasciculus pass in close proximity to STN DBS electrodes. In turn, both STN projection neurons and GPi fibers of passage represent possible therapeutic targets of DBS in the STN region. We built a comprehensive computational model of STN DBS in parkinsonian macaques to study the effects of stimulation in a controlled environment. The model consisted of three fundamental components: 1) a three-dimensional (3D) anatomical model of the macaque basal ganglia, 2) a finite element model of the DBS electrode and electric field transmitted to the tissue medium, and 3) multicompartment biophysical models of STN projection neurons, GPi fibers of passage, and internal capsule fibers of passage. Populations of neurons were positioned within the 3D anatomical model. Neurons were stimulated with electrode positions and stimulation parameters defined as clinically effective in two parkinsonian monkeys. The model predicted axonal activation of STN neurons and GPi fibers during STN DBS. Model predictions regarding the degree of GPi fiber activation matched well with experimental recordings in both monkeys. Only axonal activation of the STN neurons showed a statistically significant increase in both monkeys when comparing clinically effective and ineffective stimulation. Nonetheless, both neural targets may play important roles in the therapeutic mechanisms of STN DBS.

Deep brain stimulation (DBS) is an established clinical treatment for a range of neurological disorders. Depending on the disease state of the patient, different anatomical structures such as the ventral intermediate nucleus of the thalamus (VIM), the subthalamic nucleus or the globus pallidus are targeted for stimulation. However, the same electrode design is currently used in nearly all DBS applications, even though substantial morphological and anatomical differences exist between the various target nuclei. The fundamental goal of this study was to develop a theoretical understanding of the impact of changes in the DBS electrode contact geometry on the volume of tissue activated (VTA) during stimulation. Finite element models of the electrodes and surrounding medium were coupled to cable models of myelinated axons to predict the VTA as a function of stimulation parameter settings and electrode design. Clinical DBS electrodes have cylindrical contacts 1.27 mm in diameter (d) and 1.5 mm in height (h). Our results show that changes in contact height and diameter can substantially modulate the size and shape of the VTA, even when contact surface area is preserved. Electrode designs with a low aspect ratio (d/h) maximize the VTA by providing greater spread of the stimulation parallel to the electrode shaft without sacrificing lateral spread. The results of this study provide the foundation necessary to customize electrode design and VTA shape for specific anatomical targets, and an example is presented for the VIM. A range of opportunities exist to engineer DBS systems to maximize stimulation of the target area while minimizing stimulation of non-target areas. Therefore, it may be possible to improve therapeutic benefit and minimize side effects from DBS with the design of target-specific electrodes.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become the surgical therapy of choice for medically intractable Parkinson's disease. However, quantitative understanding of the interaction between the electric field generated by DBS and the underlying neural tissue is limited. Recently, computational models of varying levels of complexity have been used to study the neural response to DBS. The goal of this study was to evaluate the quantitative impact of incrementally incorporating increasing levels of complexity into computer models of STN DBS. Our analysis focused on the direct activation of experimentally measureable fiber pathways within the internal capsule (IC). Our model system was customized to an STN DBS patient and stimulation thresholds for activation of IC axons were calculated with electric field models that ranged from an electrostatic, homogenous, isotropic model to one that explicitly incorporated the voltage-drop and capacitance of the electrode-electrolyte interface, tissue encapsulation of the electrode, and diffusion-tensor based 3D tissue anisotropy and inhomogeneity. The model predictions were compared to experimental IC activation defined from electromyographic (EMG) recordings from eight different muscle groups in the contralateral arm and leg of the STN DBS patient. Coupled evaluation of the model and experimental data showed that the most realistic predictions of axonal thresholds were achieved with the most detailed model. Furthermore, the more simplistic neurostimulation models substantially overestimated the spatial extent of neural activation. Keywords deep brain stimulation; computational modeling; neural activation; Parkinson's disease

Objective-Despite the clinical success of deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD), little is known about the electrical spread of the stimulation. The primary goal of this study was to integrate neuroimaging, neurophysiology, and neurostimulation data sets from 10 PD patients, unilaterally implanted with subthalamic nucleus (STN) DBS electrodes, to identify the theoretical volume of tissue activated (VTA) by clinically defined therapeutic stimulation parameters.Methods-Each patient-specific model was created with a series of five steps: 1) definition of the neurosurgical stereotactic coordinate system within the context of pre-operative imaging data; 2) entry of intra-operative microelectrode recording locations from neurophysiologically defined thalamic, subthalamic, and substantia nigra neurons into the context of the imaging data; 3) fitting a 3D brain atlas to the neuroanatomy and neurophysiology of the patient; 4) positioning the DBS electrode in the documented stereotactic location, verified by post-operative imaging data; and 5) calculation of the VTA using a diffusion tensor based finite element neurostimulation model. Results-The patient-specific models show that therapeutic benefit was achieved with direct stimulation of a wide range of anatomical structures in the subthalamic region. Interestingly, of the 5 patients exhibiting a greater than 40% improvement in their unified PD rating scale (UPDRS), all but one had the majority of their VTA outside the atlas defined borders of the STN. Further, of the 5 patients with less than 40% UPDRS improvement all but one had the majority of their VTA inside the STN.Conclusions-Our results are consistent with previous studies suggesting that therapeutic benefit is associated with electrode contacts near the dorsal border of the STN, and provide quantitative estimates of the electrical spread of the stimulation in a clinically relevant context.

These results provide motivation for the integration of current steering technology into clinical DBS systems, thereby expanding opportunities to customize DBS to individual patients, and potentially enhancing therapeutic efficacy.