Modulations in oscillatory frequency and coupling in globus pallidus with increasing parkinsonian severity

Circuit-Specific Deep Brain Stimulation Provides Insights into Movement Control

Deep brain stimulation (DBS), a method in which electrical stimulation is delivered to specific areas of the brain, is an effective treatment for managing symptoms of a number of neurological and neuropsychiatric disorders. Clinical access to neural circuits during DBS provides an opportunity to study the functional link between neural circuits and behavior. This review discusses how the use of DBS in Parkinson's disease and dystonia has provided insights into the brain networks and physiological mechanisms that underlie motor control. In parallel, insights from basic science about how patterns of electrical stimulation impact plasticity and communication within neural circuits are transforming DBS from a therapy for treating symptoms to a therapy for treating circuits, with the goal of training the brain out of its diseased state.

The Role of Cerebellum and Basal Ganglia Functional Connectivity in Altered Voluntary Movement Execution in Essential Tremor

Substantial evidence highlights the role of the cerebellum in the pathophysiology of tremor in essential tremor (ET), although its potential involvement in altered movement execution in this condition remains unclear. This study aims to explore potential correlations between the cerebellum and basal ganglia functional connectivity and voluntary movement execution abnormalities in ET, objectively assessed with kinematic techniques. A total of 20 patients diagnosed with ET and 18 healthy subjects were enrolled in this study. Tremor and repetitive finger tapping were recorded using an optoelectronic kinematic system. All participants underwent comprehensive 3T-MRI examinations, including 3D-T1 and blood-oxygen-level dependent (BOLD) sequences during resting state. Morphometric analysis was conducted on the 3D-T1 images, while a seed-based analysis was performed to investigate the resting-state functional connectivity (rsFC) of dorsal and ventral portions of the dentate nucleus and the external and internal segments of the globus pallidus. Finally, potential correlations between rsFC alterations in patients and clinical as well as kinematic scores were assessed. Finger tapping movements were slower in ET than in healthy subjects. Compared to healthy subjects, patients with ET exhibited altered FC of both dentate and globus pallidus with cerebellar, basal ganglia, and cortical areas. Interestingly, both dentate and pallidal FC exhibited positive correlations with movement velocity in patients, differently from that we observed in healthy subjects, indicating the higher the FC, the faster the finger tapping. The findings of this study indicate the possible role of both cerebellum and basal ganglia in the pathophysiology of altered voluntary movement execution in patients with ET.

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.

Local field potential (LFP) power and phase-amplitude coupling (PAC) changes in the striatum and motor cortex reflect neural mechanisms associated with bradykinesia and rigidity during D2R suppression in an animal model

Impairments in motor control are the primary feature of Parkinson's disease, which is caused by dopaminergic imbalance in the basal ganglia. Identification of neural biomarkers of dopamine D2 receptor (D2R) suppression would be useful for monitoring the progress of neuropathologies and effects of treatment. Male Swiss albino ICR mice were deeply anesthetized, and electrodes were implanted in the striatum and motor cortex to record local field potential (LFP). Haloperidol (HAL), a D2R antagonist, was administered to induce decreased D2R activity. Following HAL treatment, the mice showed significantly decreased movement velocity in open field test, increased latency to descend in a bar test, and decreased latency to fall in a rotarod test. LFP signals during HAL-induced immobility (open field test) and catalepsy (bar test) were analyzed. Striatal low-gamma (30.3-44.9 Hz) power decreased during immobility periods, but during catalepsy, delta power (1-4 Hz) increased, beta1(13.6-18 Hz) and low-gamma powers decreased, and high-gamma (60.5-95.7 Hz) power increased. Striatal delta-high-gamma phase-amplitude coupling (PAC) was significantly increased during catalepsy but not immobility. In the motor cortex, during HAL-induced immobility, beta1 power significantly increased and low-gamma power decreased, but during HAL-induced catalepsy, low-gamma and beta1 powers decreased and high-gamma power increased. Delta-high-gamma PAC in the motor cortex significantly increased during catalepsy but not during immobility. Altogether, the present study demonstrated changes in delta, beta1 and gamma powers and delta-high-gamma PAC in the striatum and motor cortex in association with D2R suppression. In particular, delta power in the striatum and delta-high-gamma PAC in the striatum and motor cortex appear to represent biomarkers of neural mechanisms associated with bradykinesia and rigidity.

Monitoring time domain characteristics of Parkinson's disease using 3D memristive neuromorphic system

Introduction

Parkinson's disease (PD) is a neurodegenerative disorder affecting millions of patients. Closed-Loop Deep Brain Stimulation (CL-DBS) is a therapy that can alleviate the symptoms of PD. The CL-DBS system consists of an electrode sending electrical stimulation signals to a specific region of the brain and a battery-powered stimulator implanted in the chest. The electrical stimuli in CL-DBS systems need to be adjusted in real-time in accordance with the state of PD symptoms. Therefore, fast and precise monitoring of PD symptoms is a critical function for CL-DBS systems. However, the current CL-DBS techniques suffer from high computational demands for real-time PD symptom monitoring, which are not feasible for implanted and wearable medical devices.

Methods

In this paper, we present an energy-efficient neuromorphic PD symptom detector using memristive three-dimensional integrated circuits (3D-ICs). The excessive oscillation at beta frequencies (13-35 Hz) at the subthalamic nucleus (STN) is used as a biomarker of PD symptoms.

Results

Simulation results demonstrate that our neuromorphic PD detector, implemented with an 8-layer spiking Long Short-Term Memory (S-LSTM), excels in recognizing PD symptoms, achieving a training accuracy of 99.74% and a validation accuracy of 99.52% for a 75%-25% data split. Furthermore, we evaluated the improvement of our neuromorphic CL-DBS detector using NeuroSIM. The chip area, latency, energy, and power consumption of our CL-DBS detector were reduced by 47.4%, 66.63%, 65.6%, and 67.5%, respectively, for monolithic 3D-ICs. Similarly, for heterogeneous 3D-ICs, employing memristive synapses to replace traditional Static Random Access Memory (SRAM) resulted in reductions of 44.8%, 64.75%, 65.28%, and 67.7% in chip area, latency, and power usage.

Discussion

This study introduces a novel approach for PD symptom evaluation by directly utilizing spiking signals from neural activities in the time domain. This method significantly reduces the time and energy required for signal conversion compared to traditional frequency domain approaches. The study pioneers the use of neuromorphic computing and memristors in designing CL-DBS systems, surpassing SRAM-based designs in chip design area, latency, and energy efficiency. Lastly, the proposed neuromorphic PD detector demonstrates high resilience to timing variations in brain neural signals, as confirmed by robustness analysis.

Effect of subthalamic coordinated reset deep brain stimulation on Parkinsonian gait

Introduction

Coordinated Reset Deep Brain Stimulation (CR DBS) is a novel DBS approach for treating Parkinson's disease (PD) that uses lower levels of burst stimulation through multiple contacts of the DBS lead. Though CR DBS has been demonstrated to have sustained therapeutic effects on rigidity, tremor, bradykinesia, and akinesia following cessation of stimulation, i.e., carryover effect, its effect on Parkinsonian gait has not been well studied. Impaired gait is a disabling symptom of PD, often associated with a higher risk of falling and a reduced quality of life. The goal of this study was to explore the carryover effect of subthalamic CR DBS on Parkinsonian gait.

Methods

Three non-human primates (NHPs) were rendered Parkinsonian and implanted with a DBS lead in the subthalamic nucleus (STN). For each animal, STN CR DBS was delivered for several hours per day across five consecutive days. A clinical rating scale modified for NHP use (mUPDRS) was administered every morning to monitor the carryover effect of CR DBS on rigidity, tremor, akinesia, and bradykinesia. Gait was assessed quantitatively before and after STN CR DBS. The stride length and swing speed were calculated and compared to the baseline, pre-stimulation condition.

Results

In all three animals, carryover improvements in rigidity, bradykinesia, and akinesia were observed after CR DBS. Increased swing speed was observed in all the animals; however, improvement in stride length was only observed in NHP B2. In addition, STN CR DBS using two different burst frequencies was evaluated in NHP B2, and differential effects on the mUPDRS score and gait were observed.

Discussion

Although preliminary, our results indicate that STN CR DBS can improve Parkinsonian gait together with other motor signs when stimulation parameters are properly selected. This study further supports the continued development of CR DBS as a novel therapy for PD and highlights the importance of parameter selection in its clinical application.

Profiling the low-beta characteristics of the subthalamic nucleus in early- and late-onset Parkinson's disease

Objectives

Low-beta oscillation (13-20 Hz) has rarely been studied in patients with early-onset Parkinson's disease (EOPD, age of onset ≤50 years). We aimed to explore the characteristics of low-beta oscillation in the subthalamic nucleus (STN) of patients with EOPD and investigate the differences between EOPD and late-onset Parkinson's disease (LOPD).

Methods

We enrolled 31 EOPD and 31 LOPD patients, who were matched using propensity score matching. Patients underwent bilateral STN deep brain stimulation (DBS). Local field potentials were recorded using intraoperative microelectrode recording. We analyzed the low-beta band parameters, including aperiodic/periodic components, beta burst, and phase-amplitude coupling. We compared low-beta band activity between EOPD and LOPD. Correlation analyses were performed between the low-beta parameters and clinical assessment results for each group.

Results

We found that the EOPD group had lower aperiodic parameters, including offset (p = 0.010) and exponent (p = 0.047). Low-beta burst analysis showed that EOPD patients had significantly higher average burst amplitude (p = 0.016) and longer average burst duration (p = 0.011). Furthermore, EOPD had higher proportion of long burst (500-650 ms, p = 0.008), while LOPD had higher proportion of short burst (200-350 ms, p = 0.007). There was a significant difference in phase-amplitude coupling values between low-beta phase and fast high frequency oscillation (300-460 Hz) amplitude (p = 0.019).

Conclusion

We found that low-beta activity in the STN of patients with EOPD had characteristics that varied when compared with LOPD, and provided electrophysiological evidence for different pathological mechanisms between the two types of PD. These differences need to be considered when applying adaptive DBS on patients of different ages.

Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson’s disease

The prodromal phase of Parkinson’s disease is characterized by aggregation of the misfolded pathogenic protein α-synuclein in select neural centres, co-occurring with non-motor symptoms including sensory and cognitive loss, and emotional disturbances. It is unclear whether neuronal loss is significant during the prodrome. Underlying these symptoms are synaptic impairments and aberrant neural network activity. However, the relationships between synaptic defects and network-level perturbations are not established. In experimental models, pathological α-synuclein not only impacts neurotransmission at the synaptic level, but also leads to changes in brain network-level oscillatory dynamics—both of which likely contribute to non-motor deficits observed in Parkinson’s disease. Here we draw upon research from both human subjects and experimental models to propose a ‘synapse to network prodrome cascade’ wherein before overt cell death, pathological α-synuclein induces synaptic loss and contributes to aberrant network activity, which then gives rise to prodromal symptomology. As the disease progresses, abnormal patterns of neural activity ultimately lead to neuronal loss and clinical progression of disease. Finally, we outline goals and research needed to unravel the basis of functional impairments in Parkinson’s disease and other α-synucleinopathies.

A translational perspective on pathophysiological changes of oscillatory activity in dystonia and parkinsonism

Intracerebral recordings from movement disorders patients undergoing deep brain stimulation have allowed the identification of pathophysiological patterns in oscillatory activity that correlate with symptom severity. Changes in oscillatory synchrony occur within and across brain areas, matching the classification of movement disorders as network disorders. However, the underlying mechanisms of oscillatory changes are difficult to assess in patients, as experimental interventions are technically limited and ethically problematic. This is why animal models play an important role in neurophysiological research of movement disorders. In this review, we highlight the contributions of translational research to the mechanistic understanding of pathological changes in oscillatory activity, with a focus on parkinsonism and dystonia, while addressing the limitations of current findings and proposing possible future directions.

Cross-frequency phase-amplitude coupling in repetitive movements in patients with Parkinson's disease

Bradykinesia is a cardinal motor symptom in Parkinson’s disease (PD), the pathophysiology of which is not fully understood. We analyzed the role of cross-frequency coupling of oscillatory cortical activity in motor impairment in patients with PD and healthy controls. High-density EEG signals were recorded during various motor activities and at rest. Patients performed a repetitive finger-pressing task normally, but were slower than controls during tapping. Phase-amplitude coupling (PAC) between β (13–30 Hz) and broadband γ (50–150 Hz) was computed from individual EEG source signals in the premotor, primary motor, and primary somatosensory cortices, and the primary somatosensory complex. In all four regions, averaging the entire movement period resulted in higher PAC in patients than in controls for the resting condition and the pressing task (similar performance between groups). However, this was not the case for the tapping tasks where patients performed slower. This suggests the strength of state-related β-γ PAC does not determine Parkinsonian bradykinesia. Examination of the dynamics of oscillatory EEG signals during motor transitions revealed a distinctive motif of PAC rise and decay around press onset. This pattern was also present at press offset and slow tapping onset, linking such idiosyncratic PAC changes to transitions between different movement states. The transition-related PAC modulation in patients was similar to controls in the pressing task but flattened during slow tapping, which related to normal and abnormal performance, respectively. These findings suggest that the dysfunctional evolution of neuronal population dynamics during movement execution is an important component of the pathophysiology of Parkinsonian bradykinesia.

NEW & NOTEWORTHY Our findings using noninvasive EEG recordings provide evidence that PAC dynamics might play a role in the physiological cortical control of movement execution and may encode transitions between movement states. Results in patients with Parkinson’s disease suggest that bradykinesia is related to a deficit of the dynamic regulation of PAC during movement execution rather than its absolute strength. Our findings may contribute to the development of a new concept of the pathophysiology of bradykinesia.

Novel approaches for quantifying beta synchrony in Parkinson's disease

Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30 Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50 Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.

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."

Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations

Βeta oscillatory activity (human: 13-35 Hz; primate: 8-24 Hz) is pervasive within the cortex and basal ganglia. Studies in Parkinson's disease patients and animal models suggest that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine tone remains unclear. We recorded neural activity in the cortex and basal ganglia of healthy non-human primates while acutely and chronically up- and down-modulating dopamine levels. We assessed changes in beta oscillations in patients with Parkinson's following acute and chronic changes in dopamine tone. Here we show beta oscillation frequency is strongly coupled with dopamine tone in both monkeys and humans. Power, coherence between single-units and local field potentials (LFP), spike-LFP phase-locking, and phase-amplitude coupling are not systematically regulated by dopamine levels. These results demonstrate that beta frequency is a key property of pathological oscillations in cortical and basal ganglia networks.

Revisiting the "Paradox of Stereotaxic Surgery": Insights Into Basal Ganglia-Thalamic Interactions

Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard "rate models" of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This "paradox of stereotaxic surgery" was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation.

New Frontiers for Deep Brain Stimulation: Directionality, Sensing Technologies, Remote Programming, Robotic Stereotactic Assistance, Asleep Procedures, and Connectomics

Over the last few years, while expanding its clinical indications from movement disorders to epilepsy and psychiatry, the field of deep brain stimulation (DBS) has seen significant innovations. Hardware developments have introduced directional leads to stimulate specific brain targets and sensing electrodes to determine optimal settings via feedback from local field potentials. In addition, variable-frequency stimulation and asynchronous high-frequency pulse trains have introduced new programming paradigms to efficiently desynchronize pathological neural circuitry and regulate dysfunctional brain networks not responsive to conventional settings. Overall, these innovations have provided clinicians with more anatomically accurate programming and closed-looped feedback to identify optimal strategies for neuromodulation. Simultaneously, software developments have simplified programming algorithms, introduced platforms for DBS remote management via telemedicine, and tools for estimating the volume of tissue activated within and outside the DBS targets. Finally, the surgical accuracy has improved thanks to intraoperative magnetic resonance or computerized tomography guidance, network-based imaging for DBS planning and targeting, and robotic-assisted surgery for ultra-accurate, millimetric lead placement. These technological and imaging advances have collectively optimized DBS outcomes and allowed “asleep” DBS procedures. Still, the short- and long-term outcomes of different implantable devices, surgical techniques, and asleep vs. awake procedures remain to be clarified. This expert review summarizes and critically discusses these recent innovations and their potential impact on the DBS field.

Alpha and high gamma phase amplitude coupling during motor imagery and weighted cross-frequency coupling to extract discriminative cross-frequency patterns

Motor imagery modulates specific neural oscillations like actual movement does. Representatively, suppression of the alpha power (e.g., event-related desynchronization [ERD]) is the typical pattern of motor imagery in the motor cortex. However, in addition to this amplitude-based feature, the coupling across frequencies includes important information about the brain functions and the existence of such complex information has been reported in various invasive studies. Yet, the interaction across multiple frequencies during motor imagery processing is still unclear and has not been widely studied, particularly concerning the non-invasive signals. In this study, we provide empirical evidence of the comodulation between the phase of alpha rhythm and the amplitude of high gamma rhythm during the motor imagery process. We used electroencephalography (EEG) in our investigation during the imagination of left- or right-hand movement recorded from 52 healthy subjects, and quantified the ERD of alpha and phase-amplitude coupling (PAC) which is a relative change of modulation index to the base line period (before the cue). As a result, we found that the coupling between the phase of alpha (8-12 Hz) and the amplitude of high gamma (70-120 Hz) and this PAC decreases during motor imagery and then rebounds to the baseline like alpha ERD (r = 0.29 to 0.42). This correlation between PAC and ERD was particularly stronger in the ipsilateral area. In addition, trials that demonstrated higher alpha power during the ready period (before the cue) showed a larger ERD during motor imagery and similarly, trials with higher modulation index during the ready period yielded a greater decrease in PAC during imagery. In the classification analysis, we found that the effective phase frequency that showed better decoding accuracy in left and right-hand imagery, varied across subjects. Motivated by result, we proposed a weighted cross-frequency coupling (WCFC) method that extracts the maximal discriminative feature by combining band power and CFC. In the evaluation, WCFC with only two electrodes yielded a performance comparable to the conventional algorithm with 64 electrodes in classifying left and right-hand motor imagery. These results indicate that the phase-amplitude frequency plays an important role in motor imagery, and that optimizing this frequency ranges is crucial for extracting information features to decode the motor imagery types.

Longitudinal analysis of local field potentials recorded from directional deep brain stimulation lead implants in the subthalamic nucleus

Objective.The electrode-tissue interface surrounding a deep brain stimulation (DBS) lead is known to be highly dynamic following implantation, which may have implications on the interpretation of intraoperatively recorded local field potentials (LFPs). We characterized beta-band LFP dynamics following implantation of a directional DBS lead in the sensorimotor subthalamic nucleus (STN), which is a primary target for treating Parkinson's disease.Approach.Directional STN-DBS leads were implanted in four healthy, non-human primates. LFPs were recorded over two weeks and again 1-4 months after implantation. Impedance was measured for two weeks post-implant without stimulation to compare the reactive tissue response to changes in LFP oscillations. Beta-band (12-30 Hz) peak power was calculated from the LFP power spectra using both common average referencing (CAR) and intra-row bipolar referencing (IRBR).Results.Resting-state LFPs in two of four subjects revealed a steady increase of beta power over the initial two weeks post-implant whereas the other two subjects showed variable changes over time. Beta power variance across days was significantly larger in the first two weeks compared to 1-4 months post-implant in all three long-term subjects. Further, spatial maps of beta power several hours after implantation did not correlate with those measured two weeks or 1-4 months post-implant. CAR and IRBR beta power correlated across short- and long-term time points. However, depending on the time period, subjects showed a significant bias towards larger beta power using one referencing scheme over the other. Lastly, electrode-tissue impedance increased over the two weeks post-implant but showed no significant correlation to beta power.Significance.These results suggest that beta power in the STN may undergo significant changes following DBS lead implantation. DBS lead diameter and electrode recording configurations can affect the post-implant interpretation of oscillatory features. Such insights will be important for extrapolating results from intraoperative and externalized LFP recordings.

Spatiotemporal features of β-γ phase-amplitude coupling in Parkinson's disease derived from scalp EEG

Abnormal phase-amplitude coupling between β and broadband-γ activities has been identified in recordings from the cortex or scalp of patients with Parkinson's disease. While enhanced phase-amplitude coupling has been proposed as a biomarker of Parkinson's disease, the neuronal mechanisms underlying the abnormal coupling and its relationship to motor impairments in Parkinson's disease remain unclear. To address these issues, we performed an in-depth analysis of high-density EEG recordings at rest in 19 patients with Parkinson's disease and 20 age- and sex-matched healthy control subjects. EEG signals were projected onto the individual cortical surfaces using source reconstruction techniques and separated into spatiotemporal components using independent component analysis. Compared to healthy controls, phase-amplitude coupling of Parkinson's disease patients was enhanced in dorsolateral prefrontal cortex, premotor cortex, primary motor cortex and somatosensory cortex, the difference being statistically significant in the hemisphere contralateral to the clinically more affected side. β and γ signals involved in generating abnormal phase-amplitude coupling were not strictly phase-phase coupled, ruling out that phase-amplitude coupling merely reflects the abnormal activity of a single oscillator in a recurrent network. We found important differences for couplings between the β and γ signals from identical components as opposed to those from different components (originating from distinct spatial locations). While both couplings were abnormally enhanced in patients, only the latter were correlated with clinical motor severity as indexed by part III of the Movement Disorder Society Unified Parkinson's Disease Rating Scale. Correlations with parkinsonian motor symptoms of such inter-component couplings were found in premotor, primary motor and somatosensory cortex, but not in dorsolateral prefrontal cortex, suggesting motor domain specificity. The topography of phase-amplitude coupling demonstrated profound differences in patients compared to controls. These findings suggest, first, that enhanced phase-amplitude coupling in Parkinson's disease patients originates from the coupling between distinct neural networks in several brain regions involved in motor control. Because these regions included the somatosensory cortex, abnormal phase-amplitude coupling is not exclusively tied to the hyperdirect tract connecting cortical regions monosynaptically with the subthalamic nucleus. Second, only the coupling between β and γ signals from different components appears to have pathophysiological significance, suggesting that therapeutic approaches breaking the abnormal lateral coupling between neuronal circuits may be more promising than targeting phase-amplitude coupling per se.

Parkinsonism Alters Beta Burst Dynamics across the Basal Ganglia-Motor Cortical Network

Elevated synchronized oscillatory activity in the beta band has been hypothesized to be a pathophysiological marker of Parkinson's disease (PD). Recent studies have suggested that parkinsonism is closely associated with increased amplitude and duration of beta burst activity in the subthalamic nucleus (STN). How beta burst dynamics are altered from the normal to parkinsonian state across the basal ganglia-thalamocortical (BGTC) motor network, however, remains unclear. In this study, we simultaneously recorded local field potential activity from the STN, internal segment of the globus pallidus (GPi), and primary motor cortex (M1) in three female rhesus macaques, and characterized how beta burst activity changed as the animals transitioned from normal to progressively more severe parkinsonian states. Parkinsonism was associated with an increased incidence of beta bursts with longer duration and higher amplitude in the low beta band (8-20 Hz) in both the STN and GPi, but not in M1. We observed greater concurrence of beta burst activity, however, across all recording sites (M1, STN, and GPi) in PD. The simultaneous presence of low beta burst activity across multiple nodes of the BGTC network that increased with severity of PD motor signs provides compelling evidence in support of the hypothesis that low beta synchronized oscillations play a significant role in the underlying pathophysiology of PD. Given its immersion throughout the motor circuit, we hypothesize that this elevated beta-band activity interferes with spatial-temporal processing of information flow in the BGTC network that contributes to the impairment of motor function in PD.SIGNIFICANCE STATEMENT This study fills a knowledge gap regarding the change in temporal dynamics and coupling of beta burst activity across the basal ganglia-thalamocortical (BGTC) network during the evolution from normal to progressively more severe parkinsonian states. We observed that changes in beta oscillatory activity occur throughout BGTC and that increasing severity of parkinsonism was associated with a higher incidence of longer duration, higher amplitude low beta bursts in the basal ganglia, and increased concurrence of beta bursts across the subthalamic nucleus, globus pallidus, and motor cortex. These data provide new insights into the potential role of changes in the temporal dynamics of low beta activity within the BGTC network in the pathogenesis of Parkinson's disease.

Subthalamic beta oscillations correlate with dopaminergic degeneration in experimental parkinsonism

Excessive beta activity has been shown in local field potential recordings from the cortico-basal ganglia loop of Parkinson's disease patients and in its various animal models. Recent evidence suggests that enhanced beta oscillations may play a central role in the pathophysiology of the disorder and that beta activity may be directly linked to the motor impairment. However, the temporal evolution of exaggerated beta oscillations during the ongoing dopaminergic neurodegeneration and its relation to the motor impairment and histological changes are still unknown. We investigated motor behavioral, in-vivo electrophysiological (subthalamic nucleus, motor cortex) and histological changes (striatum, substantia nigra compacta) 2, 5, 10 and 20-30 days after a 6-hydroxydopamine injection into the medial forebrain bundle in Wistar rats. We found strong correlations between subthalamic beta power and motor impairment. No correlation was found for beta power in the primary motor cortex. Only subthalamic but not cortical beta power was strongly correlated with the histological markers of the dopaminergic neurodegeneration. Significantly increased subthalamic beta oscillations could be detected before this increase was found in primary motor cortex. At the latest observation time point, a significantly higher percentage of long beta bursts was found. Our study is the first to show a strong relation between subthalamic beta power and the dopaminergic neurodegeneration. Thus, we provide additional evidence for an important pathophysiological role of subthalamic beta oscillations and prolonged beta bursts in Parkinson's disease.

Neuromodulation effects of deep brain stimulation on beta rhythm: A longitudinal local field potential study

BACKGROUND

Deep brain stimulation (DBS) holds great promise in treating various brain diseases but its chronic therapeutic mechanisms are unclear.

OBJECTIVE

To explore the immediate and chronic effects of DBS on brain oscillations, and understand how different sub-bands of oscillations may be related to symptom improvement in Parkinson's patients.

METHODS

We carried out a longitudinal study to examine the effects of DBS on local field potentials recorded by sensing-enabled neurostimulators in the subthalamic nuclei of Parkinson's patients, using a novel block-design stimulation paradigm.

RESULTS

DBS significantly suppressed beta activity (13-35Hz) but the suppression effect appeared to gradually attenuate during a 6-month follow-up period after surgery (p = 0.002). However, beta suppression did not attenuate after repeated stimulation over several minutes (p > 0.110), suggesting that the changes in beta suppression may reflect a slow reconfiguration of neural pathways instead of habituation. Suppression of beta was also associated with clinical symptom improvement across subjects. Importantly, symptom-relevant features fell within the high beta band at month 1 but shifted to the low beta band at month 6, indicating that the high beta and the low beta oscillations may play different functional roles and respond differently to stimulation over the long-term treatment.

CONCLUSION

These data may advance understanding of chronic DBS effects on beta oscillations and their association with clinical improvement, offering novel insights to the therapeutic mechanisms of DBS.

Lateralized Connectivity between Globus Pallidus and Motor Cortex is Associated with Freezing of Gait in Parkinson's Disease

Freezing of gait (FoG) is a brief, episodic absence or marked reduction of forward progression of the feet, despite the intention to walk, that is common in people with Parkinson's disease (PD). We hypothesized that not only motor, but higher level cognitive and attention areas may be impaired in freezers. In this study, we aimed to characterize differences in cortical and subcortical functional connectivity specific to FoG. We examined resting state neuroimaging and objective measures of FoG severity and gait from 103 individuals (28 PD + FoG, 36 PD - FoG and 39 healthy controls). Inertial sensors were used to quantify freezing severity and gait. Groups with and without FoG were matched on age, disease severity, cognitive status, and levodopa medication. MRI data was processed using surface-based registration. High-quality imaging data were used to characterize differences in connectivity specific to FoG using a pre-defined set of Regions of Interest (ROIs) and validated using whole-brain connectivity analysis. Associations between functional connectivity and objective measures of FoG were determined via predictive modeling using hold-out cross validation. We found that connectivity between the left globus pallidus (GP) and left somatosensory cortex and between two brain areas in the default and insular/vestibular networks exhibited significant differences specific to FoG and were also strong and significant predictors of FoG severity. Our findings suggest that the interplay among motor, default and vestibular areas of the left cortex are critical in the pathology of FoG.

Delta oscillations are a robust biomarker of dopamine depletion severity and motor dysfunction in awake mice

Delta oscillations (0.5-4 Hz) are a robust feature of basal ganglia pathophysiology in patients with Parkinson's disease (PD) in relationship to tremor, but their relationship to other parkinsonian symptoms has not been investigated. While delta oscillations have been observed in mouse models of PD, they have only been investigated in anesthetized animals, suggesting that the oscillations may be an anesthesia artifact and limiting the ability to relate them to motor symptoms. Here, we establish a novel approach to detect spike oscillations embedded in noise to provide the first study of delta oscillations in awake, dopamine-depleted mice. We find that approximately half of neurons in the substantia nigra pars reticulata (SNr) exhibit delta oscillations in dopamine depletion and that these oscillations are a strong indicator of dopamine loss and akinesia, outperforming measures such as changes in firing rate, irregularity, bursting, and synchrony. These oscillations are typically weakened, but not ablated, during movement. We further establish that these oscillations are caused by the loss of D2-receptor activation and do not originate from motor cortex, contrary to previous findings in anesthetized animals. Instead, SNr oscillations precede those in M1 at a 100- to 300-ms lag, and these neurons' relationship to M1 oscillations can be used as the basis for a novel classification of SNr into two subpopulations. These results give insight into how dopamine loss leads to motor dysfunction and suggest a reappraisal of delta oscillations as a marker of akinetic symptoms in PD.NEW & NOTEWORTHY This work introduces a novel method to detect spike oscillations amidst neural noise. Using this method, we demonstrate that delta oscillations in the basal ganglia are a defining feature of awake, dopamine-depleted mice and are strongly correlated with dopamine loss and parkinsonian motor symptoms. These oscillations arise from a loss of D2-receptor activation and do not require motor cortex. Similar oscillations in human patients may be an underappreciated marker and target for Parkinson's disease (PD) treatment.

Online Mapping With the Deep Brain Stimulation Lead: A Novel Targeting Tool in Parkinson's Disease

BACKGROUND

Beta-frequency oscillations (13-30 Hz) are a subthalamic hallmark in patients with Parkinson's disease, and there is increased interest in their utility as an intraoperative marker.

OBJECTIVES

The objectives of this study were to assess whether beta activity measured directly from macrocontacts of deep brain stimulation leads could be used (a) as an intraoperative electrophysiological approach for guiding lead placements and (b) for physiologically informed stimulation delivery.

METHODS

Every millimeter along the surgical trajectory, local field-potential data were collected from each macrocontact, and power spectral densities were calculated and visualized (n = 39 patients). This was done for online intraoperative functional mapping and post hoc statistical analyses using 2 methods: generating distributions of spectral activity along surgical trajectories and direct delineation (presence versus lack) of beta peaks. In a subset of patients, this approach was corroborated by microelectrode recordings. Furthermore, the match rate between beta peaks at the final target position and the clinically determined best stimulation site were assessed.

RESULTS

Subthalamic recording sites were delineated by both methods of reconstructing functional topographies of spectral activity along surgical trajectories at the group level (P < 0.0001). Beta peaks were detected when any portion of the 1.5 mm macrocontact was within the microelectrode-defined subthalamic border. The highest beta peak at the final implantation site corresponded to the site of active stimulation in 73.3% of hemispheres (P < 0.0001). In 93.3% of hemispheres, active stimulation corresponded to the first-highest or second-highest beta peak.

CONCLUSIONS

Online measures of beta activity with the deep brain stimulation macroelectrode can be used to inform surgical lead placement and contribute to optimization of stimulation programming procedures. © 2020 International Parkinson and Movement Disorder Society.

Frequency-Specific Optogenetic Deep Brain Stimulation of Subthalamic Nucleus Improves Parkinsonian Motor Behaviors

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy for the motor symptoms of Parkinson's disease (PD). However, the neural elements mediating symptom relief are unclear. A previous study concluded that direct optogenetic activation of STN neurons was neither necessary nor sufficient for relief of parkinsonian symptoms. However, the kinetics of the channelrhodopsin-2 (ChR2) used for cell-specific activation are too slow to follow the high rates required for effective DBS, and thus the contribution of activation of STN neurons to the therapeutic effects of DBS remains unclear. We quantified the behavioral and neuronal effects of optogenetic STN DBS in female rats following unilateral 6-hydroxydopamine (6-OHDA) lesion using an ultrafast opsin (Chronos). Optogenetic STN DBS at 130 pulses per second (pps) reduced pathologic circling and ameliorated deficits in forelimb stepping similarly to electrical DBS, while optogenetic STN DBS with ChR2 did not produce behavioral effects. As with electrical DBS, optogenetic STN DBS exhibited a strong dependence on stimulation rate; high rates produced symptom relief while low rates were ineffective. High-rate optogenetic DBS generated both increases and decreases in firing rates of single neurons in STN, globus pallidus externa (GPe), and substantia nigra pars reticular (SNr), and disrupted β band oscillatory activity in STN and SNr. High-rate optogenetic STN DBS can indeed ameliorate parkinsonian motor symptoms through reduction of abnormal oscillatory activity in the STN-associated neural circuit, and these results highlight that the kinetic properties of opsins have a strong influence on the effects of optogenetic stimulation.SIGNIFICANCE STATEMENT Whether STN local cells contribute to the therapeutic effects of subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) remains unclear. We re-examined the role of STN local cells in mediating the symptom-relieving effects of STN DBS using cell type-specific optogenetic stimulation with a much faster opsin, Chronos. Direct optogenetic stimulation of STN neurons was effective in treating the symptoms of parkinsonism in the 6-hydroxydopamine (6-OHDA) lesion rat. These results highlight that the kinetic properties of opsins can have a strong influence on the effects of optogenetic activation/inhibition and must be considered when employing optogenetic to study high-rate neural stimulation.

Basal ganglia oscillations as biomarkers for targeting circuit dysfunction in Parkinson's disease

Oscillations are a naturally occurring phenomenon in highly interconnected dynamical systems. However, it is thought that excessive synchronized oscillations in brain circuits can be detrimental for many brain functions by disrupting neuronal information processing. Because synchronized basal ganglia oscillations are a hallmark of Parkinson's disease (PD), it has been suggested that aberrant rhythmic activity associated with symptoms of the disease could be used as a physiological biomarker to guide pharmacological and electrical neuromodulatory interventions. We here briefly review the various manifestations of basal ganglia oscillations observed in human subjects and in animal models of PD. In this context, we also review the evidence supporting a pathophysiological role of different oscillations for the suppression of voluntary movements as well as for the induction of excessive motor activity. In light of these findings, it is discussed how oscillations could be used to guide a more precise targeting of dysfunctional circuits to obtain improved symptomatic treatment of PD.

Cortical Phase-Amplitude Coupling in a Progressive Model of Parkinsonism in Nonhuman Primates

Parkinson's disease is associated with abnormal oscillatory electrical activities of neurons and neuronal ensembles throughout the basal ganglia-thalamocortical network. It has recently been documented in patients with advanced parkinsonism that the amplitude of gamma-band oscillations (50-200 Hz) in electrocorticogram recordings from the primary motor cortex is abnormally coupled to the phase of beta band oscillations within the same signals. It is not known when in the course of the disease the abnormal phase-amplitude coupling (PAC) arises, and whether it is influenced by arousal or prior exposure to dopaminergic medications. To address these issues, we analyzed the relationship between the severity of parkinsonian motor signs and the extent of PAC in a progressive model of parkinsonism, using primates that were not exposed to levodopa prior to testing. PAC was measured in electrocorticogram signals from the primary motor cortex and the supplementary motor area in 3 monkeys that underwent weekly injections of small doses of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, rendering them progressively parkinsonian. We found that parkinsonism was associated with increased coupling between the phase of low-frequency (4-10 Hz) oscillations and the amplitude of oscillations in the high gamma band (50-150 Hz). These changes only reached significance when the animals became fully parkinsonian. The increased PAC was normalized after levodopa treatment. We also found a similar increase in PAC during sleep, even in normal animals. The identified PAC was independent of concomitant changes in spectral power in the 2.9-9.8Hz or 49.8-150.4 Hz ranges. We conclude that PAC is predominately a sign of advanced parkinsonism, and is, thus, not essential for the development of parkinsonism. However, increased PAC appears to correlate with the severity of fully developed parkinsonism.

Understanding Parkinson's disease and deep brain stimulation: Role of monkey models

Parkinson's disease (PD) is a progressive neurodegenerative movement disorder affecting over 10 million people worldwide. In the 1930s and 1940s there was little understanding regarding what caused PD or how to treat it. In a desperate attempt to improve patients' lives different regions of the neuraxis were ablated. Morbidity and mortality were common, but some patients' motor signs improved with lesions involving the basal ganglia or thalamus. With the discovery of l-dopa the advent of medical therapy began and surgical approaches became less frequent. It soon became apparent, however, that medical therapy was associated with side effects in the form of drug-induced dyskinesia and motor fluctuations and surgical therapies reemerged. Fortunately, during this time studies in monkeys had begun to lay the groundwork to understand the functional organization of the basal ganglia, and with the discovery of the neurotoxin MPTP a monkey model of PD had been developed. Using this model scientists were characterizing the physiological changes that occurred in the basal ganglia in PD and models of basal ganglia function and dysfunction were proposed. This work provided the rationale for the return of pallidotomy, and subsequently deep brain stimulation procedures. In this paper we describe the evolution of these monkey studies, how they provided a greater understanding of the pathophysiology underlying the development of PD and provided the rationale for surgical procedures, the search to understand mechanisms of DBS, and how these studies have been instrumental in understanding PD and advancing the development of surgical therapies for its treatment.

Bifurcation structure determines different phase-amplitude coupling patterns in the activity of biologically plausible neural networks

Phase-amplitude cross frequency coupling (PAC) is a rather ubiquitous phenomenon that has been observed in a variety of physical domains; however, the mechanisms underlying the emergence of PAC and its functional significance in the context of neural processes are open issues under debate. In this work we analytically demonstrate that PAC phenomenon naturally emerges in mean-field models of biologically plausible networks, as a signature of specific bifurcation structures. The proposed analysis, based on bifurcation theory, allows the identification of the mechanisms underlying oscillatory dynamics that are essentially different in the context of PAC. Specifically, we found that two PAC classes can coexist in the complex dynamics of the analyzed networks: 1) harmonic PAC which is an epiphenomenon of the nonsinusoidal waveform shape characterized by the linear superposition of harmonically related spectral components, and 2) nonharmonic PAC associated with "true" coupled oscillatory dynamics with independent frequencies elicited by a secondary Hopf bifurcation and mechanisms involving periodic excitation/inhibition (PEI) of a network population. Importantly, these two PAC types have been experimentally observed in a variety of neural architectures confounding traditional parametric and nonparametric PAC metrics, like those based on linear filtering or the waveform shape analysis, due to the fact that these methods operate on a single one-dimensional projection of an intrinsically multidimensional system dynamics. We exploit the proposed tools to study the functional significance of the PAC phenomenon in the context of Parkinson's disease (PD). Our results show that pathological slow oscillations (e.g. β band) and nonharmonic PAC patterns emerge from dissimilar underlying mechanisms (bifurcations) and are associated to the competition of different BG-thalamocortical loops. Thus, this study provides theoretical arguments that demonstrate that nonharmonic PAC is not an epiphenomenon related to the pathological β band oscillations, thus supporting the experimental evidence about the relevance of PAC as a potential biomarker of PD.

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.

Longitudinal Recordings Reveal Transient Increase of Alpha/Low-Beta Power in the Subthalamic Nucleus Associated With the Onset of Parkinsonian Rest Tremor

Functional magnetic resonance imaging studies suggest that different subcortico-cortical circuits control different aspects of Parkinsonian rest tremor. The basal ganglia were proposed to drive tremor onset, and the cerebellum was suggested to be responsible for tremor maintenance (“dimmer-switch” hypothesis). Although several electrophysiological correlates of tremor have been described, it is currently unclear whether any of these is specific to tremor onset or maintenance. In this study, we present data from a single patient measured repeatedly within 2 years after implantation of a deep brain stimulation (DBS) system capable of recording brain activity from the target. Local field potentials (LFPs) from the subthalamic nucleus and the scalp electroencephalogram were recorded 1 week, 3 months, 6 months, 1 year, and 2 years after surgery. Importantly, the patient suffered from severe rest tremor of the lower limbs, which could be interrupted voluntarily by repositioning the feet. This provided the unique opportunity to record many tremor onsets in succession. We found that tremor onset and tremor maintenance were characterized by distinct modulations of subthalamic oscillations. Alpha/low-beta power increased transiently immediately after tremor onset. In contrast, beta power was continuously suppressed during tremor maintenance. Tremor maintenance was additionally associated with subthalamic and cortical power increases around individual tremor frequency. To our knowledge, this is the first evidence of distinct subthalamic LFP modulations in tremor onset and tremor maintenance. Our observations suggest the existence of an acceleration signal for Parkinsonian rest tremor in the basal ganglia, in line with the “dimmer-switch” hypothesis.

Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson's disease

In this paper, we present a novel Bayesian adaptive dual controller (ADC) for autonomously programming deep brain stimulation devices. We evaluated the Bayesian ADC's performance in the context of reducing beta power in a computational model of Parkinson's disease, in which it was tasked with finding the set of stimulation parameters which optimally reduced beta power as fast as possible. Here, the Bayesian ADC has dual goals: (a) to minimize beta power by exploiting the best parameters found so far, and (b) to explore the space to find better parameters, thus allowing for better control in the future. The Bayesian ADC is composed of two parts: an inner parameterized feedback stimulator and an outer parameter adjustment loop. The inner loop operates on a short time scale, delivering stimulus based upon the phase and power of the beta oscillation. The outer loop operates on a long time scale, observing the effects of the stimulation parameters and using Bayesian optimization to intelligently select new parameters to minimize the beta power. We show that the Bayesian ADC can efficiently optimize stimulation parameters, and is superior to other optimization algorithms. The Bayesian ADC provides a robust and general framework for tuning stimulation parameters, can be adapted to use any feedback signal, and is applicable across diseases and stimulator designs.

Longer β oscillatory episodes reliably identify pathological subthalamic activity in Parkinsonism

BACKGROUND

The efficacy of deep brain stimulation (DBS) - primarily of the subthalamic nucleus (STN) - for advanced Parkinson's disease (PD) is commonly attributed to the suppression of pathological synchronous β oscillations along the cortico-thalamo-basal ganglia network. Conventional continuous high-frequency DBS indiscriminately influences pathological and normal neural activity. The DBS protocol would therefore be more effective if stimulation was only applied when necessary (closed-loop adaptive DBS).

OBJECTIVES AND METHODS

Our study aimed to identify a reliable biomarker of the pathological neuronal activity in parkinsonism that could be used as a trigger for adaptive DBS. To this end, we examined the oscillatory features of paired spiking activities recorded in three distinct nodes of the basal ganglia network of 2 African green monkeys before and after induction of parkinsonism (by MPTP intoxication).

RESULTS

Parkinsonism-related basal ganglia β oscillations consisted of synchronized time-limited episodes, rather than a continuous stretch, of β oscillatory activity. Episodic basal ganglia β oscillatory activity, although prolonged in parkinsonism, was not necessarily pathological given that short β episodes could also be detected in the healthy state. Importantly, prolongation of the basal ganglia β episodes was more pronounced than their intensification in the parkinsonian state-especially in the STN. Hence, deletion of longer β episodes was more effective than deletion of stronger β episodes in reducing parkinsonian STN synchronized oscillatory activity.

CONCLUSIONS

Prolonged STN β episodes are pathological in parkinsonism and can be used as optimal trigger for future adaptive DBS applications. © 2018 International Parkinson and Movement Disorder Society.

Mathematical Modeling for Description of Oscillation Suppression Induced by Deep Brain Stimulation

A mathematical modeling for description of oscillation suppression by deep brain stimulation (DBS) is explored in this paper. High-frequency DBS introduced to the basal ganglia network can suppress pathological neural oscillations that occur in the Parkinsonian state. However, selecting appropriate stimulation parameters remains a challenging issue due to the limited understanding of the underlying mechanisms of the Parkinsonian state and its control. In this paper, we use a describing function analysis to provide an intuitive way to select the optimal stimulation parameters based on a biologically plausible computational model of the Parkinsonian neural network. By the stability analysis using the describing function method, effective DBS parameter regions for inhibiting the pathological oscillations can be predicted. Additionally, it is also found that a novel sinusoidal-shaped DBS may become an alternative stimulation pattern and expends less energy, but with a different mechanism. This paper provides new insight into the possible mechanisms underlying DBS and a prediction of optimal DBS parameter settings, and even suggests how to select novel DBS wave patterns for the treatment of movement disorders, such as Parkinson's disease.

Predictive encoding of motor behavior in the supplementary motor area is disrupted in parkinsonism

Many studies suggest that Parkinson's disease (PD) is associated with changes in neuronal activity patterns throughout the basal ganglia-thalamocortical motor circuit. There are limited electrophysiological data, however, describing how parkinsonism impacts the presupplementary motor area (pre-SMA) and SMA proper (SMAp), cortical areas known to be involved in movement planning and motor control. In this study, local field potentials (LFPs) were recorded in the pre-SMA/SMAp of a nonhuman primate during a visually cued reaching task. Recordings were made in the same subject in both the naive and parkinsonian state using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine model of parkinsonism. We found that in the naive animal, well before a go-cue providing instruction of reach onset and direction was given, LFP activity was dynamically modulated in both high (20-30 Hz) and low beta (10-20 Hz) bands, and the magnitude of this modulation (e.g., decrease/increase in beta amplitude for each band, respectively) correlated linearly with reaction time (RT) on a trial-to-trial basis, suggesting it may predictively encode for RT. Consistent with this hypothesis, we observed that this activity was more prominent within the pre-SMA compared with SMAp. In the parkinsonian state, however, pre-SMA/SMAp beta band modulation was disrupted, particularly in the high beta band, such that the predictive encoding of RT was significantly diminished. In addition, the predictive encoding of RT preferentially within pre-SMA over SMAp was lost. These findings add to our understanding of the role of pre-SMA/SMAp in motor behavior and suggest a fundamental role of these cortical areas in early preparatory and premovement processes that are altered in parkinsonism. NEW & NOTEWORTHY Goal-directed movements, such as reaching for an object, necessitate temporal preparation and organization of information processing within the basal ganglia-thalamocortical motor network. Impaired movement in parkinsonism is thought to be the result of pathophysiological activity disrupting information flow within this network. This work provides neurophysiological evidence linking altered motor preplanning processes encoded in pre-SMA/SMAp beta band modulation to the pathogenesis of motor disturbances in parkinsonism.

Modeling and Analysis of Beta Oscillations in the Basal Ganglia

Enhanced beta (12-30 Hz) oscillatory activity in the basal ganglia (BG) is a prominent feature of the Parkinsonian state in animal models and in patients with Parkinson's disease. Increased beta oscillations are associated with severe dopaminergic striatal depletion. However, the mechanisms underlying these pathological beta oscillations remain elusive. Inspired by the experimental observation that only subsets of neurons within each nucleus in the BG exhibit oscillatory activities, a computational model of the BG-thalamus neuronal network is proposed, which is characterized by subdivided nuclei within the BG. Using different currents externally applied to the neurons within a given nucleus, neurons behave according to one of the two subgroups, named "-N" and "-P," where "-N" and "-P" denote the normal and the Parkinsonian states, respectively. The ratio of "-P" to "-N" neurons indicates the degree of the Parkinsonian state. Simulation results show that if "-P" neurons have a high degree of connectivity in the subthalamic nucleus (STN), they will have a significant downstream effect on the generation of beta oscillations in the globus pallidus. Interestingly, however, the generation of beta oscillations in the STN is independent of the selection of the "-P" neurons in the external segment of the globus pallidus (GPe), despite the reciprocal structure between STN and GPe. This computational model may pave the way to revealing the mechanism of such pathological behaviors in a realistic way that can replicate experimental observations. The simulation results suggest that the STN is more suitable than GPe as a deep brain stimulation target.

High-resolution local field potentials measured with deep brain stimulation arrays

OBJECTIVE

Local field potential (LFP) recordings along a deep brain stimulation (DBS) lead can provide useful feedback for titrating DBS therapy. However, conventional DBS leads with four cylindrical macroelectrodes likely undersample the spatial distribution of sinks and sources in a given brain region. In this study, we investigated the spectral power and spatial feature sizes of LFP activity in non-human primate subthalamic nucleus and globus pallidus using chronically implanted 32-channel directional DBS arrays.

APPROACH

Subthalamic nucleus and globus pallidus LFP signals were recorded from directional DBS arrays in the resting state and during a reach-and-retrieval task in two non-human primates in naïve and parkinsonian conditions. LFP recordings were compared amongst bipolar pairs of electrodes using individual and grouped electrode configurations, with the latter mimicking the cylindrical macroelectrode configurations used in current clinical LFP recordings.

MAIN RESULTS

Recordings from these DBS arrays showed that (1) beta oscillations have spatial 'fingerprints' in the subthalamic nucleus and globus pallidus, and (2) that these oscillations were muted when grouping electrode contacts together to create cylindrical macroelectrodes similar in relative dimension to those used clinically. Further, these maps depended on parkinsonian condition and whether the subject was resting or performing a motor task.

SIGNIFICANCE

Development of future closed-loop DBS therapies that rely on LFP feedback will benefit from implanting DBS arrays with electrode sizes and spacings that are more consistent with the dimensions of oscillatory sinks and sources within the brain.

Occurrence of thalamic high frequency oscillations in patients with different tremor syndromes

OBJECTIVE

To assess whether high frequency oscillations (HFOs, >150 Hz), known to occur in basal ganglia nuclei, can be observed in the thalamus.

METHODS

We recorded intraoperative local field potentials from the ventral intermediate nucleus (VIM) of the thalamus in patients with Essential Tremor (N = 16), Parkinsonian Tremor (3), Holmes Tremor (2) and Dystonic Tremor (1) during implantation of electrodes for deep brain stimulation. Recordings were performed with up to five micro/macro-electrodes that were simultaneously advanced to the stereotactic target.

RESULTS

Thalamic HFOs occurred in all investigated tremor syndromes. A detailed analysis of the Essential Tremor subgroup revealed that medial channels recorded HFOs more frequently than other channels. The highest peaks were observed 4 mm above target. Macro- but not microelectrode recordings were dominated by peaks in the slow HFO band (150-300 Hz), which were stable across several depths and channels.

CONCLUSION

HFOs occur in the thalamus and are not specific to any of the tremors investigated. Their spatial distribution is not homogeneous, and their appearance depends on the type of electrode used for recording.

SIGNIFICANCE

The occurrence of HFOs in the thalamus of tremor patients indicates that HFOs are not part of basal ganglia pathophysiology.

Parkinsonian Rest Tremor Is Associated With Modulations of Subthalamic High-Frequency Oscillations

BACKGROUND

High frequency oscillations (>200 Hz) have been observed in the basal ganglia of PD patients and were shown to be modulated by the administration of levodopa and voluntary movement.

OBJECTIVE

The objective of this study was to test whether the power of high-frequency oscillations in the STN is associated with spontaneous manifestation of parkinsonian rest tremor.

METHODS

The electromyogram of both forearms and local field potentials from the STN were recorded in 11 PD patients (10 men, age 58 [9.4] years, disease duration 9.2 [6.3] years). Patients were recorded at rest and while performing repetitive hand movements before and after levodopa intake. High-frequency oscillation power was compared across epochs containing rest tremor, tremor-free rest, or voluntary movement and related to the tremor cycle.

RESULTS

We observed prominent slow (200-300 Hz) and fast (300-400 Hz) high-frequency oscillations. The ratio between slow and fast high-frequency oscillation power increased when tremor became manifest. This increase was consistent across nuclei (94%) and occurred in medication ON and OFF. The ratio outperformed other potential markers of tremor, such as power at individual tremor frequency, beta power, or low gamma power. For voluntary movement, we did not observe a significant difference when compared with rest or rest tremor. Finally, rhythmic modulations of high-frequency oscillation power occurred within the tremor cycle.

CONCLUSIONS

Subthalamic high-frequency oscillation power is closely linked to the occurrence of parkinsonian rest tremor. The balance between slow and fast high-frequency oscillation power combines information on motor and medication state. © 2016 International Parkinson and Movement Disorder Society.

The role of cortical oscillations in a spiking neural network model of the basal ganglia

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8–12Hz) and beta (13–30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus—globus pallidus loop. In contrast, gamma (30–90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders.

Parkinsonism and vigilance: alteration in neural oscillatory activity and phase-amplitude coupling in the basal ganglia and motor cortex

Oscillatory neural activity in different frequency bands and phase-amplitude coupling (PAC) are hypothesized to be biomarkers of Parkinson's disease (PD) that could explain dysfunction in the motor circuit and be used for closed-loop deep brain stimulation (DBS). How these putative biomarkers change from the normal to the parkinsonian state across nodes in the motor circuit and within the same subject, however, remains unknown. In this study, we characterized how parkinsonism and vigilance altered oscillatory activity and PAC within the primary motor cortex (M1), subthalamic nucleus (STN), and globus pallidus (GP) in two nonhuman primates. Static and dynamic analyses of local field potential (LFP) recordings indicate that 1) after induction of parkinsonism using the neurotoxin MPTP, low-frequency power (8-30 Hz) increased in the STN and GP in both subjects, but increased in M1 in only one subject; 2) high-frequency power (~330 Hz) was present in the STN in both normal subjects but absent in the parkinsonian condition; 3) elevated PAC measurements emerged in the parkinsonian condition in both animals, but in different sites in each animal (M1 in one subject and GPe in the other); and 4) the state of vigilance significantly impacted how oscillatory activity and PAC were expressed in the motor circuit. These results support the hypothesis that changes in low- and high-frequency oscillatory activity and PAC are features of parkinsonian pathophysiology and provide evidence that closed-loop DBS systems based on these biomarkers may require subject-specific configurations as well as adaptation to changes in vigilance.NEW & NOTEWORTHY Chronically implanted electrodes were used to record neural activity across multiple nodes in the basal ganglia-thalamocortical circuit simultaneously in a nonhuman primate model of Parkinson's disease, enabling within-subject comparisons of electrophysiological biomarkers between normal and parkinsonian conditions and different vigilance states. This study improves our understanding of the role of oscillatory activity and phase-amplitude coupling in the pathophysiology of Parkinson's disease and supports the development of more effective DBS therapies based on pathophysiological biomarkers.

Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus

OBJECTIVE

To investigate the possibility of tremor detection based on deep brain activity.

METHODS

We re-analyzed recordings of local field potentials (LFPs) from the subthalamic nucleus in 10 PD patients (12 body sides) with spontaneously fluctuating rest tremor. Power in several frequency bands was estimated and used as input to Hidden Markov Models (HMMs) which classified short data segments as either tremor-free rest or rest tremor. HMMs were compared to direct threshold application to individual power features.

RESULTS

Applying a threshold directly to band-limited power was insufficient for tremor detection (mean area under the curve [AUC] of receiver operating characteristic: 0.64, STD: 0.19). Multi-feature HMMs, in contrast, allowed for accurate detection (mean AUC: 0.82, STD: 0.15), using four power features obtained from a single contact pair. Within-patient training yielded better accuracy than across-patient training (0.84vs. 0.78, p=0.03), yet tremor could often be detected accurately with either approach. High frequency oscillations (>200Hz) were the best performing individual feature.

CONCLUSIONS

LFP-based markers of tremor are robust enough to allow for accurate tremor detection in short data segments, provided that appropriate statistical models are used.

SIGNIFICANCE

LFP-based markers of tremor could be useful control signals for closed-loop deep brain stimulation.

Frequency and function in the basal ganglia: the origins of beta and gamma band activity

KEY POINTS

Neuronal oscillations in the basal ganglia have been observed to correlate with behaviours, although the causal mechanisms and functional significance of these oscillations remain unknown. We present a novel computational model of the healthy basal ganglia, constrained by single unit recordings from non-human primates. When the model is run using inputs that might be expected during performance of a motor task, the network shows emergent phenomena: it functions as a selection mechanism and shows spectral properties that match those seen in vivo. Beta frequency oscillations are shown to require pallido-striatal feedback, and occur with behaviourally relevant cortical input. Gamma oscillations arise in the subthalamic-globus pallidus feedback loop, and occur during movement. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the basal ganglia and lays the foundation for an integrated approach to study basal ganglia pathologies such as Parkinson's disease in silico.

ABSTRACT

Neural oscillations in the basal ganglia (BG) are well studied yet remain poorly understood. Behavioural correlates of spectral activity are well described, yet a quantitative hypothesis linking time domain dynamics and spectral properties to BG function has been lacking. We show, for the first time, that a unified description is possible by interpreting previously ignored structure in data describing globus pallidus interna responses to cortical stimulation. These data were used to expose a pair of distinctive neuronal responses to the stimulation. This observation formed the basis for a new mathematical model of the BG, quantitatively fitted to the data, which describes the dynamics in the data, and is validated against other stimulus protocol experiments. A key new result is that when the model is run using inputs hypothesised to occur during the performance of a motor task, beta and gamma frequency oscillations emerge naturally during static-force and movement, respectively, consistent with experimental local field potentials. This new model predicts that the pallido-striatum connection has a key role in the generation of beta band activity, and that the gamma band activity associated with motor task performance has its origins in the pallido-subthalamic feedback loop. The network's functionality as a selection mechanism also occurs as an emergent property, and closer fits to the data gave better selection properties. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the BG and therefore lays the foundation for an integrated approach to study BG pathologies such as Parkinson's disease in silico.

Inducible ablation of dopamine D2 receptors in adult mice impairs locomotion, motor skill learning and leads to severe parkinsonism

Motor execution and planning are tightly regulated by dopamine D1 and D2 receptors present in basal ganglia circuits. Although stimulation of D1 receptors is known to enhance motor function, the global effect of D2 receptor (D2R) stimulation or blockade remains highly controversial, with studies showing increasing, decreasing or no changes in motor activity. Moreover, pharmacological and genetic attempts to block or eliminate D2R have led to controversial results that questioned the importance of D2R in motor function. In this study, we generated an inducible Drd2 null-allele mouse strain that circumvented developmental compensations found in constitutive Drd2^-/- mice and allowed us to directly evaluate the participation of D2R in spontaneous locomotor activity and motor learning. We have found that loss of D2R during adulthood causes severe motor impairments, including hypolocomotion, deficits in motor coordination, impaired learning of new motor routines and spontaneous catatonia. Moreover, severe motor impairment, resting tremor and abnormal gait and posture, phenotypes reminiscent of Parkinson's disease, were evident when the mutation was induced in aged mice. Altogether, the conditional Drd2 knockout model studied here revealed the overall fundamental contribution of D2R in motor functions and explains some of the side effects elicited by D2R blockers when used in neurological and psychiatric conditions, including schizophrenia, bipolar disorder, Tourette's syndrome, dementia, alcohol-induced delusions and obsessive-compulsive disorder.

Network-wide oscillations in the parkinsonian state: alterations in neuronal activities occur in the premotor cortex in parkinsonian nonhuman primates

A number of studies suggest that Parkinson's disease (PD) is associated with alterations of neuronal activity patterns in the basal-ganglia-thalamocortical circuit. There are limited electrophysiological data, however, describing how the premotor cortex, which is involved in movement and decision-making, is likely impacted in PD. In this study, spontaneous local field potential (LFP) and single unit neuronal activity were recorded in the dorsal premotor area of nonhuman primates in both the naïve and parkinsonian state using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of parkinsonism. In both animals, we observed a shift of power in LFP power spectral densities (1-350 Hz) from higher to lower frequency bands; parkinsonism resulted in increased power in frequencies <8 Hz and decreased power at frequencies >30 Hz. A comparable but not identical trend was observed in the power spectral analysis of single unit spike trains: alpha power increased in both animals and gamma power decreased in one; power in other frequency bands remaining unchanged. Although not consistent across animals, we also observed changes in discharge rates and bursting activity. Overall, the LFP and single unit analysis suggest that abnormalities in premotor neural activity are a feature of parkinsonism, although specific details of those abnormalities may differ between subjects. This study further supports the concept that PD is a network disorder that induces abnormal spontaneous neural activities across the basal-ganglia-thalamocortical circuit including the premotor cortex and provides foundational knowledge for future studies regarding the relationship between changes in neuronal activity in this region and the development of motor deficits in PD.NEW & NOTEWORTHY This study begins to fill a gap in knowledge regarding how Parkinson's disease (PD) may cause abnormal functioning of the premotor cortex. It is novel as the premotor activity is examined in both the naïve and parkinsonian states, in the same subjects, at the single unit and LFP level. It provides foundational knowledge on which to build future studies to explore the relationships between premotor activities and specific parkinsonian motor and cognitive deficits.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson’s disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.