Time-frequency analysis of transient neuromuscular events: dynamic changes in activity of the subthalamic nucleus and forearm muscles related to the intermittent resting tremor

Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease

OBJECTIVE

Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application.

METHODS

In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations.

RESULTS

While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block).

CONCLUSION

We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations.

SIGNIFICANCE

Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.

Multi-timescale neuromodulation strategy for closed-loop deep brain stimulation in Parkinson's disease

Objective.Beta triggered closed-loop deep brain stimulation (DBS) shows great potential for improving the efficacy while reducing side effect for Parkinson's disease. However, there remain great challenges due to the dynamics and stochasticity of neural activities. In this study, we aimed to tune the amplitude of beta oscillations with different time scales taking into account influence of inherent variations in the basal ganglia-thalamus-cortical circuit.Approach. A dynamic basal ganglia-thalamus-cortical mean-field model was established to emulate the medication rhythm. Then, a dynamic target model was designed to embody the multi-timescale dynamic of beta power with milliseconds, seconds and minutes. Moreover, we proposed a closed-loop DBS strategy based on a proportional-integral-differential (PID) controller with the dynamic control target. In addition, the bounds of stimulation amplitude increments and different parameters of the dynamic target were considered to meet the clinical constraints. The performance of the proposed closed-loop strategy, including beta power modulation accuracy, mean stimulation amplitude, and stimulation variation were calculated to determine the PID parameters and evaluate neuromodulation performance in the computational dynamic mean-field model.Main results. The Results show that the dynamic basal ganglia-thalamus-cortical mean-field model simulated the medication rhythm with the fasted and the slowest rate. The dynamic control target reflected the temporal variation in beta power from milliseconds to minutes. With the proposed closed-loop strategy, the beta power tracked the dynamic target with a smoother stimulation sequence compared with closed-loop DBS with the constant target. Furthermore, the beta power could be modulated to track the control target under different long-term targets, modulation strengths, and bounds of the stimulation increment.Significance. This work provides a new method of closed-loop DBS for multi-timescale beta power modulation with clinical constraints.

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

Parkinsonian rest tremor can be distinguished from voluntary hand movements based on subthalamic and cortical activity

OBJECTIVE

To distinguish Parkinsonian rest tremor and different voluntary hand movements by analyzing brain activity.

METHODS

We re-analyzed magnetoencephalography and local field potential recordings from the subthalamic nucleus of six patients with Parkinson's disease. Data were obtained after withdrawal from dopaminergic medication (Med Off) and after administration of levodopa (Med On). Using gradient-boosted tree learning, we classified epochs as tremor, fist-clenching, forearm extension or tremor-free rest.

RESULTS

Subthalamic activity alone was insufficient for distinguishing the four different motor states (balanced accuracy mean: 38%, std: 7%). The combination of cortical and subthalamic features, in contrast, allowed for a much more accurate classification (balanced accuracy mean: 75%, std: 17%). Adding a single cortical area improved balanced accuracy by 17% on average, as compared to classification based on subthalamic activity alone. In most patients, the most informative cortical areas were sensorimotor cortical regions. Decoding performance was similar in Med On and Med Off.

CONCLUSIONS

Electrophysiological recordings allow for distinguishing several motor states, provided that cortical signals are monitored in addition to subthalamic activity.

SIGNIFICANCE

By combining cortical recordings, subcortical recordings and machine learning, adaptive deep brain stimulation systems might be able to detect tremor specifically and to respond adequately to several motor states.

Paradoxical Modulation of STN β-Band Activity with Medication Compared to Deep Brain Stimulation

BACKGROUND

Excessive subthalamic nucleus (STN) β-band (13-35 Hz) synchronized oscillations has garnered interest as a biomarker for characterizing disease state and developing adaptive stimulation systems for Parkinson's disease (PD).

OBJECTIVES

To report on a patient with abnormal treatment-responsive modulation in the β-band.

METHODS

We examined STN local field potentials from an externalized deep brain stimulation (DBS) lead while assessing PD motor signs in four conditions (OFF, MEDS, DBS, and MEDS+DBS).

RESULTS

The patient presented here exhibited a paradoxical increase in β power following administration of levodopa and pramipexole (MEDS), but an attenuation in β power during DBS and MEDS+DBS despite clinical improvement of 50% or greater under all three therapeutic conditions.

CONCLUSIONS

This case highlights the need for further study on the role of β oscillations in the pathophysiology of PD and the importance of personalized approaches to the development of β or other biomarker-based DBS closed loop algorithms. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson's disease

Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) with less energy delivered to the brain and less stimulation induced side effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement in people with Parkinson's disease and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over a time period of 400 ms in most previous ADBS studies, but a shorter smoothing period could have the advantage of being more sensitive to changes in beta power, which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400 ms and a shorter 200 ms smoothing window during reaching movements. Results from 13 people with Parkinson's disease showed that reducing the smoothing window for quantifying beta did lead to shortened beta burst durations by increasing the number of beta bursts shorter than 200 ms and more frequent switching on/off of the stimulator but had no behavioural effects. Both ADBS and CDBS improved motor performance to an equivalent extent compared to no DBS. Secondary analysis revealed that there were independent effects of a decrease in beta power and an increase in gamma power in predicting faster movement speed, while a decrease in beta event related desynchronization (ERD) predicted quicker movement initiation. CDBS suppressed both beta and gamma more than ADBS, whereas beta ERD was reduced to a similar level during CDBS and ADBS compared with no DBS, which together explained the achieved similar performance improvement in reaching movements during CDBS and ADBS. In addition, ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. These results suggest that STN beta-triggered ADBS is effective in improving motor performance during reaching movements in people with Parkinson's disease, and that shortening of the smoothing window does not result in any additional behavioural benefit. When developing ADBS systems for Parkinson's disease, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and information from motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.

Multivariable closed-loop control of deep brain stimulation for Parkinson's disease

Objective. Closed-loop deep brain stimulation (DBS) methods for Parkinson's disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered.Approach.A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals.Main results.Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered.Significance.Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.

EEG dynamics induced by zolpidem forecast consciousness evolution in prolonged disorders of consciousness

OBJECTIVE

To explore whether the EEG dynamics induced by zolpidem can predict consciousness evolution in patients with prolonged disorders of consciousness (PDOC).

METHODS

We conducted a prospective explorative analysis on thirty-six patients with PDOC and eleven healthy controls. The EEG power spectrum was analyzed and categorized into 'ABCD' patterns at baseline and one hour after zolpidem administration at 10 mg. The clinical outcome was defined as consciousness improvement and no improvement six months after enrollment using the Coma Recovery Scale-Revised (CRS-R) score.

RESULTS

Zolpidem administration significantly increased the EEG power in the delta & theta bands and decreased EEG power in the beta bands in healthy controls. Further follow-up studies indicated that the increased EEG beta-band power induced by zolpidem can predict an improved consciousness six months after enrollment with an area under the receiver operating characteristic curve (AUC) of 0.829, the sensitivity of 94.38% and an accuracy of 81.48%.

CONCLUSIONS

Our work revealed that the specific EEG responses to zolpidem can predict consciousness recovery in PDOC patients.

SIGNIFICANCE

The zolpidem-induced specific EEG responses could potentially predict the recovery of PDOC patients, which may help clinicians and patients' families in their decision-making process.

Quantification of Head Tremors in Medical Conditions: A Comparison of Analyses Using a 2D Video Camera and a 3D Wireless Inertial Motion Unit

This study compares two methods to quantify the amplitude and frequency of head movements in patients with head tremor: one based on video-based motion analysis, and the other using a miniature wireless inertial magnetic motion unit (IMMU). Concomitant with the clinical assessment of head tremor severity, head linear displacements in the frontal plane and head angular displacements in three dimensions were obtained simultaneously in forty-nine patients using one video camera and an IMMU in three experimental conditions while sitting (at rest, counting backward, and with arms extended). Head tremor amplitude was quantified along/around each axis, and head tremor frequency was analyzed in the frequency and time-frequency domains. Correlation analysis investigated the association between the clinical severity of head tremor and head linear and angular displacements. Our results showed better sensitivity of the IMMU compared to a 2D video camera to detect changes of tremor amplitude according to examination conditions, and better agreement with clinical measures. The frequency of head tremor calculated from video data in the frequency domain was higher than that obtained using time-frequency analysis and those calculated from the IMMU data. This study provides strong experimental evidence in favor of using an IMMU to quantify the amplitude and time-frequency oscillatory features of head tremor, especially in medical conditions.

Adaptive deep brain stimulation: Retuning Parkinson's disease

A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.

Real-time removal of stimulation artifacts in closed-loop deep brain stimulation

Objective.Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters.Approach.We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals andin vivoclosed-loop DBS applications in Parkinsonian animal models.Main results. The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2-150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS applicationsin vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations.Significance.The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.

Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology

Introduction: Advances in neuromodulation and deep brain stimulation (DBS) technologies have facilitated opportunities for improved clinical benefit and side effect management. However, new technologies have added complexity to clinic-based DBS programming.Areas covered: In this article, we review basic basal ganglia physiology, proposed mechanisms of action and technical aspects of DBS. We discuss novel DBS technologies for movement disorders including the role of advanced imaging software, lead design, IPG design, novel programming techniques including directional stimulation and coordinated reset neuromodulation. Additional topics include the use of potential biomarkers, such as local field potentials, electrocorticography, and adaptive stimulation. We will also discuss future directions including optogenetically inspired DBS.Expert opinion: The introduction of DBS for the management of movement disorders has expanded treatment options. In parallel with our improved understanding of brain physiology and neuroanatomy, new technologies have emerged to address challenges associated with neuromodulation, including variable effectiveness, side-effects, and programming complexity. Advanced functional neuroanatomy, improved imaging, real-time neurophysiology, improved electrode designs, and novel programming techniques have collectively been driving improvements in DBS outcomes.

Local field potentials in Parkinson's disease: A frequency-based review

Deep brain stimulation (DBS) surgery offers a unique opportunity to record local field potentials (LFPs), the electrophysiological population activity of neurons surrounding the depth electrode in the target area. With direct access to the subcortical activity, LFP research has provided valuable insight into disease mechanisms and cognitive processes and inspired the advent of adaptive DBS for Parkinson's disease (PD). A frequency-based framework is usually employed to interpret the implications of LFP signatures in LFP studies on PD. This approach standardizes the methodology, simplifies the interpretation of LFP patterns, and makes the results comparable across studies. Importantly, previous works have found that activity patterns do not represent disease-specific activity but rather symptom-specific or task-specific neuronal signatures that relate to the current motor, cognitive or emotional state of the patient and the underlying disease. In the present review, we aim to highlight distinguishing features of frequency-specific activities, mainly within the motor domain, recorded from DBS electrodes in patients with PD. Associations of the commonly reported frequency bands (delta, theta, alpha, beta, gamma, and high-frequency oscillations) to motor signs are discussed with respect to band-related phenomena such as individual tremor and high/low beta frequency activity, as well as dynamic transients of beta bursts. We provide an overview on how electrophysiology research in DBS patients has revealed and will continuously reveal new information about pathophysiology, symptoms, and behavior, e.g., when combining deep LFP and surface electrocorticography recordings.

Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia

Low-frequency oscillatory activity (3-9 Hz) and increased synchrony in the basal ganglia (BG) are recognized to be crucial for Parkinsonian tremor. However, the dynamical mechanism underlying the tremor-related oscillations still remains unknown. In this paper, the roles of the indirect and hyperdirect pathways on synchronization and tremor-related oscillations are considered based on a modified Hodgkin-Huxley model. Firstly, the effects of indirect and hyperdirect pathways are analysed individually, which show that increased striatal activity to the globus pallidus external (GPe) or strong cortical gamma input to the subthalamic nucleus (STN) is sufficient to promote synchrony and tremor-related oscillations in the BG network. Then, the mutual effects of both pathways are analysed by adjusting the related currents simultaneously. Our results suggest that synchrony and tremor-related oscillations would be strengthened if the current of these two paths are in relative imbalance. And the network tends to be less synchronized and less tremulous when the frequency of cortical input is in the theta band. These findings may provide novel treatments in the cortex and striatum to alleviate symptoms of tremor in Parkinson's disease.

Brain Network Oscillations During Gait in Parkinson's Disease

Human bipedal walking is a complex motor task that requires supraspinal control for balance and flexible coordination of timing and scaling of many muscles in different environment. Gait impairments are a hallmark of Parkinson’s disease (PD), reflecting dysfunction of cortico-basal ganglia-brainstem circuits. Recent studies using implanted electrodes and surface electroencephalography have demonstrated gait-related brain oscillations in the basal ganglia and cerebral cortex. Here, we review the physiological and pathophysiological roles of (1) basal ganglia oscillations, (2) cortical oscillations, and (3) basal ganglia-cortical interactions during walking. These studies extend a novel framework for movement of disorders where specific patterns of abnormal oscillatory synchronization in the basal ganglia thalamocortical network are associated with specific signs and symptoms. Therefore, we propose that many gait dysfunctions in PD arise from derangements in brain network, and discuss potential therapies aimed at restoring gait impairments through modulation of brain network in PD.

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.

Local field potential dynamics in the primate cortex in relation to parkinsonism reveled by machine learning: A comparison between the primary motor cortex and the supplementary area

The present study compares the cortical local field potentials (LFPs) in the primary motor cortex (M1) and the supplementary motor area (SMA) of non-human primates rendered Parkinsonian with administration of dopaminergic neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The dynamic of the LFPs was investigated under several mathematical frameworks and machine learning was used to discriminate the recordings based on these features between healthy, parkinsonian with off-medication and parkinsonian with on-medication states. The importance of each feature in the discrimination process was further investigated. The dynamic of the LFPs in M1 and SMA was affected regarding its variability (time domain analysis), oscillatory activities (frequency domain analysis) and complex patterns (non-linear domain analysis). Machine learning algorithms achieved accuracy near 0.90 for comparisons between conditions. The TreeBagger algorithm provided best accuracy. The relative importance of these features differed with the cortical location, condition and treatment. Overall, the most important features included beta oscillation, fractal dimension, gamma oscillation, entropy and asymmetry of amplitude fluctuation. The importance of features in discriminating between normal and pathological states, and on- or off-medication states depends on the pair-comparison and it is region-specific. These findings are discussed regarding the refinement of current models for movement disorders and the development of on-demand therapies.

The Top 50 Most-Cited Articles in Orthostatic Tremor: A Bibliometric Review

Background

Article-level citation count is a hallmark indicating scientific impact. We aimed to pinpoint and evaluate the top 50 most-cited articles in orthostatic tremor (OT).

Methods

The ISI Web of Knowledge database and 2017 Journal Citation Report Science Edition were used to retrieve the 50 top-cited OT articles published from 1984 to April 2019. Information was collected by the Analyze Tool on the Web of Science, including number of citations, publication title, journal name, publication year, and country and institution of origin. Supplementary analyses were undertaken to clarify authorship, study design, level of evidence, and category.

Results

Up to 66% of manuscripts were recovered from five journals: Movement Disorders (n = 18), Brain (n = 4), Journal of Clinical Neurophysiology (n = 4), Neurology (n = 4), and Clinical Neurophysiology (n = 3). Articles were published between 1984 and 2018, with expert opinion as the predominant design (n = 22) and review as category (n = 17). Most articles had level 5 evidence (n = 26). According to their countries of origin, 34% of articles belonged to the United States (n = 17) leading the list, followed by United Kingdom (n = 15). University College London yielded the greater number of articles (n = 12), followed by the University of Kiel (n = 9). Most popular authors were G. Deuschl (n = 10), C.D. Marsden (n = 6), J. Jankovic (n = 5), P.D. Thompson (n = 5), J.C. Rothwell (n = 5), L.J. Findley (n = 4), and P. Brown (n = 4), who together accounted for 48% of them. All papers were in English.

Discussion

Publishing high-cited OT articles could be facilitated by source journal, study design, category, publication language, and country and institution of origin.

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.

Suppression of Parkinsonian Beta Oscillations by Deep Brain Stimulation: Determination of Effective Protocols

A neural field model of the corticothalamic-basal ganglia system is developed that describes enhanced beta activity within subthalamic and pallidal circuits in Parkinson's disease (PD) via system resonances. A model of deep brain stimulation (DBS) of typical clinical targets, the subthalamic nucleus (STN) and globus pallidus internus (GPi), is added and studied for several distinct stimulation protocols that are used for treatment of the motor symptoms of PD and that reduce pathological beta band activity (13-30 Hz) in the corticothalamic-basal ganglia network. The resulting impact of DBS on enhanced beta activity in the STN and GPi, as well as cortico-subthalamic and cortico-pallidal coherence, are studied. Both STN-DBS and GPi-DBS are found to be effective for suppressing peak STN and GPi power in the beta band, with GPi-DBS being slightly more effective in both the STN and the GPi for all stimulus protocols tested. The largest decrease in cortico-STN coherence is observed during STN-DBS, whereas GPi-DBS is most effective for reducing cortico-GPi coherence. A reduction of the pathologically large STN connection strengths that define the parkinsonian state results in enhanced 6 Hz activity and could thus represent a compensatory mechanism that has the side effect of driving parkinsonian tremor-like oscillations. This model provides a method for systematically testing effective DBS protocols that agrees with experimental and clinical findings. Furthermore, the model suggests GPi-DBS and STN-DBS have distinct impacts on elevated synchronization between the basal ganglia and motor cortex in PD.

Quantitative theory of deep brain stimulation of the subthalamic nucleus for the suppression of pathological rhythms in Parkinson's disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is modeled to explore the mechanisms of this effective, but poorly understood, treatment for motor symptoms of drug-refractory Parkinson's disease and dystonia. First, a neural field model of the corticothalamic-basal ganglia (CTBG) system is developed that reproduces key clinical features of Parkinson's disease, including its characteristic 4-8 Hz and 13-30 Hz electrophysiological signatures. Deep brain stimulation of the STN is then modeled and shown to suppress the pathological 13-30 Hz (beta) activity for physiologically realistic and optimized stimulus parameters. This supports the idea that suppression of abnormally coherent activity in the CTBG system is a major factor in DBS therapy for Parkinson's disease, by permitting normal dynamics to resume. At high stimulus intensities, nonlinear effects in the target population mediate wave-wave interactions between resonant beta activity and the stimulus pulse train, leading to complex spectral structure that shows remarkable similarity to that seen in steady-state evoked potential experiments.

Loss of Balance between Striatal Feedforward Inhibition and Corticostriatal Excitation Leads to Tremor

Fast-spiking interneurons (FSIs) exert powerful inhibitory control over the striatum and are hypothesized to balance the massive excitatory cortical and thalamic input to this structure. We recorded neuronal activity in the dorsolateral striatum and globus pallidus (GP) concurrently with the detailed movement kinematics of freely behaving female rats before and after selective inhibition of FSI activity using IEM-1460 microinjections. The inhibition led to the appearance of episodic rest tremor in the body part that depended on the somatotopic location of the injection within the striatum. The tremor was accompanied by coherent oscillations in the local field potential (LFP). Individual neuron activity patterns became oscillatory and coherent in the tremor frequency. Striatal neurons, but not GP neurons, displayed additional temporal, nonoscillatory correlations. The subsequent reduction in the corticostriatal input following muscimol injection to the corresponding somatotopic location in the primary motor cortex led to disruption of the tremor and a reduction of the LFP oscillations and individual neuron's phase-locked activity. The breakdown of the normal balance of excitation and inhibition in the striatum has been shown previously to be related to different motor abnormalities. Our results further indicate that the balance between excitatory corticostriatal input and feedforward FSI inhibition is sufficient to break down the striatal decorrelation process and generate oscillations resulting in rest tremor typical of multiple basal ganglia disorders.SIGNIFICANCE STATEMENT Fast-spiking interneurons (FSIs) play a key role in normal striatal processing by exerting powerful inhibitory control over the network. FSI malfunctions have been associated with abnormal processing of information within the striatum that leads to multiple movement disorders. Here, we study the changes in neuronal activity and movement kinematics following selective inhibition of these neurons. The injections led to the appearance of episodic rest tremor, accompanied by coherent oscillations in neuronal activity, which was reversed following corticostriatal inhibition. These results suggest that the balance between corticostriatal excitation and feedforward FSI inhibition is crucial for maintaining the striatal decorrelation process, and that its breakdown leads to the formation of oscillations resulting in rest tremor typical of multiple basal ganglia disorders.

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.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation

OBJECTIVE

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations.

APPROACH

Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model.

MAIN RESULTS

This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief.

SIGNIFICANCE

The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations.

Subthalamic neural entropy is a feature of freezing of gait in freely moving people with Parkinson's disease

The goal of this study was to investigate subthalamic (STN) neural features of Freezers and Non-Freezers with Parkinson's disease (PD), while freely walking without freezing of gait (FOG) and during periods of FOG, which were better elicited during a novel turning and barrier gait task than during forward walking.

METHODS

Synchronous STN local field potentials (LFPs), shank angular velocities, and ground reaction forces were measured in fourteen PD subjects (eight Freezers) off medication, OFF deep brain stimulation (DBS), using an investigative, implanted, sensing neurostimulator (Activa® PC+S, Medtronic, Inc.). Tasks included standing still, instrumented forward walking, stepping in place on dual forceplates, and instrumented walking through a turning and barrier course.

RESULTS

During locomotion without FOG, Freezers showed lower beta (13-30Hz) power (P=0.036) and greater beta Sample Entropy (P=0.032), than Non-Freezers, as well as greater gait asymmetry and arrhythmicity (P<0.05 for both). No differences in alpha/beta power and/or entropy were evident at rest. During periods of FOG, Freezers showed greater alpha (8-12Hz) Sample Entropy (P<0.001) than during walking without FOG.

CONCLUSIONS

A novel turning and barrier course was superior to FW in eliciting FOG. Greater unpredictability in subthalamic beta rhythms was evident during stepping without freezing episodes in Freezers compared to Non-Freezers, whereas greater unpredictability in alpha rhythms was evident in Freezers during FOG. Non-linear analysis of dynamic neural signals during gait in freely moving people with PD may yield greater insight into the pathophysiology of FOG; whether the increases in STN entropy are causative or compensatory remains to be determined. Some beta LFP power may be useful for rhythmic, symmetric gait and DBS parameters, which completely attenuate STN beta power may worsen rather than improve FOG.

Unified neural field theory of brain dynamics underlying oscillations in Parkinson's disease and generalized epilepsies

The mechanisms underlying pathologically synchronized neural oscillations in Parkinson's disease (PD) and generalized epilepsies are explored in parallel via a physiologically-based neural field model of the corticothalamic-basal ganglia (CTBG) system. The basal ganglia (BG) are approximated as a single effective population and their roles in the modulation of oscillatory dynamics of the corticothalamic (CT) system and vice versa are analyzed. In addition to normal EEG rhythms, enhanced activity around 4 Hz and 20 Hz exists in the model, consistent with the characteristic frequencies observed in PD. These rhythms result from resonances in loops formed between the BG and CT populations, analogous to those that underlie epileptic oscillations in a previous CT model, and which are still present in the combined CTBG system. Dopamine depletion is argued to weaken the dampening of these loop resonances in PD, and network connections then explain the significant coherence observed between BG, thalamic, and cortical population activity around 4-8 Hz and 20 Hz. Parallels between the afferent and efferent connection sites of the thalamic reticular nucleus (TRN) and BG predict low dopamine to correspond to a reduced likelihood of tonic-clonic (grand mal) seizures, which agrees with experimental findings. Furthermore, the model predicts an increased likelihood of absence (petit mal) seizure resulting from pathologically low dopamine levels in accordance with experimental observations. Suppression of absence seizure activity is demonstrated when afferent and efferent BG connections to the CT system are strengthened, which is consistent with other CTBG modeling studies. The BG are demonstrated to have a suppressive effect on activity of the CTBG system near tonic-clonic seizure states, which provides insight into the reported efficacy of current treatments in BG circuits. Sleep states of the TRN are also found to suppress pathological PD activity in accordance with observations. Overall, the findings demonstrate strong parallels between coherent oscillations in generalized epilepsies and PD, and provide insights into possible comorbidities.

Subthalamic oscillations and phase amplitude coupling are greater in the more affected hemisphere in Parkinson's disease

OBJECTIVE

Determine the incidence of resting state oscillations in alpha/beta, high frequency (HFO) bands, and their phase amplitude coupling (PAC) in a large cohort in Parkinson's disease (PD).

METHODS

Intra-operative local field potentials (LFPs) from subthalamic nucleus (STN) were recorded from 100 PD subjects, data from 74 subjects were included in the analysis.

RESULTS

Alpha/beta oscillations were evident in >99%, HFO in 87% and PAC in 98% of cases. Alpha/beta oscillations (P<0.01) and PAC were stronger in the more affected (MA) hemisphere (P=0.03). Alpha/beta oscillations were primarily found in 13-20Hz (low beta). Beta and HFO frequencies with the greatest coupling, were positively correlated (P=0.001). Tremor attenuated alpha (P=0.002) and beta band oscillations (P<0.001).

CONCLUSIONS

STN alpha/beta band oscillations and PAC were evident in ⩾98% cases and were greater in MA hemisphere. Resting tremor attenuated underlying alpha/beta band oscillations.

SIGNIFICANCE

Beta band LFP power may be used to drive adaptive deep brain stimulation (aDBS), augmented by a kinematic classifier in tremor dominant PD.

Assessment of Head Tremor with Accelerometers Versus Gyroscopic Transducers

Background

Accelerometers and gyroscopes are used commonly in the assessment of hand tremor, but their validity in the assessment of head tremor has not been studied. We hypothesized that gyroscopy would be superior to accelerometry because head tremor is rotational motion, and gyroscopes record rotational motion, free of gravitational artifact. We also hypothesized a strong logarithmic relationship between 0 to 4-point tremor ratings and the transducer measures of tremor amplitude, similar to those previously reported for hand tremor.

Methods

Head tremor was recorded for 1 minute in each of the five head positions used in the Essential Tremor Rating Assessment Scale, using a triaxial accelerometer and triaxial gyroscope mounted at the vertex of the head. Mean and maximum 3-second burst displacement tremor and rotation tremor were computed by spectral analysis. The minimum detectable change for the transducers was estimated using the residual mean squared error from repeated-measures analysis of variance.

Results

Tremor displacement and rotation (T) were logarithmically related to tremor ratings (tremor rating score; TRS): log(T) = α TRS + β, where α ≈ 0.47 for displacement and ≈0.64 for rotation, and β ≈ -1.8 and -1.4. Tremor ratings correlated more strongly with gyroscopy (r = 0.83-0.87) than with accelerometry (r = 0.71-0.75). Minimum detectable change (percent reduction) was approximately 66% of the baseline geometric mean.

Conclusions

Gyroscopic transducers are superior to accelerometry for assessment of head tremor. Both measures of head tremor are logarithmically related to tremor ratings. The minimum detectable change of the transducer measures is comparable to those previously reported for hand tremor.

Subthalamic and Cortical Local Field Potentials Associated with Pilocarpine-Induced Oral Tremor in the Rat

Tremulous jaw movements (TJMs) are rapid vertical deflections of the lower jaw that resemble chewing but are not directed at any particular stimulus. In rodents, TJMs are induced by neurochemical conditions that parallel those seen in human Parkinsonism, including neurotoxic or pharmacological depletion of striatal dopamine (DA), DA antagonism, and cholinomimetic administration. Moreover, TJMs in rodents can be attenuated by antiparkinsonian agents, including levodopa (L-DOPA), DA agonists, muscarinic antagonists, and adenosine A_2A antagonists. In human Parkinsonian patients, exaggerated physiological synchrony is seen in the beta frequency band in various parts of the cortical/basal ganglia/thalamic circuitry, and activity in the tremor frequency range (3–7 Hz) also has been recorded. The present studies were undertaken to determine if tremor-related local field potential (LFP) activity could be recorded from motor cortex (M1) or subthalamic nucleus (STN) during the TJMs induced by the muscarinic agonist pilocarpine, which is a well-known tremorogenic agent. Pilocarpine induced a robust TJM response that was marked by rhythmic electromyographic (EMG) activity in the temporalis muscle. Compared to periods with no tremor activity, TJM epochs were characterized by increased LFP activity in the tremor frequency range in both neocortex and STN. Tremor activity was not associated with increased synchrony in the beta frequency band. These studies identified tremor-related LFP activity in parts of the cortical/basal ganglia circuitry that are involved in the pathophysiology of Parkinsonism. This research may ultimately lead to identification of the oscillatory neural mechanisms involved in the generation of tremulous activity, and promote development of novel treatments for tremor disorders.

Using Portable Transducers to Measure Tremor Severity

BACKGROUND

Portable motion transducers, suitable for measuring tremor, are now available at a reasonable cost. The use of these transducers requires knowledge of their limitations and data analysis. The purpose of this review is to provide a practical overview and example software for using portable motion transducers in the quantification of tremor.

METHODS

Medline was searched via PubMed.gov in December 2015 using the Boolean expression "tremor AND (accelerometer OR accelerometry OR gyroscope OR inertial measurement unit OR digitizing tablet OR transducer)." Abstracts of 419 papers dating back to 1964 were reviewed for relevant portable transducers and methods of tremor analysis, and 105 papers written in English were reviewed in detail.

RESULTS

Accelerometers, gyroscopes, and digitizing tablets are used most commonly, but few are sold for the purpose of measuring tremor. Consequently, most software for tremor analysis is developed by the user. Wearable transducers are capable of recording tremor continuously, in the absence of a clinician. Tremor amplitude, frequency, and occurrence (percentage of time with tremor) can be computed. Tremor amplitude and occurrence correlate strongly with clinical ratings of tremor severity.

DISCUSSION

Transducers provide measurements of tremor amplitude that are objective, precise, and valid, but the precision and accuracy of transducers are mitigated by natural variability in tremor amplitude. This variability is so great that the minimum detectable change in amplitude, exceeding random variability, is comparable for scales and transducers. Research is needed to determine the feasibility of detecting smaller change using averaged data from continuous long-term recordings with wearable transducers.

Measuring complex behaviors of local oscillatory networks in deep brain local field potentials

BACKGROUND

Multiple oscillations emerging from the same neuronal substrate serve to construct a local oscillatory network. The network usually exhibits complex behaviors of rhythmic, balancing and coupling between the oscillations, and the quantification of these behaviors would provide valuable insight into organization of the local network related to brain states.

NEW METHOD

An integrated approach to quantify rhythmic, balancing and coupling neural behaviors based upon power spectral analysis, power ratio analysis and cross-frequency power coupling analysis was presented. Deep brain local field potentials (LFPs) were recorded from the thalamus of patients with neuropathic pain and dystonic tremor. t-Test was applied to assess the difference between the two patient groups.

RESULTS

The rhythmic behavior measured by power spectral analysis showed significant power spectrum difference in the high beta band between the two patient groups. The balancing behavior measured by power ratio analysis showed significant power ratio differences at high beta band to 8-20 Hz, and 30-40 Hz to high beta band between the patient groups. The coupling behavior measured by cross-frequency power coupling analysis showed power coupling differences at (theta band, high beta band) and (45-55 Hz, 70-80 Hz) between the patient groups.

COMPARISON WITH EXISTING METHOD

The study provides a strategy for studying the brain states in a multi-dimensional behavior space and a framework to screen quantitative characteristics for biomarkers related to diseases or nuclei.

CONCLUSIONS

The work provides a comprehensive approach for understanding the complex behaviors of deep brain LFPs and identifying quantitative biomarkers for brain states related to diseases or nuclei.

Characteristics of local field potentials correlate with pain relief by deep brain stimulation

OBJECTIVE

To investigate the link between neuronal activity recorded from the sensory thalamus and periventricular gray/periaqueductal gray (PVAG) and pain relief by deep brain stimulation (DBS).

METHODS

Local field potentials (LFPs) were recorded from the sensory thalamus and PVAG post-operatively from ten patients with neuropathic pain. The LFPs were quantified using spectral and time-frequency analysis, the relationship between the LFPs and pain relief was quantified with nonlinear correlation analysis.

RESULTS

The theta oscillations of both sensory thalamus and PVAG correlated inversely with pain relief. The high beta oscillations in the sensory thalamus and the alpha oscillations in the PVAG correlated positively with pain relief. Moreover, the ratio of high-power duration to low-power duration of theta band activity in the sensory thalamus and PVAG correlated inversely with pain relief. The duration ratio at the high beta band in the sensory thalamus correlated positively with pain relief.

CONCLUSIONS

Our results reveal distinct neuronal oscillations at the theta, alpha, and beta frequencies correlating with pain relief by DBS.

SIGNIFICANCE

The study provides quantitative measures for predicting the outcomes of neuropathic pain relief by DBS as well as potential biomarkers for developing adaptive stimulation strategies.

Electrocorticography reveals beta desynchronization in the basal ganglia-cortical loop during rest tremor in Parkinson's disease

The pathophysiology of rest tremor in Parkinson's disease (PD) is not well understood, and its severity does not correlate with the severity of other cardinal signs of PD. We hypothesized that tremor-related oscillatory activity in the basal-ganglia-thalamocortical loop might serve as a compensatory mechanism for the excessive beta band synchronization associated with the parkinsonian state. We recorded electrocorticography (ECoG) from the sensorimotor cortex and local field potentials (LFP) from the subthalamic nucleus (STN) in patients undergoing lead implantation for deep brain stimulation (DBS). We analyzed differences in measures of network synchronization during epochs of spontaneous rest tremor, versus epochs without rest tremor, occurring in the same subjects. The presence of tremor was associated with reduced beta power in the cortex and STN. Cortico-cortical coherence and phase-amplitude coupling (PAC) decreased during rest tremor, as did basal ganglia-cortical coherence in the same frequency band. Cortical broadband gamma power was not increased by tremor onset, in contrast to the movement-related gamma increase typically observed at the onset of voluntary movement. These findings suggest that the cortical representation of rest tremor is distinct from that of voluntary movement, and support a model in which tremor acts to decrease beta band synchronization within the basal ganglia-cortical loop.

A direct relationship between oscillatory subthalamic nucleus-cortex coupling and rest tremor in Parkinson's disease

Electrophysiological studies suggest that rest tremor in Parkinson's disease is associated with an alteration of oscillatory activity. Although it is well known that tremor depends on cortico-muscular coupling, it is unclear whether synchronization within and between brain areas is specifically related to the presence and severity of tremor. To tackle this longstanding issue, we took advantage of naturally occurring spontaneous tremor fluctuations and investigated cerebral synchronization in the presence and absence of rest tremor. We simultaneously recorded local field potentials from the subthalamic nucleus, the magnetoencephalogram and the electromyogram of forearm muscles in 11 patients with Parkinson's disease (all male, age: 52-74 years). Recordings took place the day after surgery for deep brain stimulation, after withdrawal of anti-parkinsonian medication. We selected epochs containing spontaneous rest tremor and tremor-free epochs, respectively, and compared power and coherence between subthalamic nucleus, cortex and muscle across conditions. Tremor-associated changes in cerebro-muscular coherence were localized by Dynamic Imaging of Coherent Sources. Subsequently, cortico-cortical coupling was analysed by computation of the imaginary part of coherency, a coupling measure insensitive to volume conduction. After tremor onset, local field potential power increased at individual tremor frequency and cortical power decreased in the beta band (13-30 Hz). Sensor level subthalamic nucleus-cortex, cortico-muscular and subthalamic nucleus-muscle coherence increased during tremor specifically at tremor frequency. The increase in subthalamic nucleus-cortex coherence correlated with the increase in electromyogram power. On the source level, we observed tremor-associated increases in cortico-muscular coherence in primary motor cortex, premotor cortex and posterior parietal cortex contralateral to the tremulous limb. Analysis of the imaginary part of coherency revealed tremor-dependent coupling between these cortical areas at tremor frequency and double tremor frequency. Our findings demonstrate a direct relationship between the synchronization of cerebral oscillations and tremor manifestation. Furthermore, they suggest the feasibility of tremor detection based on local field potentials and might thus become relevant for the design of closed-loop stimulation systems.

The distributed somatotopy of tremor: a window into the motor system

The posterior ventrolateral thalamus (VLp) plays a crucial role in Parkinson's tremor and in essential tremor: deep brain stimulation (DBS) of the VLp effectively diminishes both tremor types. Previous research has shown tremor oscillations in the VLp, but the spatial extent and somatotopy of these oscillations remained unclear. In this issue of Experimental Neurology, Pedrosa and colleagues measured neuro-muscular coherence at multiple sites in the VLp of patients with essential tremor and Parkinson's disease using implanted DBS electrodes (Pedrosa et al., 2012). They found multiple tremor clusters within the VLp, with spatially distinct tremor clusters for antagonistic muscles, and in many patients also multiple distinct tremor clusters for a single muscle. Interestingly, this group previously showed similar effects for the STN in tremulous Parkinson's disease (Reck et al., 2009, 2010). Together, these studies suggest that the distribution of tremor clusters is a general organizational principle of tremor, being present in two different tremor pathologies, and in two different nodes of the motor system. The presence of multiple tremor clusters also fits with the distributed somatotopy of the healthy motor system. Therefore, a further conclusion of this study could be that tremor is caused by aberrant synchronization within an otherwise healthy network, brought about by different pathophysiological neural triggers.

Cerebral causes and consequences of parkinsonian resting tremor: a tale of two circuits?

Tremor in Parkinson's disease has several mysterious features. Clinically, tremor is seen in only three out of four patients with Parkinson's disease, and tremor-dominant patients generally follow a more benign disease course than non-tremor patients. Pathophysiologically, tremor is linked to altered activity in not one, but two distinct circuits: the basal ganglia, which are primarily affected by dopamine depletion in Parkinson's disease, and the cerebello-thalamo-cortical circuit, which is also involved in many other tremors. The purpose of this review is to integrate these clinical and pathophysiological features of tremor in Parkinson's disease. We first describe clinical and pathological differences between tremor-dominant and non-tremor Parkinson's disease subtypes, and then summarize recent studies on the pathophysiology of tremor. We also discuss a newly proposed ‘dimmer-switch model’ that explains tremor as resulting from the combined actions of two circuits: the basal ganglia that trigger tremor episodes and the cerebello-thalamo-cortical circuit that produces the tremor. Finally, we address several important open questions: why resting tremor stops during voluntary movements, why it has a variable response to dopaminergic treatment, why it indicates a benign Parkinson's disease subtype and why its expression decreases with disease progression.

Demand driven deep brain stimulation: regimes and autoregressive hidden Markov implementation

Deep brain stimulation is an increasingly prevalent surgical option in the treatment of a multitude of neurological conditions, most notably Parkinson's disease. The development of a neurofeedback device is driven primarily by stimulator habituation, surgical risk factors, the cost of battery replacement, and reported neuropsychiatric side-effects under prolonged chronic administration. Here we present two distinct regimes for stimulation delivery in chronic and acute symptomatic conditions, presented in the context of Parkinsonian bradykinesias and tremor. Implementation strategies are discussed with a focus on vector-autoregressive hidden Markov models for tremor prediction. Detection of simple motor actions versus tremor are compared in a preliminary performance analysis.

Data-driven approach to the estimation of connectivity and time delays in the coupling of interacting neuronal subsystems

One of the challenges in neuroscience is the detection of directionality between signals reflecting neural activity. To reveal the directionality of coupling and time delays between interacting multi-scale signals, we use a combination of a data-driven technique called empirical mode decomposition (EMD) and partial directed coherence (PDC) together with the instantaneous causality test (ICT). EMD is used to separate multiple processes associated with different frequency bands, while PDC and ICT allow to explore directionality and characteristic time delays, respectively. We computationally validate our approach for the cases of both stochastic and chaotic oscillatory systems with different types of coupling. Moreover, we apply our approach to the analysis of the connectivity in different frequency bands between local field potentials (LFPs) bilaterally recorded from the left and right of subthalamic nucleus (STN) in patients with Parkinson's disease (PD). We reveal a bidirectional coupling between the left and right STN in the beta-band (10-30 Hz) for an akinetic PD patient and in the tremor band (3-5 Hz) for a tremor-dominant PD patient. We detect a short time delay, most probably reflecting the inter-hemispheric transmission time. Additionally, in both patients we observe a long time delay of approximately a mean period of the beta-band activity in the akinetic PD patient or the tremor band activity in the tremor-dominant PD patient. These long delays may emerge in subcortico-thalamic loops or longer pathways, comprising reflex loops, respectively. We show that the replacement of EMD by conventional bandpass filtering complicates the detection of directionality and leads to a spurious detection of time delays.