Clinical implications of local field potentials for understanding and treating movement disorders

Subthalamic nucleus local field potential stability in patients with Parkinson's disease

BACKGROUND

Despite the large body of work on local field potentials (LFPs), a measure of oscillatory activity in patients with Parkinson's disease (PD), the longitudinal evolution of LFPs is less explored.

OBJECTIVE

To determine LFP fluctuations collected in clinical settings in patients with PD and STN deep brain stimulation (DBS).

METHODS

Twenty-two STN-DBS patients (age: 67.6 ± 8.3 years; 9 females; disease duration: 10.3 ± 4.5 years) completed bilateral LFP recordings over three visits in the OFF-stimulation setting. Peak and band power measures were calculated from each recording.

RESULTS

After bilateral LFP recordings, at least one peak was detected in 18 (81.8%), 20 (90.9%), and 22 (100%) patients at visit 1, 2, and 3, respectively. No significant differences were seen in primary peak amplitude (F = 2.91, p = 0.060) over time. Amplitude of the second largest peak (F = 5.49, p = 0.006) and low-beta (F = 6.89, p = 0.002), high-beta (F = 13.23, p < 0.001), and gamma (F = 12.71, p < 0.001) band power demonstrated a significant effect of time. Post hoc comparisons determined low-beta power (Visit 1-Visit 2: t = 3.59, p = 0.002; Visit 1-Visit 3: t = 2.61, p = 0.031), high-beta (Visit 1-Visit 2: t = 4.64, p < 0.001; Visit 1-Visit 3: t = 4.23, p < 0.001) and gamma band power (Visit 1-Visit 2: t = 4.65, p < 0.001; Visit 1-Visit 3: t = 4.00, p < 0.001) were significantly increased from visit 1 recordings to both follow-up visits.

CONCLUSION

Our results provide substantial evidence that LFP can reliably be detected across multiple real-world clinical visits in patients with STN-DBS for PD. Moreover, it provides insights on the evolution of these LFPs.

Spinal Cord Stimulation Modulates Rat Cortico-Basal Ganglia Locomotor Circuit

OBJECTIVE

The cortico-basal ganglia circuit is crucial to understanding locomotor behavior and movement disorders. Spinal cord stimulation modulates that circuit, which is a promising approach to restoring motor functions. However, the effects of electrical spinal cord stimulation in the healthy brain motor circuit in pre- and postgait are poorly understood. Thus, this report aims to evaluate, through electrophysiological analyses, the dynamic spectral features of motor networks underlying locomotor initiation with spinal cord stimulation.

MATERIALS AND METHODS

Wistar male rats underwent spinal cord stimulation (current 30-150 μA, frequency 100, 333, and 500 Hz) with the electrophysiological recording of the caudate and putamen nuclei, primary and secondary motor cortices, and primary somatosensory cortex. Video tracking recorded treadmill locomotion and extracted the motor planning and gait initiation.

RESULTS

Spectral analysis of segments of gait initiation (pre- and postgait), with stimulation off, showed increased low-frequency activity. Postgait initiation showed increased alpha and beta rhythms and decreased delta rhythm with the stimulation off. Overall, the stimulation frequencies reduced alpha and beta rhythms in all brain areas during movement initiation. Regarding movement planning, such an effect was observed in the sensorimotor area, comprising the delta and alpha rhythms.

CONCLUSION

This study showed a short-term effect of spinal cord stimulation on the brain areas of the motor circuit, suggesting possible facilitation of movement planning and starting through neuromodulation. Thus, the electrophysiological characterization of this study may contribute to understanding basal ganglia networks and developing new approaches to treat movement disorders in the gait initiation phase.

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

Physiology of dystonia: Human studies

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

Localization of deep brain stimulation trajectories via automatic mapping of microelectrode recordings to MRI

Objective. Suboptimal electrode placement during subthalamic nucleus deep brain stimulation (STN DBS) surgery may arise from several sources, including frame-based targeting errors and intraoperative brain shift. We present a computer algorithm that can accurately localize intraoperative microelectrode recording (MER) tracks on preoperative magnetic resonance imaging (MRI) in real-time, thereby predicting deviation between the surgical plan and the MER trajectories.Approach. Random forest (RF) modeling was used to derive a statistical relationship between electrophysiological features on intraoperative MER and voxel intensity on preoperative T2-weighted MR imaging. This model was integrated into a larger algorithm that can automatically localize intraoperative MER recording tracks on preoperative MRI in real-time. To verify accuracy, targeting error of both the planned intraoperative trajectory ('planned') and the algorithm-derived trajectory ('calculated') was estimated by measuring deviation from the final DBS lead location on postoperative high-resolution computed tomography ('actual').Main results. MR imaging and MERs were obtained from 24 STN DBS implant trajectories. The cross-validated RF model could accurately distinguish between gray and white matter regions along MER trajectories (AUC 0.84). When applying this model within the localization algorithm, thecalculatedMER trajectory estimate was found to be significantly closer to theactualDBS lead when compared to theplannedtrajectory recorded during surgery (1.04 mm vs 1.52 mm deviation,p< 0.002), with improvement shown in 19/24 cases (79%). When applying the algorithm to simulated DBS trajectory plans with randomized targeting error, up to 4 mm of error could be resolved to <2 mm on average (p< 0.0001).Significance. This work presents an automated system for intraoperative localization of electrodes during STN DBS surgery. This neuroengineering solution may enhance the accuracy of electrode position estimation, particularly in cases where high-resolution intraoperative imaging is not available.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Deep brain stimulation of the ventrointermediate nucleus of the thalamus to treat essential tremor improves motor sequence learning

The network of brain structures engaged in motor sequence learning comprises the same structures as those involved in tremor, including basal ganglia, cerebellum, thalamus, and motor cortex. Deep brain stimulation (DBS) of the ventrointermediate nucleus of the thalamus (VIM) reduces tremor, but the effects on motor sequence learning are unknown. We investigated whether VIM stimulation has an impact on motor sequence learning and hypothesized that stimulation effects depend on the laterality of electrode location. Twenty patients (age: 38-81 years; 12 female) with VIM electrodes implanted to treat essential tremor (ET) successfully performed a serial reaction time task, varying whether the stimuli followed a repeating pattern or were selected at random, during which VIM-DBS was either on or off. Analyses of variance were applied to evaluate motor sequence learning performance according to reaction times (RTs) and accuracy. An interaction was observed between whether the sequence was repeated or random and whether VIM-DBS was on or off (F[1,18] = 7.89, p = .012). Motor sequence learning, reflected by reduced RTs for repeated sequences, was greater with DBS on than off (T[19] = 2.34, p = .031). Stimulation location correlated with the degree of motor learning, with greater motor learning when stimulation targeted the lateral VIM (n = 23, ρ = 0.46; p = .027). These results demonstrate the beneficial effects of VIM-DBS on motor sequence learning in ET patients, particularly with lateral VIM electrode location, and provide evidence for a role for the VIM in motor sequence learning.

Clinically-derived oscillatory biomarker predicts optimal subthalamic stimulation for Parkinson's disease

OBJECTIVE

Choosing the optimal electrode trajectory, stimulation location, and stimulation amplitude in subthalamic nucleus deep brain stimulation (STN DBS) for Parkinson's disease (PD) remains a time-consuming empirical effort. In this retrospective study, we derive a data-driven electrophysiological biomarker that predicts clinical DBS location and parameters, and we consolidate this information into a quantitative score that may facilitate an objective approach to STN DBS surgery and programming.

APPROACH

Random-forest feature selection was applied to a dataset of 1046 microelectrode recordings sites across 20 DBS implant trajectories to identify features of oscillatory activity that predict clinically programmed volumes of tissue activation (VTA). A cross-validated classifier was used to retrospectively predict VTA regions from these features. Spatial convolution of probabilistic classifier outputs along MER trajectories produced a biomarker score that reflects the probability of localization within a clinically optimized VTA.

MAIN RESULTS

Biomarker scores peaked within the VTA region and were significantly correlated with percent improvement in postoperative motor symptoms (MDS-UPRDS Part III, R = 0.61, p = 0.004). Notably, the length of STN, a common criterion for trajectory selection, did not show similar correlation (R = -0.31, p = 0.18). These findings suggest that biomarker-based trajectory selection and programming may improve motor outcomes by 9 ± 3 percentage points (p = 0.047) in this dataset.

SIGNIFICANCE

A clinically defined electrophysiological biomarker not only predicts VTA size and location but also correlates well with motor outcomes. Use of this biomarker for trajectory selection and initial stimulation may potentially simplify STN DBS surgery and programming.

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.

Effects of dexmedetomidine on subthalamic local field potentials in Parkinson's disease

Background

Dexmedetomidine is frequently used for sedation during deep brain stimulator implantation in patients with Parkinson's disease, but its effect on subthalamic nucleus activity is not well known. The aim of this study was to quantify the effect of increasing doses of dexmedetomidine in this population.

Methods

Controlled clinical trial assessing changes in subthalamic activity with increasing doses of dexmedetomidine (from 0.2 to 0.6 μg kg⁻¹ h⁻¹) in a non-operating theatre setting. We recorded local field potentials in 12 patients with Parkinson's disease with bilateral deep brain stimulators (24 nuclei) and compared basal activity in the nuclei of each patient and activity recorded with different doses. Plasma levels of dexmedetomidine were obtained and correlated with the dose administered.

Results

With dexmedetomidine infusion, patients became clinically sedated, and at higher doses (0.5–0.6 μg kg⁻¹ h⁻¹) a significant decrease in the characteristic Parkinsonian subthalamic activity was observed (P<0.05 in beta activity). All subjects awoke to external stimulus over a median of 1 (range: 0–9) min, showing full restoration of subthalamic activity. Dexmedetomidine dose administered and plasma levels showed a positive correlation (repeated measures correlation coefficient=0.504; P<0.001).

Conclusions

Patients needing some degree of sedation throughout subthalamic deep brain stimulator implantation for Parkinson's disease can probably receive dexmedetomidine up to 0.6 μg kg⁻¹ h⁻¹ without significant alteration of their characteristic subthalamic activity. If patients achieve a ‘sedated’ state, subthalamic activity decreases, but they can be easily awakened with a non-pharmacological external stimulus and recover baseline subthalamic activity patterns in less than 10 min.

Clinical trial registration

EudraCT 2016-002680-34; NCT-02982512.

Gamma frequencies as a predictor for the accomplishment of a motor task guided through the action observation network

BACKGROUND

Action observation describes a concept where the subsequent motor behavior of an individual can be modulated though observing an action. This occurs through the activation of neurons in the action observation network, acting on a variety of motor learning processes. This network has been proven highly useful in the rehabilitation of patients with acquired brain injury, placing "action observation" as one of the most effective techniques for motor recovery in physical neurorehabilitation.

OBJECTIVE

The aim of this paper is to define an EEG marker for motor learning, guided through observation.

METHODS

Healthy subjects (n = 41) participated voluntarily for this research. They were asked to repeat an unknown motor behavior, immediately after observing a video. During the observation, EEG raw signals where collected with a portable EEG and the results were later compared with success and fail on repeating the motor procedure. The comparison was then analyzed with the Mann-Whitney U test for non-parametrical data, with a confidence interval of 95%.

RESULTS

A significant relation between motor performance and neural activity was found for Alpha (p = 0,0149) and Gamma (0,0005) oscillatory patterns.

CONCLUSION

Gamma oscillations with frequencies between 41 and 49,75 Hz, seem to be an adequate EEG marker for motor performance guided through the action observation network. The technology used for this paper is easy to use, low-cost and presents valid measurements for the recommended oscillatory frequencies, implying a possible use on rehabilitation, by collecting data in real-time during therapeutic interventions and assessments.

Device profile of the percept PC deep brain stimulation system for the treatment of Parkinson's disease and related disorders

INTRODUCTION

Several software and hardware advances in the field of deep brain stimulation (DBS) have been realized in recent years and devices from three manufacturers are available. The Percept™ PC platform (Medtronic, Inc.) enables brain sensing, the latest innovation. Clinicians should be familiar with the differences in devices, and with the latest technologies to deliver optimized patient care.Areas covered: In this device profile, the sensing capabilities of the Percept™ PC platform are described, and the system capabilities are differentiated from other available platforms. The development of the preceding Activa™ PC+S research platform, an investigational device to simultaneously sense brain signals and provide therapeutic stimulation, is provided to place Percept™ PC in the appropriate context.Expert opinion: Percept™ PC offers unique sensing and diary functions as a means to refine therapeutic stimulation, track symptoms and correlate them to neurophysiologic characteristics. Additional features enhance the patient experience with DBS, including 3 T magnetic resonance imaging compatibility, wireless telemetry, a smaller and thinner battery profile, and increased battery longevity. Future work will be needed to illustrate the clinical utility and added value of using sensing to optimize DBS therapy. Patients implanted with Percept™ PC will have ready access to future technology developments.

Postoperative Externalization of Deep Brain Stimulation Leads Does Not Increase Infection Risk

OBJECTIVES

Externalization of deep brain stimulation (DBS) leads is performed to allow electrophysiological recording from implanted electrodes as well as assessment of clinical response to trial stimulation before implantable pulse generator (IPG) insertion. Hypothetically, lead externalization provides a route for inoculation and subsequent infection of hardware, though this has not been established definitively in the literature. We sought to determine if lead externalization affects the risk of infection in DBS surgery.

MATERIALS AND METHODS

We present our center's experience of lead externalization and surgical site infection (SSI) in DBS surgery for movement disorders. Patients were divided into two cohorts: one in which leads were not externalized and IPGs were implanted at the time of electrode insertion, and one in which leads were externalized for six days while patients underwent electrophysiological recording from DBS electrodes for research. We compare baseline characteristics of these two cohorts and their SSI rates.

RESULTS

Infective complications were experienced by 3/82 (3.7%) patients overall with one (1.2%) requiring complete hardware removal. These occurred in 1/36 (2.7%) in the externalized cohort and 2/46 (4.3%) in the nonexternalized cohort. The incidence of infection between the two cohorts was not significantly different (p = 1, two-tailed Fisher's exact test). This lack of significant difference persisted when baseline variation between the cohorts in age, hardware manufacturer, and indication for DBS were corrected by excluding patients implanted for dystonia, none of whom underwent externalization. We present and discuss in detail each of the three cases of infection.

CONCLUSIONS

Our data suggest that externalization of leads does not increase the risk of infective complications in DBS surgery. Lead externalization is a safe procedure which can provide a substrate for unique neurophysiological studies to advance knowledge and therapy of disorders treated with DBS.

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.

Randomized, Double-Blind Assessment of LFP Versus SUA Guidance in STN-DBS Lead Implantation: A Pilot Study

Background: The efficacy of deep brain stimulation (DBS) therapy in Parkinson's disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients' symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent. Methods: Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline. Results: We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, n = 3 STNs). The selected tracks were characterized by higher activity in beta (11-32 Hz) and high-frequency (200-400 Hz) bands (p < 0.01) of LFPs and stronger non-linear coupling between these bands (p < 0.05). Conclusion: Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.

Electrophysiology and Structural Connectivity of the Posterior Hypothalamic Region: Much to Learn From a Rare Indication of Deep Brain Stimulation

Cluster headache (CH) is among the most common and debilitating autonomic cephalalgias. We characterize clinical outcomes of deep brain stimulation (DBS) to the posterior hypothalamic region through a novel analysis of the electrophysiological topography and tractography-based structural connectivity. The left posterior hypothalamus was targeted ipsilateral to the refractory CH symptoms. Intraoperatively, field potentials were captured in 1 mm depth increments. Whole-brain probabilistic tractography was conducted to assess the structural connectivity of the estimated volume of activated tissue (VAT) associated with therapeutic response. Stimulation of the posterior hypothalamic region led to the resolution of CH symptoms, and this benefit has persisted for 1.5-years post-surgically. Active contacts were within the posterior hypothalamus and dorsoposterior border of the ventral anterior thalamus (VAp). Delta- (3 Hz) and alpha-band (8 Hz) powers increased and peaked with proximity to the posterior hypothalamus. In the posterior hypothalamus, the delta-band phase was coupled to beta-band amplitude, the latter of which has been shown to increase during CH attacks. Finally, we identified that the VAT encompassing these regions had a high proportion of streamlines of pain processing regions, including the insula, anterior cingulate gyrus, inferior parietal lobe, precentral gyrus, and the brainstem. Our unique case study of posterior hypothalamic region DBS supports durable efficacy and provides a platform using electrophysiological topography and structural connectivity, to improve mechanistic understanding of CH and this promising therapy.

Functional Use of Directional Local Field Potentials in the Subthalamic Nucleus Deep Brain Stimulation

Background

Directional deep brain stimulation (DBS) technology aims to address the limitations, such as stimulation-induced side effects, by delivering selective, focal modulation via segmented contacts. However, DBS programming becomes more complex and time-consuming for clinical feasibility. Local field potentials (LFPs) might serve a functional role in guiding clinical programming.

Objective

In this pilot study, we investigated the spectral dynamics of directional LFPs in subthalamic nucleus (STN) and their relationship to motor symptoms of Parkinson’s disease (PD).

Methods

We recorded intraoperative STN-LFPs from 8-contact leads (Infinity-6172, Abbott Laboratories, Illinois, United States) in 8 PD patients at rest. Directional LFPs were referenced to their common average and time-frequency analysis was computed using a modified Welch periodogram method. The beta band (13–35 Hz) features were extracted and their correlation to preoperative UPDRS-III scores were assessed.

Results

Normalized beta power (13–20 Hz) and normalized peak power (13–35 Hz) were found to be higher in anterior direction despite lack of statistical significance (p > 0.05). Results of the Spearman correlation analysis demonstrated positive trends with bradykinesia/rigidity in dorsoanterior direction (r = 0.659, p = 0.087) and with axial scores in the dorsomedial direction (r = 0.812, p = 0.072).

Conclusion

Given that testing all possible combinations of contact pairs and stimulation parameters is not feasible in a single clinic visit, spatio-spectral LFP dynamics obtained from intraoperative recordings might be used as an initial marker to select optimal contact(s).

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

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

Deep brain stimulation for Tourette's syndrome

Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by the presence of multiple motor and vocal tics. TS usually co-occurs with one or multiple psychiatric disorders. Although behavioral and pharmacological treatments for TS are available, some patients do not respond to the available treatments. For these patients, TS is a severe, chronic, and disabling disorder. In recent years, deep brain stimulation (DBS) of basal ganglia-thalamocortical networks has emerged as a promising intervention for refractory TS with or without psychiatric comorbidities. Three major challenges need to be addressed to move the field of DBS treatment for TS forward: (1) patient and DBS target selection, (2) ethical concerns with treating pediatric patients, and (3) DBS treatment optimization and improvement of individual patient outcomes (motor and phonic tics, as well as functioning and quality of life). The Tourette Association of America and the American Academy of Neurology have recently released their recommendations regarding surgical treatment for refractory TS. Here, we describe the challenges, advancements, and promises of the use of DBS in the treatment of TS. We summarize the results of clinical studies and discuss the ethical issues involved in treating pediatric patients. Our aim is to provide a better understanding of the feasibility, safety, selection process, and clinical effectiveness of DBS treatment for select cases of severe and medically intractable TS.

Tremor and myoclonus

Tremor and myoclonus are two common hyperkinetic movement disorders. Tremor is characterized by rhythmic oscillatory movements while myoclonic jerks are usually arrhythmic. Tremor can be classified into subtypes including the most common types: essential, enhanced physiological, and parkinsonian tremor. Myoclonus classification is based on its anatomic origin: cortical, subcortical, spinal, and peripheral myoclonus. The clinical presentations are unfortunately not always classic and electrophysiologic investigations can be helpful in making a phenotypic diagnosis. Video-polymyography is the main technique to (sub)classify the involuntary movements. In myoclonus, advanced electrophysiologic testing, such as back-averaging, coherence analysis, somatosensory-evoked potentials, and the C-reflex can be of additional value. Recent developments in tremor point toward a role for intermuscular coherence analysis to differentiate between tremor subtypes. Classification of the movement disorder based on clinical and electrophysiologic features is important, as it enables the search for an etiological diagnosis and guides tailored treatment.

Neural Circuit and Clinical Insights from Intraoperative Recordings During Deep Brain Stimulation Surgery

Observations using invasive neural recordings from patient populations undergoing neurosurgical interventions have led to critical breakthroughs in our understanding of human neural circuit function and malfunction. The opportunity to interact with patients during neurophysiological mapping allowed for early insights in functional localization to improve surgical outcomes, but has since expanded into exploring fundamental aspects of human cognition including reward processing, language, the storage and retrieval of memory, decision-making, as well as sensory and motor processing. The increasing use of chronic neuromodulation, via deep brain stimulation, for a spectrum of neurological and psychiatric conditions has in tandem led to increased opportunity for linking theories of cognitive processing and neural circuit function. Our purpose here is to motivate the neuroscience and neurosurgical community to capitalize on the opportunities that this next decade will bring. To this end, we will highlight recent studies that have successfully leveraged invasive recordings during deep brain stimulation surgery to advance our understanding of human cognition with an emphasis on reward processing, improving clinical outcomes, and informing advances in neuromodulatory interventions.

Five-Year Clinical Outcomes of Local versus General Anesthesia Deep Brain Stimulation for Parkinson's Disease

Background

Studies comparing long-term outcomes between general anesthesia (GA) and local anesthesia (LA) for STN-DBS in Parkinson's disease (PD) are lacking. Whether patients who received STN-DBS in GA could get the same benefit without compromising electrophysiological recording is debated.

Methods

We compared five-year outcomes for different anesthetic methods (GA vs LA) during STN-DBS for PD. Thirty-six consecutive PD patients with similar preoperative characteristics, including age, disease duration, and severity, underwent the same surgical procedures except the GA (n=22) group with inhalational anesthesia and LA (n=14) with local anesthesia during microelectrode recording and intraoperative macrostimulation test. Surgical outcome evaluations included Unified Parkinson's Disease Rating Scale (UPDRS), Mini-Mental Status Examinations, and the Beck Depression Inventory. Stimulation parameters and coordinates of STN targeting were also collected.

Results

Both groups attained similar benefits in UPDRS part III from STN-DBS (GA 43.2 ± 14.1% vs. LA 46.8 ± 13.8% decrease, p=0.45; DBS on/Med off vs. DBS off/Med off) and no difference in reduction of levodopa equivalent doses (GA 47.56 ± 18.98% vs. LA 51.37 ± 31.73%, p=0.51) at the five-year follow-up. In terms of amplitude, frequency, and pulse width, the stimulation parameters used for DBS were comparable, and the coordinates of preoperative targeting and postoperative electrode tip were similar between two groups. There was no difference in STN recording length as well. Significantly less number of MER tracts in GA was found (p=0.04). Adverse effects were similar in both groups.

Conclusions

Our study confirmed that STN localization with microelectrode recording and patient comfort could be achieved based on equal effectiveness and safety of STN-DBS under GA compared with LA.

Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson's disease

Although motor subtypes of Parkinson's disease (PD), such as tremor dominant (TD) and postural instability and gait difficulty (PIGD), have been defined based on symptoms since the mid-1990s, no underlying neural correlates of these clinical subtypes have yet been identified. Very limited data exist regarding the electrophysiological abnormalities within the subthalamic nucleus (STN) that likely accompany the symptom severity or the phenotype of PD. Here, we show that activity in subbands of local field potentials (LFPs) recorded with multiple microelectrodes from subterritories of STN provide distinguishing neurophysiological information about the motor subtypes of PD. We studied 24 patients with PD and found distinct patterns between TD (n = 13) and PIGD (n = 11) groups in high-frequency oscillations (HFOs) and their nonlinear interactions with beta band in the superior and inferior regions of the STN. Particularly, in the superior region of STN, the power of the slow HFO (sHFO) (200-260 Hz) and the coupling of its amplitude with beta-band phase were significantly stronger in the TD group. The inferior region of STN exhibited fast HFOs (fHFOs) (260-450 Hz), which have a significantly higher center frequency in the PIGD group. The cross-frequency coupling between fHFOs and beta band in the inferior region of STN was significantly stronger in the PIGD group. Our results indicate that the spatiospectral dynamics of STN-LFPs can be used as an objective method to distinguish these two motor subtypes of PD. These observations might lead to the development of sensing and stimulation strategies targeting the subterritories of STN for the personalization of deep-brain stimulation (DBS).

Removing deep brain stimulation artifacts from the electroencephalogram: Issues, recommendations and an open-source toolbox

A major question for deep brain stimulation (DBS) research is understanding how DBS of one target area modulates activity in different parts of the brain. EEG gives privileged access to brain dynamics, but its use with implanted patients is limited since DBS adds significant high-amplitude electrical artifacts that can completely obscure neural activity measured using EEG. Here, we systematically review and discuss the methods available for removing DBS artifacts. These include simple techniques such as oversampling, antialiasing analog filtering and digital low-pass filtering, which are necessary but typically not sufficient to fully remove DBS artifacts when each is used in isolation. We also cover more advanced methods, including techniques tracking outliers in the frequency-domain, which can be effective, but are rarely used. The reason for that is twofold: First, it requires advanced skills in signal processing since no user friendly tool for removing DBS artifacts is currently available. Second, it involves fine-tuning to avoid over-aggressive filtering. We highlight an open-source toolbox incorporating most artifact removal methods, allowing users to combine different strategies.

Semi-automated application for estimating subthalamic nucleus boundaries and optimal target selection for deep brain stimulation implantation surgery

OBJECTIVEDeep brain stimulation (DBS) of the subthalamic nucleus (STN) has become standard care for the surgical treatment of Parkinson's disease (PD). Reliable interpretation of microelectrode recording (MER) data, used to guide DBS implantation surgery, requires expert electrophysiological evaluation. Recent efforts have endeavored to use electrophysiological signals for automatic detection of relevant brain structures and optimal implant target location.The authors conducted an observational case-control study to evaluate a software package implemented on an electrophysiological recording system to provide online objective estimates for entry into and exit from the STN. In addition, they evaluated the accuracy of the software in selecting electrode track and depth for DBS implantation into STN, which relied on detecting changes in spectrum activity.METHODSData were retrospectively collected from 105 MER-guided STN-DBS surgeries (4 experienced neurosurgeons; 3 sites), in which estimates for entry into and exit from the STN, DBS track selection, and implant depth were compared post hoc between those determined by the software and those determined by the implanting neurosurgeon/neurophysiologist during surgery.RESULTSThis multicenter study revealed submillimetric agreement between surgeon/neurophysiologist and software for entry into and exit out of the STN as well as optimal DBS implant depth.CONCLUSIONSThe results of this study demonstrate that the software can reliably and accurately estimate entry into and exit from the STN and select the track corresponding to ultimate DBS implantation.

Improving the Standard for Deep Brain Stimulation Therapy: Target Structures and Feedback Signals for Adaptive Stimulation. Current Perspectives and Future Directions

Deep brain stimulation (DBS) is an established therapeutic option for the treatment of various neurological disorders and has been used successfully in movement disorders for over 25 years. However, the standard stimulation schemes have not changed substantially. Two major points of interest for the further development of DBS are target-structures and novel adaptive stimulation techniques integrating feedback signals. We describe recent research results on target structures and on neural and behavioural feedback signals for adaptive deep brain stimulation (aDBS), as well as outline future directions.

Sleep patterns in Parkinson's disease: direct recordings from the subthalamic nucleus

Sleep is a fundamental homeostatic process, and disorders of sleep can greatly affect quality of life. Parkinson's disease (PD) is highly comorbid for a spectrum of sleep disorders and deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been reported to improve sleep architecture in PD. We studied local field potential (LFP) recordings in PD subjects undergoing STN-DBS over the course of a full-night's sleep. We examined the changes in oscillatory activity recorded from STN between ultradian sleep states to determine whether sleep-stage dependent spectral patterns might reflect underlying dysfunction. For this study, PD (n=10) subjects were assessed with concurrent polysomnography and LFP recordings from the DBS electrodes, for an average of 7.5 hours in 'off' dopaminergic medication state. Across subjects, we found conserved spectral patterns among the canonical frequency bands (delta 0-3 Hz, theta 3-7 Hz, alpha 7-13 Hz, beta 13-30 Hz, gamma 30-90 Hz and high frequency 90-350 Hz) that were associated with specific sleep cycles: delta (0-3 Hz) activity during non-rapid eye movement (NREM) associated stages was greater than during Awake, whereas beta (13-30 Hz) activity during NREM states was lower than Awake and rapid eye movement (REM). In addition, all frequency bands were significantly different between NREM states and REM. However, each individual subject exhibited a unique mosaic of spectral interrelationships between frequency bands. Our work suggests that LFP recordings from human STN differentiate between sleep cycle states, and sleep-state specific spectral mosaics may provide insight into mechanisms underlying sleep pathophysiology.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson's disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about 0.729 ± 0.16 for decoding movement from the resting state and about 0.671 ± 0.14 for decoding left and right visually cued movements.

The brain during free movement - What can we learn from the animal model

Animals, just like humans, can freely move. They do so for various important reasons, such as finding food and escaping predators. Observing these behaviors can inform us about the underlying cognitive processes. In addition, while humans can convey complicated information easily through speaking, animals need to move their bodies to communicate. This has prompted many creative solutions by animal neuroscientists to enable studying the brain during movement. In this review, we first summarize how animal researchers record from the brain while an animal is moving, by describing the most common neural recording techniques in animals and how they were adapted to record during movement. We further discuss the challenge of controlling or monitoring sensory input during free movement. However, not only is free movement a necessity to reflect the outcome of certain internal cognitive processes in animals, it is also a fascinating field of research since certain crucial behavioral patterns can only be observed and studied during free movement. Therefore, in a second part of the review, we focus on some key findings in animal research that specifically address the interaction between free movement and brain activity. First, focusing on walking as a fundamental form of free movement, we discuss how important such intentional movements are for understanding processes as diverse as spatial navigation, active sensing, and complex motor planning. Second, we propose the idea of regarding free movement as the expression of a behavioral state. This view can help to understand the general influence of movement on brain function. Together, the technological advancements towards recording from the brain during movement, and the scientific questions asked about the brain engaged in movement, make animal research highly valuable to research into the human "moving brain".

Effect of Dexmedetomidine and Propofol on Basal Ganglia Activity in Parkinson Disease: A Controlled Clinical Trial

BACKGROUND

Deep brain stimulation electrodes can record oscillatory activity from deep brain structures, known as local field potentials. The authors' objective was to evaluate and quantify the effects of dexmedetomidine (0.2 μg·kg·h) on local field potentials in patients with Parkinson disease undergoing deep brain stimulation surgery compared with control recording (primary outcome), as well as the effect of propofol at different estimated peak effect site concentrations (0.5, 1.0, 1.5, 2.0, and 2.5 μg/ml) from control recording.

METHODS

A nonrandomized, nonblinded controlled clinical trial was carried out to assess the change in local field potentials activity over time in 10 patients with Parkinson disease who underwent deep brain stimulation placement surgery (18 subthalamic nuclei). The relationship was assessed between the activity in nuclei in the same patient at a given time and repeated measures from the same nucleus over time.

RESULTS

No significant difference was observed between the relative beta power of local field potentials in dexmedetomidine and control recordings (-7.7; 95% CI, -18.9 to 7.6). By contrast, there was a significant decline of 12.7% (95% CI, -21.3 to -4.7) in the relative beta power of the local field potentials for each increment in the estimated peak propofol concentrations at the effect site relative to the control recordings.

CONCLUSIONS

Dexmedetomidine (0.2 μg·kg·h) did not show effect on local field potentials compared with control recording. A significant deep brain activity decline from control recording was observed with incremental doses of propofol.

Adaptive Deep Brain Stimulation for Movement Disorders: The Long Road to Clinical Therapy

Continuous high-frequency DBS is an established treatment for essential tremor and Parkinson's disease. Current developments focus on trying to widen the therapeutic window of DBS. Adaptive DBS (aDBS), where stimulation is dynamically controlled by feedback from biomarkers of pathological brain circuit activity, is one such development. Relevant biomarkers may be central, such as local field potential activity, or peripheral, such as inertial tremor data. Moreover, stimulation may be directed by the amplitude or the phase (timing) of the biomarker signal. In this review, we evaluate existing aDBS studies as proof-of-principle, discuss their limitations, most of which stem from their acute nature, and propose what is needed to take aDBS into a chronic setting. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Use of intraoperative local field potential spectral analysis to differentiate basal ganglia structures in Parkinson's disease patients

Identification of brain structures traversed during implantation of deep brain-stimulating (DBS) electrodes into the subthalamic nucleus (STN-DBS) for the treatment of Parkinson's disease (PD) frequently relies on subjective correspondence between kinesthetic response and multiunit activity. However, recent work suggests that local field potentials (LFP) could be used as a more robust signal to objectively differentiate subcortical structures. The goal of this study was to analyze the spectral properties of LFP collected during STN-DBS in order to objectively identify commonly traversed brain regions and improve our understanding of aberrant oscillations in the PD-related pathophysiological cortico-basal ganglia network. In 21 PD patients, LFP were collected and analyzed during STN-DBS implantation surgery. Spectral power for delta-, theta-, alpha-, low-beta-, and high-beta-frequency bands was assessed at multiple depths throughout the subcortical structures traversed on the trajectory to the ventral border of STN. Similar to previous findings, beta-band oscillations had an increased magnitude within the borders of the motor-related area of STN, however, across several subjects, we also observed increased high-beta magnitude within the borders of thalamus. Comparing across all patients using relative power, we observed a gradual increase in the magnitude of both low- and high-beta-frequency bands as the electrode descended from striatum to STN. These results were also compared with frequency bands below beta, and similar trends were observed. Our results suggest that LFP signals recorded during the implantation of a DBS electrode evince distinct oscillatory signatures that distinguish subcortical structures.

LFP Oscillations in the Mesencephalic Locomotor Region during Voluntary Locomotion

Oscillatory rhythms in local field potentials (LFPs) are thought to coherently bind cooperating neuronal ensembles to produce behaviors, including locomotion. LFPs recorded from sites that trigger locomotion have been used as a basis for identification of appropriate targets for deep brain stimulation (DBS) to enhance locomotor recovery in patients with gait disorders. Theta band activity (6–12 Hz) is associated with locomotor activity in locomotion-inducing sites in the hypothalamus and in the hippocampus, but the LFPs that occur in the functionally defined mesencephalic locomotor region (MLR) during locomotion have not been determined. Here we record the oscillatory activity during treadmill locomotion in MLR sites effective for inducing locomotion with electrical stimulation in rats. The results show the presence of oscillatory theta rhythms in the LFPs recorded from the most effective MLR stimulus sites (at threshold ≤60 μA). Theta activity increased at the onset of locomotion, and its power was correlated with the speed of locomotion. In animals with higher thresholds (>60 μA), the correlation between locomotor speed and theta LFP oscillations was less robust. Changes in the gamma band (previously recorded in vitro in the pedunculopontine nucleus (PPN), thought to be a part of the MLR) were relatively small. Controlled locomotion was best achieved at 10–20 Hz frequencies of MLR stimulation. Our results indicate that theta and not delta or gamma band oscillation is a suitable biomarker for identifying the functional MLR sites.

REM sleep behaviour disorder: prodromal and mechanistic insights for Parkinson's disease

Rapid eye movement (REM) sleep behaviour disorder (RBD) is characterised by complex motor enactment of dreams and is a potential prodromal marker of Parkinson's disease (PD). Of note, patients with PD observed during RBD episodes exhibit improved motor function, relative to baseline states during wake periods. Here, we review recent epidemiological and mechanistic findings supporting the prodromal value of RBD for PD, incorporating clinical and electrophysiological studies. Explanations for the improved motor function during RBD episodes are evaluated in light of recent publications. In addition, we present preliminary findings describing changes in the activity of the basal ganglia across the sleep-wake cycle that contribute to our understanding of RBD.

Long-Term Task- and Dopamine-Dependent Dynamics of Subthalamic Local Field Potentials in Parkinson's Disease

Subthalamic nucleus (STN) local field potentials (LFP) are neural signals that have been shown to reveal motor and language behavior, as well as pathological parkinsonian states. We use a research-grade implantable neurostimulator (INS) with data collection capabilities to record STN-LFP outside the operating room to determine the reliability of the signals over time and assess their dynamics with respect to behavior and dopaminergic medication. Seven subjects were implanted with the recording augmented deep brain stimulation (DBS) system, and bilateral STN-LFP recordings were collected in the clinic over twelve months. Subjects were cued to perform voluntary motor and language behaviors in on and off medication states. The STN-LFP recorded with the INS demonstrated behavior-modulated desynchronization of beta frequency (13-30 Hz) and synchronization of low gamma frequency (35-70 Hz) oscillations. Dopaminergic medication did not diminish the relative beta frequency oscillatory desynchronization with movement. However, movement-related gamma frequency oscillatory synchronization was only observed in the medication on state. We observed significant inter-subject variability, but observed consistent STN-LFP activity across recording systems and over a one-year period for each subject. These findings demonstrate that an INS system can provide robust STN-LFP recordings in ambulatory patients, allowing for these signals to be recorded in settings that better represent natural environments in which patients are in a variety of medication states.

GPi Oscillatory Activity Differentiates Tics from the Resting State, Voluntary Movements, and the Unmedicated Parkinsonian State

Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic.

Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest.

Results: In all PD patients, we noted excessive beta band activity (13–30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4–7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200–400 Hz) and gamma band (35–200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5–10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects.

Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5–10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present.

A Method for Removal of Deep Brain Stimulation Artifact From Local Field Potentials

This paper presents a signal processing method for the electrophysiology simultaneously recorded during deep brain stimulation (DBS) as a research tool. Regarding the local field potential (LFP) signals recorded during stimulation, a novel method was proposed for removal of stimulation artifacts caused by the much stronger stimulating pulse compared to typical LFP. This artifact suppression method was tested and evaluated in an in vitro situation. The results indicate that the stimulation artifacts are well suppressed by this method. Secondly, this method was tested in vivo in Parkinson's disease (PD) patients. It was used to process the LFP signals recorded intraoperatively from PD patients to preliminarily explore the quantitative dependencies of beta band synchronization variations in the subthalamic nucleus (STNs) on the applied DBS parameters, including stimulation voltage, frequency and pulse width. The results confirm that DBS therapy can suppress excessive beta frequency activity and that the degree of attenuation increases with increasing DBS voltage within a range of 1-3 V and increasing DBS frequency within a range of 60-120 Hz. The proposed artifact suppression method provides technical support for exploring the direct effect of electrical stimulation on the brain activities.

Clinical Outcome and Characterization of Local Field Potentials in Holmes Tremor Treated with Pallidal Deep Brain Stimulation

BACKGROUND

Holmes tremor (HT) is an irregular, low-frequency rest tremor associated with prominent action and postural tremors. Currently, the most effective stereotactic target and neurophysiologic characterization of HT, specifically local field potentials (LFPs) are uncertain. We present the outcome, intraoperative neurophysiologic analysis with characterization of LFPs in a patient managed with left globus pallidus interna deep brain stimulation (Gpi DBS).

CASE REPORT

A 24-year-old male underwent left Gpi DBS for medically refractory HT. LFPs demonstrated highest powers in the delta range in Gpi. At the 6-month follow-up, a 90% reduction in tremor was observed.

DISCUSSION

Pallidal DBS should be considered as an alternative target for management of refractory HT. LFP demonstrated neuronal activity associated with higher power in the delta region, similarly seen in patients with generalized dystonia.

Prediction of STN-DBS Electrode Implantation Track in Parkinson's Disease by Using Local Field Potentials

Optimal electrophysiological placement of the DBS electrode may lead to better long term clinical outcomes. Inter-subject anatomical variability and limitations in stereotaxic neuroimaging increase the complexity of physiological mapping performed in the operating room. Microelectrode single unit neuronal recording remains the most common intraoperative mapping technique, but requires significant expertise and is fraught by potential technical difficulties including robust measurement of the signal. In contrast, local field potentials (LFPs), owing to their oscillatory and robust nature and being more correlated with the disease symptoms, can overcome these technical issues. Therefore, we hypothesized that multiple spectral features extracted from microelectrode-recorded LFPs could be used to automate the identification of the optimal track and the STN localization. In this regard, we recorded LFPs from microelectrodes in three tracks from 22 patients during DBS electrode implantation surgery at different depths and aimed to predict the track selected by the neurosurgeon based on the interpretation of single unit recordings. A least mean square (LMS) algorithm was used to de-correlate LFPs in each track, in order to remove common activity between channels and increase their spatial specificity. Subband power in the beta band (11–32 Hz) and high frequency range (200–450 Hz) were extracted from the de-correlated LFP data and used as features. A linear discriminant analysis (LDA) method was applied both for the localization of the dorsal border of STN and the prediction of the optimal track. By fusing the information from these low and high frequency bands, the dorsal border of STN was localized with a root mean square (RMS) error of 1.22 mm. The prediction accuracy for the optimal track was 80%. Individual beta band (11–32 Hz) and the range of high frequency oscillations (200–450 Hz) provided prediction accuracies of 72 and 68% respectively. The best prediction result obtained with monopolar LFP data was 68%. These results establish the initial evidence that LFPs can be strategically fused with computational intelligence in the operating room for STN localization and the selection of the track for chronic DBS electrode implantation.