Deep brain stimulation of the subthalamic nucleus in Parkinson disease 2013-2023: where are we a further 10 years on?

Deep brain stimulation has been in clinical use for 30 years and during that time it has changed markedly from a small-scale treatment employed by only a few highly specialized centers into a widespread keystone approach to the management of disorders such as Parkinson's disease. In the intervening decades, many of the broad principles of deep brain stimulation have remained unchanged, that of electrode insertion into stereotactically targeted brain nuclei, however the underlying technology and understanding around the approach have progressed markedly. Some of the most significant advances have taken place over the last decade with the advent of artificial intelligence, directional electrodes, stimulation/recording implantable pulse generators and the potential for remote programming among many other innovations. New therapeutic targets are being assessed for their potential benefits and a surge in the number of deep brain stimulation implantations has given birth to a flourishing scientific literature surrounding the pathophysiology of brain disorders such as Parkinson's disease. Here we outline the developments of the last decade and look to the future of deep brain stimulation to attempt to discern some of the most promising lines of inquiry in this fast-paced and rapidly evolving field.

Synchrony Drives Motor Cortex Beta Bursting, Waveform Dynamics, and Phase-Amplitude Coupling in Parkinson's Disease.

Several lines of inquiry have separately identified beta oscillations, synchrony, waveform shape, and phase-amplitude coupling as important but sometimes inconsistent factors in the pathophysiology of Parkinson's disease. What has so far been lacking is a means by which these neurophysiological parameters are interrelated and how they relate to clinical symptomatology. To clarify the relationship among oscillatory power, bursting, synchrony, and phase-amplitude coupling, we recorded local field potentials/electrocorticography from hand motor and premotor cortical area in human subjects with c (N = 10) and Parkinson's disease (N = 22) during deep brain stimulator implantation surgery (14 females, 18 males). We show that motor cortical high beta oscillations in Parkinson's disease demonstrate increased burst durations relative to essential tremor patients. Notably, increased corticocortical synchrony between primary motor and premotor cortices precedes motor high beta bursts, suggesting a possible causal relationship between corticocortical synchrony and localized increases in beta power. We further show that high beta bursts are associated with significant changes in waveform shape and that beta-encoded phase-amplitude coupling is more evident during periods of high beta bursting. These findings reveal a deeper structure to the pathologic changes identified in the neurophysiology of Parkinson's disease, suggesting mechanisms by which the treatment may be enhanced using targeted network synchrony disruption approaches.SIGNIFICANCE STATEMENT Understanding Parkinson's disease pathophysiology is crucial for optimizing symptom management. Present inconsistencies in the literature may be explained by temporal transients in neural signals driven by transient fluctuations in network synchrony. Synchrony may also act as a unifying phenomenon for the pathophysiological observations reported in Parkinson's disease. Here, simultaneous recordings from motor cortices show that increases in network beta synchrony anticipate episodes of beta bursting. We furthermore identify beta bursting as being associated with changes in waveform shape and increases in phase-amplitude coupling. Our results identify network synchrony as a driver of various pathophysiological observations reported in the literature and account for inconsistencies in the literature by virtue of the temporally variable nature of the phenomenon.

Pallidal stimulation in Parkinson disease differentially modulates local and network ß activity.

ß hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. OBJECTIVES: We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex. APPROACH: We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open. MAIN RESULTS: DBS significantly suppressed low ß power within the GPi (-26.98% ± 15.14%), p < 0.05) without modulation of sensorimotor cortical ß power (low or high). In contrast, stimulation suppressed pallidocortical high ß coherence (-38.89% ± 6.19%, p = 0.02) and dWPLI (-61.40% ± 8.75%, p = 0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex. SIGNIFICANCE: We highlight the role of DBS in desynchronizing network activity, particularly in the high ß band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low ß oscillations locally within the basal ganglia and high ß oscillations across the BGTC motor circuit.

Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments.

BACKGROUND: Over the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson's disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy. METHODS: In this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon's map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification. RESULTS: The results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively. CONCLUSIONS: This research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.

Oxford craniotomy infections database: a cost analysis of craniotomy infection.

We describe the process of establishing a large database for the investigation of craniotomy infection and the preliminary results of this database. The initial results have been used to generate a cost analysis for craniotomy infection. The craniotomy infections database prospectively registers craniotomy cases taking place in the John Radcliffe Hospital. In order to achieve this, each patient's details are registered at the time of operation and followed up to identify cases of infection. Infection was defined strictly according to Centre for Disease Control criteria and validated by at least two members of clinical staff. The first 10 months of data are presented here which identifies a total of 245 craniotomies and 20 verified craniotomy infections. An overall infection rate of 8% is identified, and the cost incurred by the neurosurgery department as a result of craniotomy infections is estimated at £1 85 660 for the 10-month period studied. This amounts to a cost per case of infection of £9283.