Analysis of Movement-Related Beta Oscillations in the Off-Medication State During Subthalamic Nucleus Deep Brain Stimulation Surgery

Cortical and Subthalamic Nucleus Spectral Changes During Limb Movements in Parkinson's Disease Patients with and Without Dystonia

BACKGROUND

Dystonia is an understudied motor feature of Parkinson's disease (PD). Although considerable efforts have focused on brain oscillations related to the cardinal symptoms of PD, whether dystonia is associated with specific electrophysiological features is unclear.

OBJECTIVE

The objective of this study was to investigate subcortical and cortical field potentials at rest and during contralateral hand and foot movements in patients with PD with and without dystonia.

METHODS

We examined the prevalence and distribution of dystonia in patients with PD undergoing deep brain stimulation surgery.  During surgery, we recorded intracranial electrophysiology from the motor cortex and directional electrodes in the subthalamic nucleus (STN) both at rest and during self-paced repetitive contralateral hand and foot movements. Wavelet transforms and mixed models characterized changes in spectral content in patients with and without dystonia.

RESULTS

Dystonia was highly prevalent at enrollment (61%) and occurred most commonly in the foot. Regardless of dystonia status, cortical recordings display beta (13-30 Hz) desynchronization during movements versus rest, while STN signals show increased power in low frequencies (6.0 ± 3.3 and 4.2 ± 2.9 Hz peak frequencies for hand and foot movements, respectively). Patients with PD with dystonia during deep brain stimulation surgery displayed greater M1 beta power at rest and STN low-frequency power during movements versus those without dystonia.

CONCLUSIONS

Spectral power in motor cortex and STN field potentials differs markedly during repetitive limb movements, with cortical beta desynchronization and subcortical low-frequency synchronization, especially in patients with PD with dystonia. Greater knowledge on field potential dynamics in human motor circuits can inform dystonia pathophysiology in PD and guide novel approaches to therapy. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The future perspectives of psychiatric neurosurgery

The future of psychiatric neurosurgery can be viewed from two separate perspectives: the immediate future and the distant future. Both show promise, but the treatment strategy for mental diseases and the technology utilized during these separate periods will likely differ dramatically. It can be expected that the initial advancements will be built upon progress of neuroimaging and stereotactic targeting while surgical technology becomes adapted to patient-specific symptomatology and structural/functional imaging parameters. This individualized approach has already begun to show significant promise when applied to deep brain stimulation for treatment-resistant depression and obsessive-compulsive disorder. If effectiveness of these strategies is confirmed by well designed, double-blind, placebo-controlled clinical studies, further technological advances will continue into the distant future, and will likely involve precise neuromodulation at the cellular level, perhaps using wireless technology with or without closed-loop design. This approach, being theoretically less invasive and carrying less risk, may ultimately propel psychiatric neurosurgery to the forefront in the treatment algorithm of mental illness. Despite prominent development of non-invasive therapeutic options, such as stereotactic radiosurgery or transcranial magnetic resonance-guided focused ultrasound, chances are there will still be a need in surgical management of patients with most intractable psychiatric conditions.

Temporal Patterns of Spontaneous Fixational Eye Movements: The Influence of Basal Ganglia

BACKGROUND

Spontaneity is a unique feature of the nervous system. One of the fundamentally critical and recognized forms of spontaneous motor activity is witnessed in the visuomotor system. Microsaccades, the miniature spontaneous eye movements, are critical for the visual perception. We hypothesized that microsaccades follow specific temporal patterns that are modulated by the basal ganglia output.

METHODS

We used high-resolution video-oculography to capture microsaccades in 48 subjects (31 healthy and 17 with Parkinson's disease) when subjects were asked to hold their gaze on a straight-ahead target projected on white background. We analyzed spontaneous discharge patterns of microsaccades.

RESULTS

The first analysis considering coefficient of variation in intersaccadic interval distribution demonstrated that microsaccades in Parkinson's disease are more dispersed than the control group. The second analysis scrutinized microsaccades' temporal variability and revealed 3 distinct occurrence patterns: regular rhythmic, clustered, and randomly occurring following a Poisson-like process. The regular pattern was relatively more common in Parkinson's disease. Subthalamic DBS modulated this temporal pattern. The amount of change in the temporal variability depended on the DBS-induced volume of tissue activation and its overlap with the subthalamic nucleus. The third analysis determined the autocorrelations of microsaccades within 2-second time windows. We found that Parkinson's disease altered local temporal organization in microsaccade generation, and DBS had a modulatory effect.

CONCLUSION

The microsaccades occur in 3 temporal patterns. The basal ganglia are one of the modulators of the microsaccade spontaneity.

Is there a single beta oscillation band interfering with movement in Parkinson's disease?

Beta oscillations in basal ganglia are considered to contribute to motor dysfunction in Parkinson's disease (PD). However, there is a high variety in frequency borders for beta oscillations between studies, which complicates the comparison and interpretation of results. Here we aimed to study the homogeneity of oscillations in the broad "beta" range (8-30 Hz) and their implication to motor functioning in PD. For this purpose, we recorded local field potentials (LFP) in the subthalamic nucleus (STN) during 34 deep brain stimulation surgeries. We identified spectral features of LFP recordings in the range 8-30 Hz to search for candidate sub-regions of stable oscillations and assessed their association with clinical scores on the contralateral side of the body and sensitivity to motor tests. Lower frequency oscillations (8-16 Hz) had a significant positive association with bradykinesia score. During voluntary movements, we observed a significant increase in LFP power in the 12-16 Hz range and a decrease in the 18-26 Hz range. We may conclude that the 8-30 Hz oscillation range includes oscillations with different functional features-sensitivity and responsiveness to movement, and clinical symptoms, which should be taken into account in further studies of beta oscillations association with PD pathophysiology. These data assume the coexistence of several frequency domains within beta range that are modulated in different ways under dopaminergic regulation and motor processing in human STN.

Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter

Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-β range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher β₂ activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-β range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP β-band encodes phenotype-movement dependent information in PD patients.