Relationship between neural activation and electric field distribution during deep brain stimulation.

Models and simulations are commonly used to study deep brain stimulation (DBS). Simulated stimulation fields are often defined and visualized by electric field isolevels or volumes of tissue activated (VTA). The aim of the present study was to evaluate the relationship between stimulation field strength as defined by the electric potential V, the electric field E, and the divergence of the electric field ∇(2) V, and neural activation. Axon cable models were developed and coupled to finite-element DBS models in three-dimensional (3-D). Field thresholds ( VT , ET, and ∇(2) VT ) were derived at the location of activation for various stimulation amplitudes (1 to 5 V), pulse widths (30 to 120 µs), and axon diameters (2.0 to 7.5 µm). Results showed that thresholds for VT and ∇(2) VT were highly dependent on the stimulation amplitude while ET were approximately independent of the amplitude for large axons. The activation field strength thresholds presented in this study may be used in future studies to approximate the VTA during model-based investigations of DBS without the need of computational axon models.

Proceedings of the Second Annual Deep Brain Stimulation Think Tank: What's in the Pipeline.

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Efficacy of a new charge-balanced biphasic electrical stimulus in the isolated sciatic nerve and the hippocampal slice.

Most deep brain stimulators apply rectangular monophasic voltage pulses. By modifying the stimulus shape, it is possible to optimize stimulus efficacy and find the best compromise between clinical effect, minimal side effects and power consumption of the stimulus generator. In this study, we compared the efficacy of three types of charge-balanced biphasic pulses (CBBPs, nominal duration 100 µs) in isolated sciatic nerves and in in vitro hippocampal brain slices of the rat. Using these two models, we tested the efficacy of several stimulus shapes exclusively on axons (in the sciatic nerve) and compared the effect with that of stimuli in the more complex neuronal network of the hippocampal slice by considering the stimulus-response relation. We showed that (i) adding an interphase gap (IPG, range 100-500 µs) to the CBBP enhances stimulus efficacy in the rat sciatic nerve and (ii) that this type of stimuli (CBBP with IPG) is also more effective in hippocampal slices. This benefit was similar for both models of voltage and current stimulation. In our two models, asymmetric CBBPs were less beneficial. Therefore, CBBPs with IPG appear to be well suited for application to DBS, since they enhance efficacy, extend battery life and potentially reduce harmful side effects.

Motor cortex stimulation for Parkinson's disease: a modelling study.

Chronic motor cortex stimulation (MCS) is currently being investigated as a treatment method for Parkinson's disease (PD). Unfortunately, the underlying mechanisms of this treatment are unclear and there are many uncertainties regarding the most effective stimulation parameters and electrode configuration. In this paper, we present a MCS model with a 3D representation of several axonal populations. The model predicts that the activation of either the basket cell or pyramidal tract (PT) type axons is involved in the clinical effect of MCS. We propose stimulation protocols selectively targeting one of these two axon types. To selectively target the basket cell axons, our simulations suggest using either cathodal or bipolar stimulation with the electrode strip placed perpendicular rather than parallel to the gyrus. Furthermore, selectivity can be increased by using multiple cathodes. PT type axons can be selectively targeted with anodal stimulation using electrodes with large contact sizes. Placing the electrode epidurally is advisable over subdural placement. These selective protocols, when practically implemented, can be used to further test which axon type should be activated for clinically effective MCS and can subsequently be applied to optimize treatment. In conclusion, this paper increases insight into the neuronal population involved in the clinical effect of MCS on PD and proposes strategies to improve this therapy.

Automatic subthalamic nucleus detection from microelectrode recordings based on noise level and neuronal activity.

Microelectrode recording (MER) along surgical trajectories is commonly applied for refinement of the target location during deep brain stimulation (DBS) surgery. In this study, we utilize automatically detected MER features in order to locate the subthalamic nucleus (STN) employing an unsupervised algorithm. The automated algorithm makes use of background noise level, compound firing rate and power spectral density along the trajectory and applies a threshold-based method to detect the dorsal and the ventral borders of the STN. Depending on the combination of measures used for detection of the borders, the algorithm allocates confidence levels for the annotation made (i.e. high, medium and low). The algorithm has been applied to 258 trajectories obtained from 84 STN DBS implantations. MERs used in this study have not been pre-selected or pre-processed and include all the viable measurements made. Out of 258 trajectories, 239 trajectories were annotated by the surgical team as containing the STN versus 238 trajectories by the automated algorithm. The agreement level between the automatic annotations and the surgical annotations is 88%. Taking the surgical annotations as the golden standard, across all trajectories, the algorithm made true positive annotations in 231 trajectories, true negative annotations in 12 trajectories, false positive annotations in 7 trajectories and false negative annotations in 8 trajectories. We conclude that our algorithm is accurate and reliable in automatically identifying the STN and locating the dorsal and ventral borders of the nucleus, and in a near future could be implemented for on-line intra-operative use.

Steering deep brain stimulation fields using a high resolution electrode array.

Deep brain stimulation (DBS) therapy relies on electrical stimulation of neuronal elements in small brain targets. However, the lack of fine spatial control over field distributions in current systems implies that stimulation easily spreads into adjacent structures that may induce adverse side-effects. This study investigates DBS field steering using a novel DBS lead design carrying a high-resolution electrode array. We apply computational models to simulate voltage distributions and DBS activation volumes in order to theoretically assess the potential of field steering in DBS. Our computational analysis demonstrates that the DBS-array is capable of accurately displacing activation volumes with sub-millimeter precision. Our findings demonstrate that future systems for DBS therapy may provide for more accurate target coverage than currently available systems achieve.

Frequency-selectivity of a thalamocortical relay neuron during Parkinson's disease and deep brain stimulation: a computational study.

In this computational study, we investigated (i) the functional importance of correlated basal ganglia (BG) activity associated with Parkinson's disease (PD) motor symptoms by analysing the effects of globus pallidus internum (GPi) bursting frequency and synchrony on a thalamocortical (TC) relay neuron, which received GABAergic projections from this nucleus; (ii) the effects of subthalamic nucleus (STN) deep brain stimulation (DBS) on the response of the TC relay neuron to synchronized GPi oscillations; and (iii) the functional basis of the inverse relationship that has been reported between DBS frequency and stimulus amplitude, required to alleviate PD motor symptoms [A. L. Benabid et al. (1991)Lancet, 337, 403-406]. The TC relay neuron selectively responded to and relayed synchronized GPi inputs bursting at a frequency located in the range 2-25 Hz. Input selectivity of the TC relay neuron is dictated by low-threshold calcium current dynamics and passive membrane properties of the neuron. STN-DBS prevented the TC relay neuron from relaying synchronized GPi oscillations to cortex. Our model indicates that DBS alters BG output and input selectivity of the TC relay neuron, providing an explanation for the clinically observed inverse relationship between DBS frequency and stimulus amplitude.