Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus

McIntyre, Cameron C.; Mori, Susumu; Sherman, David; Thakor, Nitish V.; Vitek, Jerrold L.

doi:10.1016/j.clinph.2003.10.033

Cited by 454 publications

(390 citation statements)

References 39 publications

Supporting

Mentioning

367

Contrasting

Unclassified

Order By: Relevance

“…The use of homogeneous isotropic subdomians of the encapsulation and bulk tissue medium are gross simplifications of the three-dimensionally complex tissue micro-and macro-structure surrounding implanted electrodes (Haberler et al, 2000;McIntyre et al, 2004c;Moss et al, 2004). In turn, a more accurate representation of the tissue medium will undoubtedly introduce additional variability in the impedance.…”

Section: Discussionmentioning

confidence: 99%

Sources and effects of electrode impedance during deep brain stimulation

Butson

Maks

McIntyre

2006

Clinical Neurophysiology

Self Cite

320

281

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Sources and effects of electrode impedance during deep brain stimulation

Butson

Maks

McIntyre

2006

Clinical Neurophysiology

Self Cite

320

281

View full text Add to dashboard Cite

show abstract

“…The anisotropy of white matter was not modelled. The anisotropy of white matter has earlier been accounted for in modelling studies with promising results by deriving electrical conductivity tensors from diffusion tensor images (DTI) [35]. However, the resolution of the DTI images that can be produced with 1.5 Tesla scanners is rather poor and the small anisotropic fibre paths in the vicinity of the electrode e.g.…”

Section: Discussionmentioning

confidence: 99%

Method for patient-specific finite element modeling and simulation of deep brain stimulation

Åström

Zrinzo

Tisch

et al. 2008

Med Biol Eng Comput

View full text Add to dashboard Cite

Deep brain stimulation (DBS) is an established treatment for Parkinson's disease (PD). Success of DBS is highly dependent on electrode location and electrical parametersettings. The aim of this study was to develop a general method for setting up patient-specific 3D computer models of DBS, based on magnetic resonance images, and to demonstrate the use of such models for assessing the position of the electrode contacts and the distribution of the electric field in relation to individual patient anatomy. A software tool was developed for creating finite element DBS-models. The electric field generated by DBS was simulated in one patient and the result was visualized with isolevels and glyphs. The result was evaluated and corresponded well with reported effects and side effects of stimulation. It was demonstrated that patient-specific finite element models and simulations of DBS can be useful for increasing the understanding of the clinical outcome of DBS.

show abstract

“…The first involved looking at the voltage distributions along the axon initial segments (AISs) of the modeled neurons. Using a typical value for the AIS (δ = 30 μm) as a characteristic length scale, the characteristic function involving the second difference of the voltage along the AIS was formed (McIntyre and Grill 1999;Rattay 1986;Rattay 1988;Warman et al 1992;McIntyre et al 2004):…”

Section: External Field Stimulationmentioning

confidence: 99%

Studies of stimulus parameters for seizure disruption using neural network simulations

et al. 2007

View full text Add to dashboard Cite

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 μm × 800 μm region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 Hz to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.

show abstract

Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus

Cited by 454 publications

References 39 publications

Sources and effects of electrode impedance during deep brain stimulation

Sources and effects of electrode impedance during deep brain stimulation

Method for patient-specific finite element modeling and simulation of deep brain stimulation

Studies of stimulus parameters for seizure disruption using neural network simulations

Contact Info

Product

Resources

About