Subthalamic local field potentials in Parkinson's disease and isolated dystonia: An evaluation of potential biomarkers

B(RAIN)2-BRAIN integrated Resource for Anatomy and Intracranial Neurophysiology

The Brain Integrated Resource for Human Anatomy and Intracranial Neurophysiology (B(RAIN)2) is a multi-center data resource that provides standardized imaging and intracranial neurophysiological data from patients who have undergone deep brain stimulation (DBS) implantation with intracranial electroencephalography (iEEG) recordings. The database includes patients' electrophysiological recordings from the cerebral cortex and deeper brain structures, alongside high-resolution neurological imaging scans taken at preoperative, intraoperative, and postoperative stages. The data are systematically organized using the Brain Imaging Data Structure (BIDS) format for imaging data and iEEG-BIDS for intracranial electrophysiological recordings. This standardized structure facilitates data integration, sharing, and analysis across research institutions. Additionally, the database features detailed metadata, such as diagnostic information and neurological assessment scores, providing a comprehensive profile of each patient's data.

Could adaptive deep brain stimulation treat freezing of gait in Parkinson's disease?

Next-generation neurostimulators capable of running closed-loop adaptive deep brain stimulation (aDBS) are about to enter the clinical landscape for the treatment of Parkinson's disease. Already promising results using aDBS have been achieved for symptoms such as bradykinesia, rigidity and motor fluctuations. However, the heterogeneity of freezing of gait (FoG) with its wide range of clinical presentations and its exacerbation with cognitive and emotional load make it more difficult to predict and treat. Currently, a successful aDBS strategy to ameliorate FoG lacks a robust oscillatory biomarker. Furthermore, the technical implementation of suppressing an upcoming FoG episode in real-time represents a significant technical challenge. This review describes the neurophysiological signals underpinning FoG and explains how aDBS is currently being implemented. Furthermore, we offer a discussion addressing both theoretical and practical areas that will need to be resolved if we are going to be able to unlock the full potential of aDBS to treat FoG.

Subthalamic and pallidal oscillations and their couplings reflect dystonia severity and improvements by deep brain stimulation

BACKGROUND

Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) and subthalamic nucleus (STN) is employed for the treatment of dystonia. Pallidal low-frequency oscillations have been proposed as a pathophysiological marker for dystonia. However, the role of subthalamic oscillations and STN-GPi coupling in relation to dystonia remains unclear.

OBJECTIVE

We aimed to explore oscillatory activities within the STN-GPi circuit and their correlation with the severity of dystonia and efficacy achieved by DBS treatment.

METHODS

Local field potentials were recorded simultaneously from the STN and GPi from 13 dystonia patients. Spectral power analysis was conducted for selected frequency bands from both nuclei, while power correlation and the weighted phase lag index were used to evaluate power and phase couplings between these two nuclei, respectively. These features were incorporated into generalized linear models to assess their associations with dystonia severity and DBS efficacy.

RESULTS

The results revealed that pallidal theta power, subthalamic beta power and subthalamic-pallidal theta phase coupling and beta power coupling all correlated with clinical severity. The model incorporating all selected features predicts empirical clinical scores and DBS-induced improvements, whereas the model relying solely on pallidal theta power failed to demonstrate significant correlations.

CONCLUSIONS

Beyond pallidal theta power, subthalamic beta power, STN-GPi couplings in theta and beta bands, play a crucial role in understanding the pathophysiological mechanism of dystonia and developing optimal strategies for DBS.

Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease

Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.

A Systematic Review of Neurophysiology-Based Localization Techniques Used in Deep Brain Stimulation Surgery of the Subthalamic Nucleus

OBJECTIVE

This systematic review is conducted to identify, compare, and analyze neurophysiological feature selection, extraction, and classification to provide a comprehensive reference on neurophysiology-based subthalamic nucleus (STN) localization.

MATERIALS AND METHODS

The review was carried out using the methods and guidelines of the Kitchenham systematic review and provides an in-depth analysis on methods proposed on STN localization discussed in the literature between 2000 and 2021. Three research questions were formulated, and 115 publications were identified to answer the questions.

RESULTS

The three research questions formulated are answered using the literature found on the respective topics. This review discussed the technologies used in past research, and the performance of the state-of-the-art techniques is also reviewed.

CONCLUSION

This systematic review provides a comprehensive reference on neurophysiology-based STN localization by reviewing the research questions other new researchers may also have.

The guiding effect of local field potential during deep brain stimulation surgery for programming in Parkinson's disease patients

BACKGROUND

Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery require subsequent programming, which is complex and cumbersome. The local field potential (LFP) in the deep brain is associated with motor symptom improvement. The current study aimed to identify LFP biomarkers correlated with improved motor symptoms in PD patients after DBS and verify their guiding role in postoperative programming.

METHODS

Initially, the study included 36 PD patients undergoing DBS surgery. Temporary external electrical stimulation was performed during electrode implantation, and LFP signals around the electrode contacts were collected before and after stimulation. The stimulating contact at 6 months of programming was regarded as the optimal and effective stimulating contact. The LFP signal of this contact during surgery was analyzed to identify potential LFP biomarkers. Next, we randomly assigned another 30 PD patients who had undergone DBS to physician empirical programming and LFP biomarker-guided programming groups and compared the outcomes.

RESULTS

In the first part of the study, LFP signals of electrode contacts changed after electrical stimulation. Electrical stimulation reduced gamma energy and the beta/alpha oscillation ratio. The different programming method groups were compared, indicating the superiority of beta/alpha oscillations ratio-guided programming over physician experience programming for patients' improvement rate (IR) of UPDRS-III. There were no significant differences in the IR of UPDRS-III, post-LED, IR-PDQ39, number of programmings, and the contact change rate between the gamma oscillations-guided programming and empirical programming groups.

CONCLUSION

Overall, the findings reveal that gamma oscillations and the beta/alpha oscillations ratio are potential biomarkers for programming in PD patients after DBS. Instead of relying solely on spike action potential signals from single neurons, LFP biomarkers can provide the appropriate depth for electrode placement.

Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop

Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today's technological potential. Adaptive DBS, where stimulation parameters depend on the patient's physiological state, emerges as an important step towards "smart" DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and analytical methods are an important tool to explore the richness of the available data and identify signal properties to close the loop in DBS. To tackle this challenge, machine learning (ML) methods applied to DBS have gained popularity due to their ability to make good predictions in the presence of multiple variables and subtle patterns. ML based approaches are being explored at different fronts such as the identification of electrophysiological biomarkers and the development of personalized control systems, leading to effective symptom relief. In this review, we explore how ML can help overcome the challenges in the development of closed-loop DBS, particularly its role in the search for effective electrophysiology biomarkers. Promising results demonstrate ML potential for supporting a new generation of adaptive DBS, with better management of stimulation delivery, resulting in more efficient and patient-tailored treatments.

Cross-Frequency Coupling and Intelligent Neuromodulation

Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.

Physiology of dystonia: Human studies

In this chapter, we discuss neurophysiological techniques that have been used in the study of dystonia. We examine traditional disease models such as inhibition and excessive plasticity and review the evidence that these play a causal role in pathophysiology. We then review the evidence for sensory and peripheral influences within pathophysiology and look at an emergent literature that tries to probe how oscillatory brain activity may be linked to dystonia pathophysiology.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

The Therapeutic Potential of Non-Invasive and Invasive Cerebellar Stimulation Techniques in Hereditary Ataxias

The degenerative ataxias comprise a heterogeneous group of inherited and acquired disorders that are characterized by a progressive cerebellar syndrome, frequently in combination with one or more extracerebellar signs. Specific disease-modifying interventions are currently not available for many of these rare conditions, which underscores the necessity of finding effective symptomatic therapies. During the past five to ten years, an increasing number of randomized controlled trials have been conducted examining the potential of different non-invasive brain stimulation techniques to induce symptomatic improvement. In addition, a few smaller studies have explored deep brain stimulation (DBS) of the dentate nucleus as an invasive means to directly modulate cerebellar output, thereby aiming to alleviate ataxia severity. In this paper, we comprehensively review the clinical and neurophysiological effects of transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation (rTMS), and dentate nucleus DBS in patients with hereditary ataxias, as well as the presumed underlying mechanisms at the cellular and network level and perspectives for future research.

Subthalamic Nucleus Stimulation-Induced Local Field Potential Changes in Dystonia

BACKGROUND

Subthalamic nucleus (STN) stimulation is an effective treatment for Parkinson's disease and induced local field potential (LFP) changes that have been linked with clinical improvement. STN stimulation has also been used in dystonia although the internal globus pallidus is the standard target where theta power has been suggested as a physiomarker for adaptive stimulation.

OBJECTIVE

We aimed to explore if enhanced theta power was also present in STN and if stimulation-induced spectral changes that were previously reported for Parkinson's disease would occur in dystonia.

METHODS

We recorded LFPs from 7 patients (12 hemispheres) with isolated craniocervical dystonia whose electrodes were placed such that inferior, middle, and superior contacts covered STN, zona incerta, and thalamus.

RESULTS

We did not observe prominent theta power in STN at rest. STN stimulation induced similar spectral changes in dystonia as in Parkinson's disease, such as broadband power suppression, evoked resonant neural activity (ERNA), finely-tuned gamma oscillations, and an increase in aperiodic exponents in STN-LFPs. Both power suppression and ERNA localize to STN. Based on this, single-pulse STN stimulation elicits evoked neural activities with largest amplitudes in STN, which are relayed to the zona incerta and thalamus with changing characteristics as the distance from STN increases.

CONCLUSIONS

Our results show that STN stimulation-induced spectral changes are a nondisease-specific response to high-frequency stimulation, which can serve as placement markers for STN. This broadens the scope of STN stimulation and makes it an option for other disorders with excessive oscillatory peaks in STN. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Effects of Contralateral Deep Brain Stimulation and Levodopa on Subthalamic Nucleus Oscillatory Activity and Phase-Amplitude Coupling

BACKGROUND

The modulatory effects of medication and deep brain stimulation (DBS) on subthalamic nucleus (STN) neural activity in Parkinson's disease have been widely studied. However, effects on the contralateral side to the stimulated STN, in particular, changes in local field potential (LFP) oscillatory activity and phase-amplitude coupling (PAC), have not yet been reported.

OBJECTIVE

The aim of this study was to examine changes in STN LFP activity across a range of frequency bands and STN PAC for different combinations of DBS and medication on/off on the side contralateral to the applied stimulation.

MATERIALS AND METHODS

We examined STN LFPs that were recorded using externalized leads from eight parkinsonian patients during unilateral DBS from the side contralateral to the stimulation. LFP spectral power in alpha (5 to ∼13 Hz), low beta (13 to ∼20 Hz), high beta (20-30 Hz), and high gamma plus high-frequency oscillation (high gamma+HFO) (100-400 Hz) bands were estimated for different combinations of medication and unilateral stimulation (off/on). PAC between beta and high gamma+HFO in the STN LFPs was also investigated. The effect of the condition was examined using linear mixed models.

RESULTS

PAC in the STN LFP was reduced by DBS when compared to the baseline condition (no medication and stimulation). Medication had no significant effect on PAC. Alpha power decreased with DBS, both alone and when combined with medication. Beta power decreased with DBS, medication, and DBS and medication combined. High gamma+HFO power increased during the application of contralateral DBS and was unaltered by medication.

CONCLUSIONS

The results provide new insights into the effects of DBS and levodopa on STN LFP PAC and oscillatory activity on the side contralateral to stimulation. These may have important implications in understanding mechanisms underlying motor improvements with DBS, including changes on both contralateral and ipsilateral sides, while suggesting a possible role for contralateral sensing during unilateral DBS.

Effect and Relationship of Gait on Subcortical Local Field Potentials in Parkinson's Disease: A Systematic Review

OBJECTIVES

Developments in deep brain stimulation (DBS) technology have enabled the ability to detect local field potentials (LFPs) in Parkinson disease (PD). Gait dysfunction is one of the most prevalent deficits seen in PD. However, no consensus has been reached on the effect of gait on LFPs and the relationship between LFPs and clinical measures of gait. The objective of this systematic review was to synthesize existing research regarding the relationship between gait dysfunction and LFPs in PD.

METHODS

A systematic search of the literature yielded a total of ten articles, including 132 patients with PD, which met the criteria for inclusion.

RESULTS

Beta frequency band measures showed low-to-strong correlation to clinical gait measures (r = -0.50 to 0.82). Two studies found decreased beta power during gait; one found increased beta frequency peaks during gait; and one found higher beta power during dual-task gait than during single-task gait. One of the three studies comparing patients with and without freezing found significantly increased beta burst duration and power during gait in freezers compared with nonfreezers. All studies showed moderate-to-high methodologic quality.

CONCLUSIONS

This review highlights the need to consider the effect of gait on LFP recordings, particularly when used to guide DBS programming. Although sample sizes were small, it appears LFPs are associated to and modulated by gait in patients with PD. This evidence suggests that LFPs have the potential to be used as a biomarker of gait dysfunction in PD.

A systematic review of local field potential physiomarkers in Parkinson's disease: from clinical correlations to adaptive deep brain stimulation algorithms

Deep brain stimulation (DBS) treatment has proven effective in suppressing symptoms of rigidity, bradykinesia, and tremor in Parkinson's disease. Still, patients may suffer from disabling fluctuations in motor and non-motor symptom severity during the day. Conventional DBS treatment consists of continuous stimulation but can potentially be further optimised by adapting stimulation settings to the presence or absence of symptoms through closed-loop control. This critically relies on the use of 'physiomarkers' extracted from (neuro)physiological signals. Ideal physiomarkers for adaptive DBS (aDBS) are indicative of symptom severity, detectable in every patient, and technically suitable for implementation. In the last decades, much effort has been put into the detection of local field potential (LFP) physiomarkers and in their use in clinical practice. We conducted a research synthesis of the correlations that have been reported between LFP signal features and one or more specific PD motor symptoms. Features based on the spectral beta band (~ 13 to 30 Hz) explained ~ 17% of individual variability in bradykinesia and rigidity symptom severity. Limitations of beta band oscillations as physiomarker are discussed, and strategies for further improvement of aDBS are explored.

Mitigating Mismatch Compression in Differential Local Field Potentials

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.

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.

Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.

Correlated Activity in the Degenerate Retina Inhibits Focal Response to Electrical Stimulation

Retinal prostheses have shown some clinical success in patients with retinitis pigmentosa and age-related macular degeneration. However, even after the implantation of a retinal prosthesis, the patient’s visual acuity is at best less than 20/420. Reduced visual acuity may be explained by a decrease in the signal-to-noise ratio due to the spontaneous hyperactivity of retinal ganglion cells (RGCs) found in degenerate retinas. Unfortunately, abnormal retinal rewiring, commonly observed in degenerate retinas, has rarely been considered for the development of retinal prostheses. The purpose of this study was to investigate the aberrant retinal network response to electrical stimulation in terms of the spatial distribution of the electrically evoked RGC population. An 8 × 8 multielectrode array was used to measure the spiking activity of the RGC population. RGC spikes were recorded in wild-type [C57BL/6J; P56 (postnatal day 56)], rd1 (P56), rd10 (P14 and P56) mice, and macaque [wild-type and drug-induced retinal degeneration (RD) model] retinas. First, we performed a spike correlation analysis between RGCs to determine RGC connectivity. No correlation was observed between RGCs in the control group, including wild-type mice, rd10 P14 mice, and wild-type macaque retinas. In contrast, for the RD group, including rd1, rd10 P56, and RD macaque retinas, RGCs, up to approximately 400–600 μm apart, were significantly correlated. Moreover, to investigate the RGC population response to electrical stimulation, the number of electrically evoked RGC spikes was measured as a function of the distance between the stimulation and recording electrodes. With an increase in the interelectrode distance, the number of electrically evoked RGC spikes decreased exponentially in the control group. In contrast, electrically evoked RGC spikes were observed throughout the retina in the RD group, regardless of the inter-electrode distance. Taken together, in the degenerate retina, a more strongly coupled retinal network resulted in the widespread distribution of electrically evoked RGC spikes. This finding could explain the low-resolution vision in prosthesis-implanted patients.

Frequency Nesting Interactions in the Subthalamic Nucleus Correlate With the Step Phases for Parkinson's Disease

Gait disturbance in Parkinson's disease (PD) can be ameliorated by sound stimulation. Given that excessive β synchronization in basal ganglia is linked to motor impairment in PD, whether the frequency nesting interactions are associated with the gait problem is far from clear. To this end, the masking phase-amplitude coupling (PAC) method was proposed to overcome the trade-off between intrinsic nonlinearity/non-stationarity and demand for predetermined frequencies, normally extracted by the filter. In this study, we analyzed LFPs recorded from 13 patients (one female) with PD during stepping with bilateral deep brain electrodes implanted in the subthalamic nucleus (STN). We found that not only high-frequency oscillation (100-300 Hz) was modulated by β (13-30 Hz) but also β and γ amplitude were modulated by their low-frequency components in δ/θ/α and δ/θ/α/β bands. These PAC values were suppressed by sound stimulation, along with an improvement in gait. We also showed that gait-related high-β (Hβ) modulation in the STN was sensitive to auditory cues, and Hβ gait-phase modulation increased with a metronome. Meanwhile, phase-locking values (PLVs) across all frequencies were significantly suppressed around contralateral heel strikes, manifesting the contralateral step as a critical gait phase in gait initiation for PD. Only the PLVs around contralateral steps were sensitive to auditory cues. Our results support masking PAC as an effective method in exploring frequency nesting interactions in LFPs and reveal the linkages between sound stimulation and couplings related to gait phases in the STN. These findings raise the possibility that nesting interactions in the STN work as feasible biomarkers in alleviating gait disorders.

Brain oscillatory dysfunctions in dystonia

Dystonia is a hyperkinetic movement disorder associated with loss of inhibition, abnormal plasticity, dysfunctional sensorimotor integration, and brain oscillatory dysfunctions at cortical and subcortical levels of the central nervous system. Hence, dystonia is considered a network disorder that can, in many cases, be efficiently treated by pallidal deep brain stimulation (DBS). Abnormal oscillatory activity has been identified across the motor circuit of patients with dystonia. Increased low frequency (LF) synchronization in the internal pallidum is the most prominent abnormality. LF oscillations have been associated with the severity of dystonic motor symptoms; they are suppressed by DBS and localized to the clinically most effective stimulation site. Although the origin of these pathologic changes in brain activity needs further clarifications, their characterization will help in adjusting DBS parameters for successful clinical outcome.

Brain oscillations and Parkinson disease

Brain oscillations have been associated with Parkinson's disease (PD) for a long time mainly due to the fundamental oscillatory nature of parkinsonian rest tremor. Over the years, this association has been extended to frequencies well above that of tremor, largely owing to the opportunities offered by deep brain stimulation (DBS) to record electrical activity directly from the patients' basal ganglia. This chapter reviews the results of research on brain oscillations in PD focusing on theta (4-7Hz), beta (13-35Hz), gamma (70-80Hz) and high-frequency oscillations (200-400Hz). For each of these oscillations, we describe localization and interaction with brain structures and between frequencies, changes due to dopamine intake, task-related modulation, and clinical relevance. The study of brain oscillations will also help to dissect the mechanisms of action of DBS. Overall, the chapter tentatively depicts PD in terms of "oscillopathy."

Exploring the connections between basal ganglia and cortex revealed by transcranial magnetic stimulation, evoked potential and deep brain stimulation in dystonia

We review the findings for motor cortical excitability, plasticity and evoked potentials in dystonia. Plasticity can be induced and assessed in cortical areas by non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and the invasive technique of deep brain stimulation (DBS), which allows access to deep brain structures. Single-pulse TMS measures have been widely studied in dystonia and consistently showed reduced silent period duration. Paired pulse TMS measures showed reduced short and long interval intracortical inhibition, interhemispheric inhibition, long-latency afferent inhibition and increased intracortical facilitation in dystonia. Repetitive transcranial magnetic stimulation (rTMS) of the premotor cortex improved handwriting with prolongation of the silent period in focal hand dystonia patients. Continuous theta-burst stimulation (cTBS) of the cerebellum or cTBS of the dorsal premotor cortex improved dystonia in some studies. Plasticity induction protocols in dystonia demonstrated excessive motor cortical plasticity with the reduction in cortico-motor topographic specificity. Bilateral DBS of the globus pallidus internus (GPi) improves dystonia, associated pain and functional disability. Local field potentials recordings in dystonia patients suggested that there is increased power in the low-frequency band (4-12 Hz) in the GPi. Cortical evoked potentials at peak latencies of 10 and 25 ms can be recorded with GPi stimulation in dystonia. Plasticity induction protocols based on the principles of spike timing dependent plasticity that involved repeated pairing of GPi-DBS and motor cortical TMS at latencies of cortical evoked potentials induced motor cortical plasticity. These studies expanded our knowledge of the pathophysiology of dystonia and how cortical excitability and plasticity are altered with different treatments such as DBS.

Gamma Oscillations and Coherence Are Weaker in the Dorsomedial Subregion of STN in Parkinson's Disease

Background: Deep-brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for motor symptoms of advanced Parkinson's disease (PD). Due to a lack of detailed somatotopic organization in STN, the clinically most effective part of the STN for stimulation has already become one of the hot research focuses. At present, there are some reports about topographic distribution for different depths within the STN, but few about a mediolateral topography in this area.

Objective: The objective was to investigate the local field potential (LFP) distribution patterns in dorsomedial and dorsolateral subparts of STN.

Methods: In total, 18 PD patients eventually enrolled in this study. The DBS electrodes were initially located on the lateral portion of dorsolateral STN. Because of internal capsule side effects presented at low threshold (below 1.5 mA), the electrode was reimplanted more medially to the dorsomedial STN. In this process, intraoperative LFPs from dorsomedial and dorsolateral STN were recorded from the inserted electrode. Both beta power and gamma power of the LFPs were calculated using the power spectral density (PSD) for each DBS contact pair. Furthermore, coherence between any two pairs of contacts was computed in the dorsomedial and dorsolateral parts of STN, respectively. Meanwhile, the Unified Parkinson's Disease Rating Scale part III (UPDRS-III) was monitored prior to surgery and at the 6-month follow-up.

Results: Compared to the dorsolateral part of STN, gamma oscillations (p < 0.01) and coherence (p < 0.05) were all weaker in the dorsomedial part. However, no obvious differences in beta oscillations and coherence were observed between the two groups (p > 0.05). Moreover, it should be noted that DBS of the dorsomedial STN resulted in significant improvement in the UPDRS-III in PD patients. There was a 61.50 ± 21.30% improvement in UPDRS-III scores in Med-off/Stim-on state relative to the Med-off state at baseline (from 15.44 ± 6.84 to 43.94 ± 15.79, p < 0.01).

Conclusions: The specific features of gamma activity may be used to differentiate STN subregions. Moreover, the dorsomedial part of STN might be a potential target for DBS in PD.

Neurophysiological biomarkers to optimize deep brain stimulation in movement disorders

Intraoperative neurophysiological information could increase accuracy of surgical deep brain stimulation (DBS) lead placement. Subsequently, DBS therapy could be optimized by specifically targeting pathological activity. In Parkinson's disease, local field potentials (LFPs) excessively synchronized in the beta band (13-35 Hz) correlate with akinetic-rigid symptoms and their response to DBS therapy, particularly low beta band suppression (13-20 Hz) and high frequency gamma facilitation (35-250 Hz). In dystonia, LFPs abnormally synchronize in the theta/alpha (4-13 Hz), beta and gamma (60-90 Hz) bands. Phasic dystonic symptoms and their response to DBS correlate with changes in theta/alpha synchronization. In essential tremor, LFPs excessively synchronize in the theta/alpha and beta bands. Adaptive DBS systems will individualize pathological characteristics of neurophysiological signals to automatically deliver therapeutic DBS pulses of specific spatial and temporal parameters.

Embedded adaptive deep brain stimulation for cervical dystonia controlled by motor cortex theta oscillations

Dystonia is a disabling movement disorder characterized by excessive muscle contraction for which the underlying pathophysiology is incompletely understood and treatment interventions limited in efficacy. Here we utilize a novel, sensing-enabled, deep brain stimulator device, implanted in a patient with cervical dystonia, to record local field potentials from chronically implanted electrodes in the sensorimotor cortex and subthalamic nuclei bilaterally. This rechargeable device was able to record large volumes of neural data at home, in the naturalistic environment, during unconstrained activity. We confirmed the presence of theta (3-7 Hz) oscillatory activity, which was coherent throughout the cortico-subthalamic circuit and specifically suppressed by high-frequency stimulation. Stimulation also reduced the duration, rate and height of theta bursts. These findings motivated a proof-of-principle trial of a new form of adaptive deep brain stimulation - triggered by theta-burst activity recorded from the motor cortex. This facilitated increased peak stimulation amplitudes without induction of dyskinesias and demonstrated improved blinded clinical ratings compared to continuous DBS, despite reduced total electrical energy delivered. These results further strengthen the pathophysiological role of low frequency (theta) oscillations in dystonia and demonstrate the potential for novel adaptive stimulation strategies linked to cortico-basal theta bursts.

Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients

Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.

Oscillatory activity in the BNST/ALIC and the frontal cortex in OCD: acute effects of DBS

Deep brain stimulation (DBS) of the bed nucleus of the stria terminalis/anterior limb of the internal capsule (BNST/ALIC) is successfully used for treatment of patients with obsessive-compulsive disorder (OCD). Clinical and experimental studies have suggested that enhanced network synchronization in the theta band is correlated with severity of symptoms. The mechanisms of action of DBS remain unclear in OCD. We here investigate the effect of acute stimulation of the BNCT/ALIC on oscillatory neuronal activity in patients with OCD implanted with DBS electrodes. We recorded the oscillatory activity of local field potentials (LFPs) from DBS electrodes (contact + 0/- 3; bipolar configuration; both hemispheres) from the BNST/ALIC parallel with frontal cortical electroencephalogram (EEG) one day after DBS surgery in four patients with OCD. BNST/ALIC and frontal EEG oscillatory activities were analysed before stimulation as baseline, and after three periods of stimulation with different voltage amplitudes (1 V, 2 V and 3.5 V) at 130 Hz. Overall, acute high frequency DBS reduced oscillatory theta band (4-8 Hz; p < 0.01) but increased other frequency bands in BNST/ALIC and the frontal cortex (p < 0.01). We show that stimulation of the BNST/ALIC in OCD modulates oscillatory activity in brain regions that are involved in the pathomechanisms of OCD. Our findings confirm and extend the findings that enhanced theta oscillatory activity in neuronal networks may be a biomarker for OCD.

Deep Brain Stimulation Initiative: Toward Innovative Technology, New Disease Indications, and Approaches to Current and Future Clinical Challenges in Neuromodulation Therapy

Deep brain stimulation (DBS) is one of the most important clinical therapies for neurological disorders. DBS also has great potential to become a great tool for clinical neuroscience research. Recently, the National Engineering Laboratory for Neuromodulation at Tsinghua University held an international Deep Brain Stimulation Initiative workshop to discuss the cutting-edge technological achievements and clinical applications of DBS. We specifically addressed new clinical approaches and challenges in DBS for movement disorders (Parkinson's disease and dystonia), clinical application toward neurorehabilitation for stroke, and the progress and challenges toward DBS for neuropsychiatric disorders. This review highlighted key developments in (1) neuroimaging, with advancements in 3-Tesla magnetic resonance imaging DBS compatibility for exploration of brain network mechanisms; (2) novel DBS recording capabilities for uncovering disease pathophysiology; and (3) overcoming global healthcare burdens with online-based DBS programming technology for connecting patient communities. The successful event marks a milestone for global collaborative opportunities in clinical development of neuromodulation to treat major neurological disorders.

Simultaneous cortical and subcortical recordings in humans with movement disorders: Acute and chronic paradigms

Invasive basal ganglia recordings in humans have significantly advanced our understanding of the neurophysiology of movement disorders. A recent technical advance has been the addition of electrocorticography to basal ganglia recording, for evaluating distributed motor networks. Here we review the rationale, results, and ethics of this multisite recording technique in movement disorders, as well as its application in chronic recording paradigms utilizing implantable neural interfaces that include a sensing function.

Neurophysiological insights in dystonia and its response to deep brain stimulation treatment

Dystonia is a movement disorder characterised by involuntary muscle contractions resulting in abnormal movements, postures and tremor. The pathophysiology of dystonia is not fully understood but loss of neuronal inhibition, excessive sensorimotor plasticity and defective sensory processing are thought to contribute to network dysfunction underlying the disorder. Neurophysiology studies have been important in furthering our understanding of dystonia and have provided insights into the mechanism of effective dystonia treatment with pallidal deep brain stimulation. In this article we review neurophysiology studies in dystonia and its treatment with Deep Brain Stimulation, including Transcranial magnetic stimulation studies, studies of reflexes and sensory processing, and oscillatory activity recordings including local field potentials, micro-recordings, EEG and evoked potentials.

Subthalamic Single Cell and Oscillatory Neural Dynamics of a Dyskinetic Medicated Patient With Parkinson's Disease

Single cell neuronal activity (SUA) and local field potentials (LFP) in the subthalamic nucleus (STN) of unmedicated Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery have been well-characterized during microelectrode recordings (MER). However, there is limited knowledge about the changes in the firing patterns and oscillations above and within the territories of STN after the intake of dopaminergic medication. Here, for the first time, we report the STN single cell and oscillatory neural dynamics in a medicated patient with idiopathic PD using intraoperative MER. We recorded LFP and SUA with microelectrodes at various depths during bilateral STN-DBS electrode implantation. We isolated 26 neurons in total and observed that tonic and irregular firing patterns of individual neurons predominated throughout the territories of STN. While burst-type firings have been well-characterized in the dorsal territories of STN in unmedicated patients, interestingly, this activity was not observed in our medicated subject. LFP recordings lacked the excessive beta (8-30 Hz) activity, characteristic of the unmedicated state and signal energy was mainly dominated by slow oscillations below 8 Hz. We observed sharp gamma oscillations between 70 and 90 Hz within and above the STN. Despite the presence of a broadband high frequency activity in 200-400 Hz range, no cross-frequency interaction in the form of phase-amplitude coupling was noted between low and high frequency oscillations of LFPs. While our results are in agreement with the previously reported LFP recordings from the DBS lead in medicated PD patients, the sharp gamma peak present throughout the depth recordings and the lack of bursting firings after levodopa intake have not been reported before. The lack of bursting in SUA, the lack of excessive beta activity and cross frequency coupling between HFOs and lower rhythms further validate the link between bursting firing regime of neurons and pathological oscillatory neural activity in PD-STN. Overall, these observations not only validate the existing literature on the PD electrophysiology in healthy/medicated animal models but also provide insights regarding the underlying electro-pathophysiology of levodopa-induced dyskinesias in PD patients through demonstration of multiscale relationships between single cell firings and field potentials.

Characteristics of globus pallidus internus local field potentials in generalized dystonia patients with TWNK mutation

OBJECTIVE

We focused on a rare gene mutation causing dystonia in two siblings who received globus pallidus internus deep brain stimulation (GPi-DBS). The aim was to characterize the relationship between neuronal activity patterns and clinical syndromes.

METHODS

Whole exome sequencing was applied to identify the TWNK (previous symbol C10orf2) mutation; Two siblings with TWNK mutation presented as generalized dystonia with rigidity and bradykinesia; four other sporadic generalized dystonia patients underwent GPi-DBS and local field potentials (LFPs) were recorded. Oscillatory activities were illustrated with power spectra and temporal dynamics measured by the Lempel-Ziv complexity (LZC).

RESULTS

Normalized power spectra of GPi LFPs differed between patients with TWNK mutation and dystonia over the low beta bands. Patients with TWNK mutation had higher low beta power (15-27 Hz, unpaired t-test, corrected P < 0.0022) and lower LZC (15-27 Hz, unpaired t-test, P < 0.01) than other patients with generalized dystonia. On the other hand, the TWNK mutation patients showed decreased low frequency and beta oscillation in the GPi after DBS, as well as improved movement performance.

CONCLUSION

The LFPs were different in TWNK mutation dystonia siblings than other patients with generalized dystonia, which indicate the abnormal LFPs were related to symptoms rather than specific disease. In addition, the inhibited effect on oscillations also provided a potential evidence for DBS treatment on rare movement disorders.

SIGNIFICANCE

This study could potentially aid in the future development of adaptive DBS via rare disease LFPs comparison.

Debugging Adaptive Deep Brain Stimulation for Parkinson's Disease

Deep brain stimulation (DBS) is a successful treatment for patients with Parkinson's disease. In adaptive DBS, stimulation is titrated according to feedback about clinical state and underlying pathophysiology. This contrasts with conventional stimulation, which is fixed and continuous. In acute trials, adaptive stimulation matches the efficacy of conventional stimulation while delivering about half the electrical energy. The latter means potentially fewer side-effects. The next step is to determine the long-term efficacy, efficiency, and side-effect profile of adaptive stimulation, and chronic trials are currently being considered by the medical devices industry. However, there are several different approaches to adaptive DBS, and several possible limitations have been highlighted. Here we review the findings to date to ascertain how and who to stimulate in chronic trials designed to establish the long-term utility of adaptive DBS. © 2020 International Parkinson and Movement Disorder Society.

Toward adaptive deep brain stimulation for dystonia

The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson's disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.

The Functional Role of Thalamocortical Coupling in the Human Motor Network

The amplitude of high broadband activity in human cortical field potentials indicates local processing and has repeatedly been shown to reflect motor control in the primary motor cortex. In a group of male and female subjects affected by essential tremor and undergoing deep brain stimulation surgery, ventral intermediate nucleus low-frequency oscillations (<30 Hz) entrain the corticomotor high broadband activity (>40 Hz) during rest, relinquishing that role during movement execution. This finding suggests that there is significant cross-rhythm communication between thalamocortical regions, and motor behavior corresponds to changes in thalamocortical phase-amplitude coupling profiles. Herein, we demonstrate that thalamocortical coupling is a crucial mechanism for gating motor behavior.SIGNIFICANCE STATEMENT We demonstrate, for the first time, how thalamocortical coupling is mediating movement execution in humans. We show how the low-frequency oscillation from the ventral intermediate nucleus, known as the motor nucleus of the thalamus, entrains the excitability of the primary motor cortex, as reflected by the phase-amplitude coupling between the two regions. We show that thalamocortical phase-amplitude coupling is a manifestation of a gating mechanism for movement execution mediated by the thalamus. These findings highlight the importance of incorporating cross-frequency relationship in models of motor behavior; and given the spatial specificity of this mechanism, this work could be used to improve functional targeting during surgical implantations in subcortical regions.

Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions

Cortico-basal ganglia circuits are thought to play a crucial role in the selection and control of motor behaviors and have also been implicated in the processing of motivational content and in higher cognitive functions. During the last two decades, electrophysiological recordings in basal ganglia circuits have shown that several disease conditions are associated with specific changes in the temporal patterns of neuronal activity. In particular, synchronized oscillations have been a frequent finding suggesting that excessive synchronization of neuronal activity may be a pathophysiological mechanism involved in a wide range of neurologic and psychiatric conditions. We here review the experimental support for this hypothesis primarily in relation to Parkinson’s disease but also in relation to dystonia, essential tremor, epilepsy, and psychosis/schizophrenia.

Changing views of the pathophysiology of Parkinsonism

Studies of the pathophysiology of parkinsonism (specifically akinesia and bradykinesia) have a long history and primarily model the consequences of dopamine loss in the basal ganglia on the function of the basal ganglia/thalamocortical circuit(s). Changes of firing rates of individual nodes within these circuits were originally considered central to parkinsonism. However, this view has now given way to the belief that changes in firing patterns within the basal ganglia and related nuclei are more important, including the emergence of burst discharges, greater synchrony of firing between neighboring neurons, oscillatory activity patterns, and the excessive coupling of oscillatory activities at different frequencies. Primarily focusing on studies obtained in nonhuman primates and human patients with Parkinson's disease, this review summarizes the current state of this field and highlights several emerging areas of research, including studies of the impact of the heterogeneity of external pallidal neurons on parkinsonism, the importance of extrastriatal dopamine loss, parkinsonism-associated synaptic and morphologic plasticity, and the potential role(s) of the cerebellum and brainstem in the motor dysfunction of Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Cortico-subthalamic Coherence in a Patient With Dystonia Induced by Chorea-Acanthocytosis: A Case Report

The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) treatment in Parkinson's disease (PD) but much less frequently targeted for other disorders. Here we report the results of simultaneous local field potential (LFP) recordings and magnetoencephalography (MEG) in a single patient who was implanted bilaterally in the STN for the treatment of dystonia induced by chorea-acanthocytosis. Consistent with the previous results in PD, the dystonia patient showed significant subthalamo-cortical coherence in the high beta band (28-35 Hz) on both sides localized to the mesial sensorimotor areas. In addition, on the right side, significant coherence was found in the theta-alpha band (4-12 Hz) that localized to the medial prefrontal cortex with the peak in the anterior cingulate gyrus. Comparison of STN power spectra with a previously reported PD cohort showed increased power in the theta and alpha bands and decreased power in the low beta band in dystonia which is consistent with most of the previous studies. The present report extends the range of disorders for which cortico-subthalamic oscillatory connectivity has been characterized. Our results strengthen the evidence that at least some of the subthalamo-cortical oscillatory coherent networks are a feature of the healthy brain, although we do not rule out that coherence magnitude could be affected by disease.

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.