Modeling and simulation of deep brain stimulation electrodes with various active contacts

A Review on Implantable Neuroelectrodes

The efficacy of every neuromodulation modality depends upon the characteristics of the electrodes used to stimulate the chosen target. The geometrical, chemical, mechanical and physical configuration of electrodes used in neurostimulation affects several performance attributes like stimulation efficiency, selectivity, tissue response, etc. The efficiency of stimulation in relation to electrode impedance is influenced by the electrode material and/or its geometry. The nature of the electrode material determines the charge transfer across the electrode-tissue interface, which also relates to neuronal tissue damage. Electrode morphology or configuration pattern can facilitate the modulation of extracellular electric field (field shaping). This enables selective activation of neurons and minimizes side effects. Biocompatibility and biostability of the electrode materials or electrode coating have a role in glial formation and tissue damage. Mechanical and electrochemical stability (corrosion resistance) determines the long-term efficacy of any neuromodulation technique. Here, a review of electrodes typically used for implantable neuromodulation is discussed. Factors affecting the performance of electrodes like stimulation efficiency, selectivity and tissue responses to the electrode-tissue interface are discussed. Technological advancements to improve electrode characteristics are also included.

Impacts of stimulus parameters and configurations on motor cortex direct electrical stimulation using intrinsic optical imaging: a pilot study

Background

Motor cortex stimulation applied as a clinical treatment for neuropathic disorders for decades. With stimulation electrodes placed directly on the cortical surface, this neuromodulation method provides higher spatial resolution than other non-invasive therapies. Yet, the therapeutic effects reported were not in conformity with different syndromes. One of the main issues is that the stimulation parameters are always determined by clinical experience. The lack of understanding about how the stimulation current propagates in the cortex and various stimulation parameters and configurations obstruct the development of this method.

Methods

In this study, we investigated the effect of different stimulation configurations on cortical responses to motor cortical stimulations using intrinsic optical imaging.

Results

Our results showed that the cortical activation of electrical stimulation is not only related to the current density but also related to the propagation distance. Besides, stimulation configurations also affect the propagation of the stimulation current.

Conclusions

All these results provide preliminary experimental evidence for parameter and electrode configuration optimizations.

Deep brain stimulation: Challenges at the tissue-electrode interface and current solutions

Deep brain stimulation (DBS) is used to treat the motor symptoms of Parkinson's disease patients by stimulating the subthalamic nucleus. However, optimization of DBS is still needed since the performance of the neural electrodes is limited by the body's response to the implant. This review discusses the issues with DBS, such as placement of electrodes, foreign body response, and electrode degradation. The current solutions to these technical issues include modifications to electrode material, coatings, and geometry.

Role of skin tissue layers and ultra-structure in transcutaneous electrical stimulation including tDCS

BACKGROUND

During transcranial electrical stimulation (tES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), current density concentration around the electrode edges that is predicted by simplistic skin models does not match experimental observations of erythema, heating, or other adverse events. We hypothesized that enhancing models to include skin anatomical details, would alter predicted current patterns to align with experimental observations.

METHOD

We develop a high-resolution multi-layer skin model (epidermis, dermis, and fat), with or without additional ultra-structures (hair follicles, sweat glands, and blood vessels). Current flow patterns across each layer and within ultra-structures were predicted using finite element methods considering a broad range of modeled tissue parameters including 78 combinations of skin layer conductivities (S m^-1): epidermis (standard: 1.05 × 10^-5; range: 1.05 × 10^-6 to 0.465); dermis (standard: 0.23; range: 0.0023 to 23), fat (standard: 2 × 10^-4; range: 0.02 to 2 × 10^-5). The impact of each ultra-structures in isolation and combination was evaluated with varied basic geometries. An integrated final model is then developed.

RESULTS

Consistent with prior models, current flow through homogenous skin was annular (concentrated at the electrode edges). In multi-layer skin, reducing epidermis conductivity and/or increasing dermis conductivity decreased current near electrode edges, however no realistic tissue layer parameters produced non-annular current flow at both epidermis and dermis. Addition of just hair follicles, sweat glands, or blood vessels resulted in current peaks around each ultrastructure, irrespective of proximity to electrode edges. Addition of only sweat glands was the most effective approach in reducing overall current concentration near electrode edges. Representation of blood vessels resulted in a uniform current flow across the vascular network. Finally, we ran the first realistic model of current flow across the skin.

CONCLUSION

We confirm prior models exhibiting current concentration near hair follicles or sweat glands, but also exhibit that an overall annular pattern of current flow remains for realistic tissue parameters. We model skin blood vessels for the first time and show that this robustly distributes current across the vascular network, consistent with experimental erythema patterns. Only a state-of-the-art precise model of skin current flow predicts lack of current concentration near electrode edges across all skin layers.