Neuronal activity of the human subthalamic nucleus in the parkinsonian and nonparkinsonian state

Computational study of associations between the synaptic conductance of STN and GPe and the development of Parkinson's disease

There is evidence that the subthalamic nucleus (STN) and globus pallidus pars externa (GPe) involve in the development of Parkinson's disease, a neurodegenerative disorder characterized by motor and non-motor symptoms and loss of dopaminergic neurons in which the error index (EI) in firing patterns is widely used to address the related issues. Whether and how this interaction mechanism of STN and GPe affects EI in Parkinson's disease is uncertain. To account for this, we propose a kind of basal ganglia-thalamic network model associated with Parkinson's disease coupled with neurons, and investigate the effect of synaptic conductance of STN and GPe on EI in this network, as well as their internal relationship under EI as an index. The results show a relationship like a piecewise function between the error index and the slope of the state transition function of synaptic conductance from STN to GPe ( g snge ) and from GPe to STN ( g gesn ). And there is an approximate negative correlation between EI and g gesn . Increasing g snge and decreasing g gesn can improve the fidelity of thalamus information transmission and alleviate Parkinson's disease effectively. These obtained results can give some theoretical evidence that the abnormal synaptic releases of STN and GPe may be the symptoms of the development of Parkinson's disease, and further enrich the understanding of the pathogenesis and treatment mechanism of Parkinson's disease.

Subthalamic nucleus synchronization between beta band local field potential and single-unit activity in Parkinson's disease

Local field potential (LFP) oscillations in the beta band (13-30 Hz) in the subthalamic nucleus (STN) of Parkinson's disease patients have been implicated in disease severity and treatment response. The relationship between single-neuron activity in the STN and regional beta power changes remains unclear. We used spike-triggered average (STA) to assess beta synchronization in STN. Beta power and STA magnitude at the beta frequency range were compared in three conditions: STN versus other subcortical structures, dorsal versus ventral STN, and high versus low beta power STN recordings. Magnitude of STA-LFP was greater within the STN compared to extra-STN structures along the trajectory path, despite no difference in percentage of the total power. Within the STN, there was a higher percent beta power in dorsal compared to ventral STN but no difference in STA-LFP magnitude. Further refining the comparison to high versus low beta peak power recordings inside the STN to evaluate if single-unit activity synchronized more strongly with beta band activity in areas of high beta power resulted in a significantly higher STA magnitude for areas of high beta power. Overall, these results suggest that STN single units strongly synchronize to beta activity, particularly units in areas of high beta power.

Spontaneous blink-related beta power increase and theta phase reset in subthalamic nucleus of Parkinson patients during walking

OBJECTIVE

Both blinking and walking are altered in Parkinson's disease and both motor outputs have been shown to be linked in healthy subjects. Additionally, studies suggest an involvement of basal ganglia activity and striatal dopamine in blink generation. We investigated the role of the basal ganglia circuitry on spontaneous blinking and if this role is dependent on movement state and striatal dopamine.

METHODS

We analysed subthalamic nucleus (STN) activity in seven chronically implanted patients for deep brain stimulation (DBS) with respect to blinks and movement state (resting state and unperturbed walking). Neurophysiological recordings were combined with individual molecular brain imaging assessing the dopamine reuptake transporter (DAT) density for the left and right striatum separately.

RESULTS

We found a significantly higher blink rate during walking compared to resting. The blink rate during walking positively correlated with the DAT density of the left caudate nucleus. During walking only, spontaneous blinking was followed by an increase in the right STN beta power and a bilateral subthalamic phase reset in the low frequencies. The right STN blink-related beta power modulation correlated negatively with the DAT density of the contralateral putamen. The left STN blink-related beta power correlated with the DAT density of the putamen in the less dopamine-depleted hemisphere. Both correlations were specific to the walking condition and to beta power following a blink.

CONCLUSION

Our findings show that spontaneous blinking is related to striatal dopamine and has a frequency specific deployment in the STN. This correlation depends on the current movement state such as walking.

SIGNIFICANCE

This work indicates that subcortical activity following a motor event as well as the relationship between dopamine and motor events can be dependent on the motor state. Accordingly, disease related changes in brain activity should be assessed during natural movement.

Combining ultrasound and microelectrode recordings for postoperative localization of subthalamic electrodes in Parkinson's disease

OBJECTIVE

To assess transcranial sonography (TCS) as stand-alone tool and in combination with microelectrode recordings (MER) as a method for the postoperative localization of deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN).

METHODS

Individual dorsal and ventral boundaries of STN (n = 12) were determined on intraoperative MER. Postoperatively, a standardized TCS protocol was applied to measure medio-lateral, anterior-posterior and rostro-caudal electrode position using visualized reference structures (midline, substantia nigra). TCS and combined TCS-MER data were validated using fusion-imaging and clinical outcome data.

RESULTS

Test-retest reliability of standard TCS measures of electrode position was excellent. Computed tomography and TCS measures of distance between distal electrode contact and midline agreed well (Pearson correlation; r = 0.86; p < 0.001). Comparing our "gold standard" of rostro-caudal electrode localization relative to STN boundaries, i.e. combining MRI-based stereotaxy and MER data, with the combination of TCS and MER data, the measures differed by 0.32 ± 0.87 (range, -1.35 to 1.25) mm. Combined TCS-MER data identified the clinically preferred electrode contacts for STN-DBS with high accuracy (Coheńs kappa, 0.86).

CONCLUSIONS

Combined TCS-MER data allow for exact localization of STN-DBS electrodes.

SIGNIFICANCE

Our method provides a new option for monitoring of STN-DBS electrode location and guidance of DBS programming in Parkinson's disease.

Brain Networks Involved in Sensory Perception in Parkinson's Disease: A Scoping Review

Parkinson's Disease (PD) has historically been considered a disorder of motor dysfunction. However, a growing number of studies have demonstrated sensory abnormalities in PD across the modalities of proprioceptive, tactile, visual, auditory and temporal perception. A better understanding of these may inform future drug and neuromodulation therapy. We analysed these studies using a scoping review. In total, 101 studies comprising 2853 human participants (88 studies) and 125 animals (13 studies), published between 1982 and 2022, were included. These highlighted the importance of the basal ganglia in sensory perception across all modalities, with an additional role for the integration of multiple simultaneous sensation types. Numerous studies concluded that sensory abnormalities in PD result from increased noise in the basal ganglia and increased neuronal receptive field size. There is evidence that sensory changes in PD and impaired sensorimotor integration may contribute to motor abnormalities.

Intelligibility of speech in Parkinson's disease relies on anatomically segregated subthalamic beta oscillations

BACKGROUND

Speech impairment is commonly reported in Parkinson's disease and is not consistently improved by available therapies - including deep brain stimulation of the subthalamic nucleus (STN-DBS), which can worsen communication performance in some patients. Improving the outcome of STN-DBS on speech is difficult due to our incomplete understanding of the contribution of the STN to fluent speaking.

OBJECTIVE

To assess the relationship between subthalamic neural activity and speech production and intelligibility.

METHODS

We investigated bilateral STN local field potentials (LFPs) in nine parkinsonian patients chronically implanted with DBS during overt reading. LFP spectral features were correlated with clinical scores and measures of speech intelligibility.

RESULTS

Overt reading was associated with increased beta-low ([1220) Hz) power in the left STN, whereas speech intelligibility correlated positively with beta-high ([2030) Hz) power in the right STN.

CONCLUSION

We identified separate contributions from frequency and brain lateralization of the STN in the execution of an overt reading motor task and its intelligibility. This subcortical organization could be exploited for new adaptive stimulation strategies capable of identifying the occurrence of speaking behavior and facilitating its functional execution.

Neural pathway connectivity and discharge changes between M1 and STN in hemiparkinsonian rats

Alterations of electrophysiological activities, such as changed spike firing rates, reshaping the firing patterns, and aberrant frequency oscillations between the subthalamic nucleus (STN) and the primary motor cortex (M1), are thought to contribute to motor impairment in Parkinson's disease (PD). However, the alterations of electrophysiological characteristics of STN and M1 in PD are still unclear, especially under specific treadmill movement. To examine the relationship between electrophysiological activity in the STN-M1 pathway, extracellular spike trains and local field potential (LFPs) of STN and M1 were simultaneously recorded during resting and movement in unilateral 6-hydroxydopamine (6-OHDA) lesioned rats. The results showed that the identified STN neurons and M1 neurons exhibited abnormal neuronal activity after dopamine loss. The dopamine depletion altered the LFP power in STN and M1 whatever in rest or movement states. Furthermore, the enhanced synchronization of LFP oscillations after dopamine loss was found in 12-35 Hz (beta frequencies) between the STN and M1 during rest and movement. In addition, STN neurons were phase-locked firing to M1 oscillations at 12-35 Hz during rest epochs in 6-OHDA lesioned rats. The dopamine depletion also impaired the anatomical connectivity between the M1 and STN by injecting anterograde neuroanatomical tracing virus into M1 in control and PD rats. Collectively, impairment of' electrophysiological activity and anatomical connectivity in the M1-STN pathway may be the basis for dysfunction of the cortico-basal ganglia circuit, correlating with motor symptoms of PD.

Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation

Introduction

Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers.

Methods

Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG.

Results

Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity.

Discussion

Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.

Intensity-Varied Closed-Loop Noise Stimulation for Oscillation Suppression in the Parkinsonian State

This work explores the effectiveness of the intensity-varied closed-loop noise stimulation on the oscillation suppression in the Parkinsonian state. Deep brain stimulation (DBS) is the standard therapy for Parkinson's disease (PD), but its effects need to be improved. The noise stimulation has compelling results in alleviating the PD state. However, in the open-loop control scheme, the noise stimulation parameters cannot be self-adjusted to adapt to the amplitude of the synchronized neuronal activities in real time. Thus, based on the delayed-feedback control algorithm, an intensity-varied closed-loop noise stimulation strategy is proposed. Based on a computational model of the basal ganglia (BG) that can present the intrinsic properties of the BG neurons and their interactions with the thalamic neurons, the proposed stimulation strategy is tested. Simulation results show that the noise stimulation suppresses the pathological beta (12-35 Hz) oscillations without any new rhythms in other bands compared with traditional high-frequency DBS. The intensity-varied closed-loop noise stimulation has a more profound role in removing the pathological beta oscillations and improving the thalamic reliability than open-loop noise stimulation, especially for different PD states. And the closed-loop noise stimulation enlarges the parameter space of the delayed-feedback control algorithm due to the randomness of noise signals. We also provide a theoretical analysis of the effective parameter domain of the delayed-feedback control algorithm by simplifying the BG model to an oscillator model. This exploration may guide a new approach to treating PD by optimizing the noise-induced improvement of the BG dysfunction.

Transmission of delta band (0.5-4 Hz) oscillations from the globus pallidus to the substantia nigra pars reticulata in dopamine depletion

Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.

Model-based quantitative optimization of deep brain stimulation and prediction of parkinson's states

Although the exact etiology of Parkinson's disease (PD) is still unknown, there are a variety of treatments available to alleviate its symptoms according to the development stage of PD. Deep brain stimulation (DBS), the most common surgical treatment for advanced PD, accurately locates and implants stimulating electrodes at specific targets in the brain to deliver high-frequency electrical stimulation that alters the excitability of the corresponding nuclei. However, for different patients and stages of PD development, there exists a choice of the optimal DBS protocol. In this paper, we propose a quantitative method (multi-dimensional feature indexes) to determine the stimulation pattern, stimulation parameters, and target of DBS from the perspective of the network model. On the other hand, based on this method, the development of PD can be predicted so that timely treatment can be given to patients. Simulation results show that, first, different network states can be distinguished by extracting features of the firing activity of neuronal populations within the basal ganglia network system. Secondly, the optimal DBS treatment can be selected by comparing the feature indexes vectors of the pre- and post-state of the network after the action of different modes of DBS. Lastly, the evolution of the network state from normal to pathological is simulated. The critical point of network state transitions is determined. These results provide a quantitative and qualitative method for determining the optimal regimen for DBS for PD, which is helpful for clinical practice.

Electrophysiological confrontation of Lead-DBS-based electrode localizations in patients with Parkinson's disease undergoing deep brain stimulation

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Lead-DBS agreed with microelectrode recordings with millimetric precision.

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Lead-DBS identified misplaced electrodes that microelectrodes could only help suspect.

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Lead-DBS location of the limbic STN was in agreement with electrophysiological markers.

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Phase duration and firing rates could help identify dopamine neurons in humans.

Microelectrode recordings (MERs) are often used during deep brain stimulation (DBS) surgeries to confirm the position of electrodes in patients with advanced Parkinson’s disease.

The present study focused on 32 patients who had undergone DBS surgery for advanced Parkinson’s disease. The first objective was to confront the anatomical locations of intraoperative individual MERs as determined electrophysiologically with those determined postoperatively by image reconstructions. The second aim was to search for differences in cell characteristics among the three subthalamic nucleus (STN) subdivisions and between the STN and other identified subcortical structures.

Using the DISTAL atlas implemented in the Lead-DBS image reconstruction toolbox, each MER location was determined postoperatively and attributed to specific anatomical structures (sensorimotor, associative or limbic STN; substantia nigra [SN], thalamus, nucleus reticularis polaris, zona incerta [ZI]). The STN dorsal borders determined intraoperatively from electrophysiology were then compared with the STN dorsal borders determined by the reconstructed images. Parameters of spike clusters (firing rates, amplitudes – with minimum amplitude of 60 μV -, spike durations, amplitude spectral density of β-oscillations) were compared between structures (ANOVAs on ranks).

Two hundred and thirty one MERs were analyzed (144 in 34 STNs, 7 in 4 thalami, 5 in 4 ZIs, 34 in 10 SNs, 41 others). The average difference in depth of the electrophysiological dorsal STN entry in comparison with the STN entry obtained with Lead-DBS was found to be of 0.1 mm (standard deviation: 0.8 mm). All 12 analyzed MERs recorded above the electrophysiologically-determined STN entry were confirmed to be in the thalamus or zona incerta. All MERs electrophysiologically attributed to the SN were confirmed to belong to this nucleus. However, 6/34 MERs that were electrophysiologically attributed to the ventral STN were postoperatively reattributed to the SN. Furthermore, 44 MERs of 3 trajectories, which were intraoperatively attributed to the STN, were postoperatively reattributed to the pallidum or thalamus.

MER parameters seemed to differ across the STN, with higher spike amplitudes (H = 10.64, p < 0.01) and less prevalent β-oscillations (H = 9.81, p < 0.01) in the limbic STN than in the sensorimotor and associative subdivisions. Some cells, especially in the SN, showed longer spikes with lower firing rates, in agreement with described characteristics of dopamine cells. However, these probabilistic electrophysiological signatures might become clinically less relevant with the development of image reconstruction tools, which deserve to be applied intraoperatively.

Short pulse and directional thalamic deep brain stimulation have differential effects in parkinsonian and essential tremor

The aim of this study was to assess the effects of novel stimulation algorithms of deep brain stimulation (short pulse and directional stimulation) in the ventrointermediate thalamus and posterior subthalamic area (VIM/PSA-DBS) on tremor in Parkinson’s disease (PD) and to compare the effects with those in essential tremor (ET). We recruited six PD patients (70.8 ± 10.4 years) and seven ET patients (64.4 ± 9.9 years) with implanted VIM/PSA-DBS in a stable treatment condition (> 3 months postoperatively). Tremor severity and ataxia were assessed in four different stimulation conditions in a randomized order: DBS switched off (STIM OFF), omnidirectional stimulation with 60 µs (oDBS60), omnidirectional stimulation with 30 µs (oDBS30), directional stimulation at the best segment with 60 µs (dDBS60). In both patient groups, all three DBS stimulation modes reduced the total tremor score compared to STIM OFF, whereas stimulation-induced ataxia was reduced by oDBS30 and partially by dDBS60 compared to oDBS60. Tremor reduction was more pronounced in PD than in ET due to a limited DBS effect on intention and action-specific drawing tremor in ET. In PD and ET tremor, short pulse or directional VIM/PSA-DBS is an effective and well tolerated therapeutic option.

Trial registration: The study was registered in the DRKS (ID DRKS00025329, 18.05.2021, German Clinical Trials Register, DRKS—Deutsches Register Klinischer Studien).

Altered alpha and theta oscillations correlate with sequential working memory in Parkinson’s disease

Daily activities such as preparing a meal rely on the ability to arrange thoughts and actions in the right order. Patients with Parkinson’s disease have difficulties in sequencing tasks. Their deficits in sequential working memory have been associated with basal ganglia dysfunction. Here we demonstrate that altered parietal alpha and theta oscillations correlate with sequential working memory in Parkinson’s disease. We included 15 patients with Parkinson’s disease (6 women, mean age: 66.0 years), 24 healthy young (14 women, mean age: 24.1 years), and 16 older participants (7 women, mean age: 68.6 years). All participants completed a picture ordering task with scalp electroencephalogram (EEG) recording, where they arranged five pictures in a specific order and memorized them over a delay. When encoding and maintaining picture sequences, patients with Parkinson’s disease showed a lower baseline alpha peak frequency with higher alpha power than healthy young and older participants. Patients with a higher baseline alpha power responded more slowly for ordered trials. When manipulating picture sequences, patients with Parkinson’s disease showed a lower frequency of maximal power change for random versus ordered trials than healthy young and older participants. Healthy older participants showed a higher frequency of maximal power change than healthy young participants. Compared with patients with frequency of maximal power change in the alpha band (8–15 Hz), patients with frequency of maximal power change in the theta band (4–7 Hz) showed a higher ordering-related accuracy cost (random versus ordered) in the main task and tended to respond more slowly and less accurately in an independent working memory test. In conclusion, altered baseline alpha oscillations and task-dependent modulation of alpha and theta oscillations may be neural markers of poor sequential working memory in Parkinson’s disease.

Topographic connectivity and cellular profiling reveal detailed input pathways and functionally distinct cell types in the subthalamic nucleus

The subthalamic nucleus (STN) controls psychomotor activity and is an efficient therapeutic deep brain stimulation target in individuals with Parkinson's disease. Despite evidence indicating position-dependent therapeutic effects and distinct functions within the STN, the input circuit and cellular profile in the STN remain largely unclear. Using neuroanatomical techniques, we construct a comprehensive connectivity map of the indirect and hyperdirect pathways in the mouse STN. Our circuit- and cellular-level connectivities reveal a topographically graded organization with three types of indirect and hyperdirect pathways (external globus pallidus only, STN only, and collateral). We confirm consistent pathways into the human STN by 7 T MRI-based tractography. We identify two functional types of topographically distinct glutamatergic STN neurons (parvalbumin [PV+/-]) with synaptic connectivity from indirect and hyperdirect pathways. Glutamatergic PV+ STN neurons contribute to burst firing. These data suggest a complex interplay of information integration within the basal ganglia underlying coordinated movement control and therapeutic effects.

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.

Long-Lasting Desynchronization of Plastic Neuronal Networks by Double-Random Coordinated Reset Stimulation

Hypersynchrony of neuronal activity is associated with several neurological disorders, including essential tremor and Parkinson's disease (PD). Chronic high-frequency deep brain stimulation (HF DBS) is the standard of care for medically refractory PD. Symptoms may effectively be suppressed by HF DBS, but return shortly after cessation of stimulation. Coordinated reset (CR) stimulation is a theory-based stimulation technique that was designed to specifically counteract neuronal synchrony by desynchronization. During CR, phase-shifted stimuli are delivered to multiple neuronal subpopulations. Computational studies on CR stimulation of plastic neuronal networks revealed long-lasting desynchronization effects obtained by down-regulating abnormal synaptic connectivity. This way, networks are moved into attractors of stable desynchronized states such that stimulation-induced desynchronization persists after cessation of stimulation. Preclinical and clinical studies confirmed corresponding long-lasting therapeutic and desynchronizing effects in PD. As PD symptoms are associated with different pathological synchronous rhythms, stimulation-induced long-lasting desynchronization effects should favorably be robust to variations of the stimulation frequency. Recent computational studies suggested that this robustness can be improved by randomizing the timings of stimulus deliveries. We study the long-lasting effects of CR stimulation with randomized stimulus amplitudes and/or randomized stimulus timing in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity. Performing computer simulations and analytical calculations, we study long-lasting desynchronization effects of CR with and without randomization of stimulus amplitudes alone, randomization of stimulus times alone as well as the combination of both. Varying the CR stimulation frequency (with respect to the frequency of abnormal target rhythm) and the number of separately stimulated neuronal subpopulations, we reveal parameter regions and related mechanisms where the two qualitatively different randomization mechanisms improve the robustness of long-lasting desynchronization effects of CR. In particular, for clinically relevant parameter ranges double-random CR stimulation, i.e., CR stimulation with the specific combination of stimulus amplitude randomization and stimulus time randomization, may outperform regular CR stimulation with respect to long-lasting desynchronization. In addition, our results provide the first evidence that an effective reduction of the overall stimulation current by stimulus amplitude randomization may improve the frequency robustness of long-lasting therapeutic effects of brain stimulation.

Deep learning reveals personalized spatial spectral abnormalities of high delta and low alpha bands in EEG of patients with early Parkinson's disease

Objective.Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis is crucial to delay disease progression. The diagnosis of early PD has always been a difficult clinical problem due to the lack of reliable biomarkers. Electroencephalogram (EEG) is the most common clinical detection method, and studies have attempted to discover the EEG spectrum characteristics of early PD, but the reported conclusions are not uniform due to the heterogeneity of early PD patients. There is an urgent need for a more advanced algorithm to extract spectrum characteristics from EEG to satisfy the personalized requirements.Approach.The structured power spectral density with spatial distribution was used as the input of convolutional neural network (CNN). A visualization technique called gradient-weighted class activation mapping was used to extract the optimal frequency bands for identifying early PD. Based on the model visualization, we proposed a novel quantitative index of spectral characteristics, spatial-mapping relative power (SRP), to detect personalized abnormalities in the spatial spectral characteristics of EEG in early PD.Main results.We demonstrated the feasibility of applying CNN to identify the patients with early PD with an accuracy of 99.87% ± 0.03%. The models indicated the characteristic frequency bands (high-delta (3.5-4.5 Hz) and low-alpha (7.5-11 Hz) frequency bands) that are used to identify the early PD. The SRP of these two characteristic bands in early PD patients was significantly higher than that in the control group, and the abnormalities were consistent at the group and individual levels.Significance.This study provides a novel personalized detection algorithm based on deep learning to reveal the optimal frequency bands for identifying early PD and obtain the spatial frequency characteristics of early PD. The findings of this study will provide an effective reference for the auxiliary diagnosis of early PD in clinical practice.

Closing the loop of DBS using the beta oscillations in cortex

Cortical information has great importance to reflect the deep brain stimulation (DBS) effects for Parkinson's disease patients. Using cortical activities to feedback is an available closed-loop idea for DBS. Previous studies have demonstrated the pathological beta (12-35 Hz) cortical oscillations can be suppressed by appropriate DBS settings. Thus, here we propose to close the loop of DBS based on the beta oscillations in cortex. By modify the cortico-basal ganglia-thalamic neural loop model, more biologically realistic underlying the Parkinsonian phenomenon is approached. Stimulation results show the proposed closed-loop DBS strategy using cortical beta oscillation as feedback information has more profound roles in alleviating the pathological neural abnormality than the traditional open-loop DBS. Additionally, we compare the stimulation effects with subthalamic nucleus feedback strategy. It is shown that using cortical beta information as the feedback signals can further enlarge the control parameter space based on proportional-integral control structure with a lower energy expenditure. This work may pave the way to optimizing the DBS effects in a closed-loop arrangement.

Long-Lasting Desynchronization Effects of Coordinated Reset Stimulation Improved by Random Jitters

Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands.

Impaired reach-to-grasp kinematics in parkinsonian patients relates to dopamine-dependent, subthalamic beta bursts

Excessive beta-band oscillations in the subthalamic nucleus are key neural features of Parkinson’s disease. Yet the distinctive contributions of beta low and high bands, their dependency on striatal dopamine, and their correlates with movement kinematics are unclear. Here, we show that the movement phases of the reach-to-grasp motor task are coded by the subthalamic bursting activity in a maximally-informative beta high range. A strong, three-fold correlation linked beta high range bursts, imbalanced inter-hemispheric striatal dopaminergic tone, and impaired inter-joint movement coordination. These results provide new insight into the neural correlates of motor control in parkinsonian patients, paving the way for more informative use of beta-band features for adaptive deep brain stimulation devices.

Conveyance of cortical pacing for parkinsonian tremor-like hyperkinetic behavior by subthalamic dysrhythmia

Parkinson's disease is characterized by both hypokinetic and hyperkinetic symptoms. While increased subthalamic burst discharges have a direct causal relationship with the hypokinetic manifestations (e.g., rigidity and bradykinesia), the origin of the hyperkinetic symptoms (e.g., resting tremor and propulsive gait) has remained obscure. Neuronal burst discharges are presumed to be autonomous or less responsive to synaptic input, thereby interrupting the information flow. We, however, demonstrate that subthalamic burst discharges are dependent on cortical glutamatergic synaptic input, which is enhanced by A-type K+ channel inhibition. Excessive top-down-triggered subthalamic burst discharges then drive highly correlative activities bottom-up in the motor cortices and skeletal muscles. This leads to hyperkinetic behaviors such as tremors, which are effectively ameliorated by inhibition of cortico-subthalamic AMPAergic synaptic transmission. We conclude that subthalamic burst discharges play an imperative role in cortico-subcortical information relay, and they critically contribute to the pathogenesis of both hypokinetic and hyperkinetic parkinsonian symptoms.

Coordinated Reset Vibrotactile Stimulation Induces Sustained Cumulative Benefits in Parkinson's Disease

BACKGROUND

Abnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson's disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings.

METHODS

Study 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking.

RESULTS

Clinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21-30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization.

CONCLUSION

In these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.

Long-Lasting Desynchronization of Plastic Neural Networks by Random Reset Stimulation

Excessive neuronal synchrony is a hallmark of neurological disorders such as epilepsy and Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency (HF) deep brain stimulation (DBS). However, symptoms return shortly after cessation of HF-DBS. Recently developed decoupling stimulation approaches, such as Random Reset (RR) stimulation, specifically target pathological connections to achieve long-lasting desynchronization. During RR stimulation, a temporally and spatially randomized stimulus pattern is administered. However, spatial randomization, as presented so far, may be difficult to realize in a DBS-like setup due to insufficient spatial resolution. Motivated by recently developed segmented DBS electrodes with multiple stimulation sites, we present a RR stimulation protocol that copes with the limited spatial resolution of currently available depth electrodes for DBS. Specifically, spatial randomization is realized by delivering stimuli simultaneously to L randomly selected stimulation sites out of a total of M stimulation sites, which will be called L/M-RR stimulation. We study decoupling by L/M-RR stimulation in networks of excitatory integrate-and-fire neurons with spike-timing dependent plasticity by means of theoretical and computational analysis. We find that L/M-RR stimulation yields parameter-robust decoupling and long-lasting desynchronization. Furthermore, our theory reveals that strong high-frequency stimulation is not suitable for inducing long-lasting desynchronization effects. As a consequence, low and high frequency L/M-RR stimulation affect synaptic weights in qualitatively different ways. Our simulations confirm these predictions and show that qualitative differences between low and high frequency L/M-RR stimulation are present across a wide range of stimulation parameters, rendering stimulation with intermediate frequencies most efficient. Remarkably, we find that L/M-RR stimulation does not rely on a high spatial resolution, characterized by the density of stimulation sites in a target area, corresponding to a large M. In fact, L/M-RR stimulation with low resolution performs even better at low stimulation amplitudes. Our results provide computational evidence that L/M-RR stimulation may present a way to exploit modern segmented lead electrodes for long-lasting therapeutic effects.

Dopaminergic denervation impairs cortical motor and associative/limbic information processing through the basal ganglia and its modulation by the CB1 receptor

The basal ganglia (BG) are involved in cognitive/motivational functions in addition to movement control. Thus, BG segregated circuits, the sensorimotor (SM) and medial prefrontal (mPF) circuits, process different functional domains, such as motor and cognitive/motivational behaviours, respectively. With a high presence in the BG, the CB1 cannabinoid receptor modulates BG circuits. Furthermore, dopamine (DA), one of the principal neurotransmitters in the BG, also plays a key role in circuit functionality. Taking into account the interaction between DA and the endocannabinoid system at the BG level, we investigated the functioning of BG circuits and their modulation by the CB1 receptor under DA-depleted conditions. We performed single-unit extracellular recordings of substantia nigra pars reticulata (SNr) neurons with simultaneous cortical stimulation in sham and 6-hydroxydopamine (6-OHDA)-lesioned rats, together with immunohistochemical assays. We showed that DA loss alters cortico-nigral information processing in both circuits, with a predominant transmission through the hyperdirect pathway in the SM circuit and an increased transmission through the direct pathway in the mPF circuit. Moreover, although DA denervation does not change CB1 receptor density, it impairs its functionality, leading to a lack of modulation. These data highlight an abnormal transfer of information through the associative/limbic domains after DA denervation that may be related to the non-motor symptoms manifested by Parkinson's disease patients.

Impact of number of stimulation sites on long-lasting desynchronization effects of coordinated reset stimulation

Excessive neuronal synchrony is a hallmark of several neurological disorders, e.g., Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency deep brain stimulation. However, it provides only acute relief, and symptoms return shortly after cessation of stimulation. A theory-based approach called coordinated reset (CR) has shown great promise in achieving long-lasting effects. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites to counteract neuronal synchrony. Computational studies in plastic neuronal networks reported that synaptic weights reduce during stimulation, which may cause sustained structural changes leading to stabilized desynchronized activity even after stimulation ceases. Corresponding long-lasting effects were found in recent preclinical and clinical studies. We study long-lasting desynchronization by CR stimulation in excitatory recurrent neuronal networks of integrate-and-fire neurons with spike-timing-dependent plasticity (STDP). We focus on the impact of the stimulation frequency and the number of stimulation sites on long-lasting effects. We compare theoretical predictions to simulations of plastic neuronal networks. Our results are important regarding CR calibration for two reasons. We reveal that long-lasting effects become most pronounced when stimulation parameters are adjusted to the characteristics of STDP-rather than to neuronal frequency characteristics. This is in contrast to previous studies where the CR frequency was adjusted to the dominant neuronal rhythm. In addition, we reveal a nonlinear dependence of long-lasting effects on the number of stimulation sites and the CR frequency. Intriguingly, optimal long-lasting desynchronization does not require larger numbers of stimulation sites.

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

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

Independently together: subthalamic theta and beta opposite roles in predicting Parkinson's tremor

Tremor is a core feature of Parkinson’s disease and the most easily recognized Parkinsonian sign. Nonetheless, its pathophysiology remains poorly understood. Here, we show that multispectral spiking activity in the posterior-dorso-lateral oscillatory (motor) region of the subthalamic nucleus distinguishes resting tremor from the other Parkinsonian motor signs and strongly correlates with its severity. We evaluated microelectrode-spiking activity from the subthalamic dorsolateral oscillatory region of 70 Parkinson’s disease patients who underwent deep brain stimulation surgery (114 subthalamic nuclei, 166 electrode trajectories). We then investigated the relationship between patients’ clinical Unified Parkinson’s Disease Rating Scale score and their peak theta (4–7 Hz) and beta (13–30 Hz) powers. We found a positive correlation between resting tremor and theta activity (r = 0.41, P < 0.01) and a non-significant negative correlation with beta activity (r = −0.2, P = 0.5). Hypothesizing that the two neuronal frequencies mask each other’s relationship with resting tremor, we created a non-linear model of their proportional spectral powers and investigated its relationship with resting tremor. As hypothesized, patients’ proportional scores correlated better than either theta or beta alone (r = 0.54, P < 0.001). However, theta and beta oscillations were frequently temporally correlated (38/70 patients manifested significant positive temporal correlations and 1/70 exhibited significant negative correlation between the two frequency bands). When comparing theta and beta temporal relationship (r θ β) to patients’ resting tremor scores, we found a significant negative correlation between the two (r = −0.38, P < 0.01). Patients manifesting a positive correlation between the two bands (i.e. theta and beta were likely to appear simultaneously) were found to have lower resting tremor scores than those with near-zero correlation values (i.e. theta and beta were likely to appear separately). We therefore created a new model incorporating patients’ proportional theta–beta power and r θ βscores to obtain an improved neural correlate of resting tremor (r = 0.62, P < 0.001). We then used the Akaike and Bayesian information criteria for model selection and found the multispectral model, incorporating theta–beta proportional power and their correlation, to be the best fitting model, with 0.96 and 0.89 probabilities, respectively. Here we found that as theta increases, beta decreases and the two appear separately—resting tremor is worsened. Our results therefore show that theta and beta convey information about resting tremor in opposite ways. Furthermore, the finding that theta and beta coactivity is negatively correlated with resting tremor suggests that theta–beta non-linear scale may be a valuable biomarker for Parkinson’s resting tremor in future adaptive deep brain stimulation techniques.

Freezing of gait in Parkinson's disease reflects a sudden derangement of locomotor network dynamics

Freezing of gait is a disabling symptom of Parkinson's disease that causes a paroxysmal inability to generate effective stepping. The underlying pathophysiology has recently migrated towards a dysfunctional supraspinal locomotor network, but the actual network derangements during ongoing gait freezing are unknown. We investigated the communication between the cortex and the subthalamic nucleus, two main nodes of the locomotor network, in seven freely-moving subjects with Parkinson's disease with a novel deep brain stimulation device, which allows on-demand recording of subthalamic neural activity from the chronically-implanted electrodes months after the surgical procedure. Multisite neurophysiological recordings during (effective) walking and ongoing gait freezing were combined with kinematic measurements and individual molecular brain imaging studies. Patients walked in a supervised environment closely resembling everyday life challenges. We found that during (effective) walking, the cortex and subthalamic nucleus were synchronized in a low frequency band (4-13 Hz). In contrast, gait freezing was characterized in every patient by low frequency cortical-subthalamic decoupling in the hemisphere with less striatal dopaminergic innervation. Of relevance, this decoupling was already evident at the transition from normal (effective) walking into gait freezing, was maintained during the freezing episode, and resolved with recovery of the effective walking pattern. This is the first evidence for a decoding of the networked processing of locomotion in Parkinson's disease and suggests that freezing of gait is a 'circuitopathy' related to a dysfunctional cortical-subcortical communication. A successful therapeutic approach for gait freezing in Parkinson's disease should aim at directly targeting derangements of neural network dynamics.

Evolving concepts on bradykinesia

Bradykinesia is one of the cardinal motor symptoms of Parkinson's disease and other parkinsonisms. The various clinical aspects related to bradykinesia and the pathophysiological mechanisms underlying bradykinesia are, however, still unclear. In this article, we review clinical and experimental studies on bradykinesia performed in patients with Parkinson's disease and atypical parkinsonism. We also review studies on animal experiments dealing with pathophysiological aspects of the parkinsonian state. In Parkinson's disease, bradykinesia is characterized by slowness, the reduced amplitude of movement, and sequence effect. These features are also present in atypical parkinsonisms, but the sequence effect is not common. Levodopa therapy improves bradykinesia, but treatment variably affects the bradykinesia features and does not significantly modify the sequence effect. Findings from animal and patients demonstrate the role of the basal ganglia and other interconnected structures, such as the primary motor cortex and cerebellum, as well as the contribution of abnormal sensorimotor processing. Bradykinesia should be interpreted as arising from network dysfunction. A better understanding of bradykinesia pathophysiology will serve as the new starting point for clinical and experimental purposes.

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.

Long-Term Exposure to PFE-360 in the AAV-α-Synuclein Rat Model: Findings and Implications

Parkinson's disease (PD) is a progressive neurodegenerative disorder associated with impaired motor function and several non-motor symptoms, with no available disease modifying treatment. Intracellular accumulation of pathological α-synuclein inclusions is a hallmark of idiopathic PD, whereas, dominant mutations in leucine-rich repeat kinase 2 (LRRK2) are associated with familial PD that is clinically indistinguishable from idiopathic PD. Recent evidence supports the hypothesis that an increase in LRRK2 kinase activity is associated with the development of not only familial LRRK2 PD, but also idiopathic PD. Previous reports have shown preclinical effects of LRRK2 modulation on α-synuclein-induced neuropathology. Increased subthalamic nucleus (STN) burst firing in preclinical neurotoxin models and PD patients is hypothesized to be causally involved in the development of the motor deficit in PD. To study a potential pathophysiological relationship between α-synuclein pathology and LRRK2 kinase activity in PD, we investigated the effect of chronic LRRK2 inhibition in an AAV-α-synuclein overexpression rat model. In this study, we report that chronic LRRK2 inhibition using PFE-360 only induced a marginal effect on motor function. In addition, the aberrant STN burst firing and associated neurodegenerative processes induced by α-synuclein overexpression model remained unaffected by chronic LRRK2 inhibition. Our findings do not strongly support LRRK2 inhibition for the treatment of PD. Therefore, the reported beneficial effects of LRRK2 inhibition in similar α-synuclein overexpression rodent models must be considered with prudence and additional studies are warranted in alternative α-synuclein-based models.

Noise-Induced Improvement of the Parkinsonian State: A Computational Study

The benefit of noise in improving the basal ganglia (BG) dysfunctions, especially Parkinsonian state, is explored in this paper. High frequency (≥ 100 Hz) deep brain stimulation (DBS), as a clinical effective stimulation method, has compelling and fantastic results in alleviating the motor symptoms of Parkinson's disease (PD). However, the mechanism of DBS is still unclear. And the selection of the DBS waveform parameters faces great challenges to further optimize the stimulation effects and to reduce its energy expenditure. Considering that the desynchronization of the BG neuronal activities is benefited from the forced high frequency regular spikes driven by standard high frequency DBS, we expect to explore a novel stimulation method that has capability of restoring the BG physiological firing patterns without introducing artificial high-frequency fires. In this paper, a colored noise stimulation is used as a neuromodulation method to disrupt the firing patterns of the pathological neuronal activities. A computational model of the BG that exhibits the intrinsic properties of the BG neurons and their interactions with the thalamic (Th) cells is employed. Based on the model, we investigate the effects of noise stimulation and explore the impacts of the noise stimulation parameters on both relay reliability of the Th neurons and energy expenditure of the stimulation. By comparison, it can be found that noise stimulation does not entrain the network to an artificial high-frequency firing state, but induces the pathological increased synchronous activities back to a normal physiological level. Moreover, besides the capability of restoring the neuronal state, the benefits of the noise also include its balanced waveform to avert potential tissue or electrode damage and its ability to reduce the energy expenditure to 50% less than that of the standard DBS, when the noise stimulation has low frequency (≤ 100 Hz) and appropriate intensity. Thus, the exploration of the optimal noise-induced improvement of the BG dysfunction is of great significance in treating symptoms of neurological disorders such as PD.

Levodopa Modulates Functional Connectivity in the Upper Beta Band Between Subthalamic Nucleus and Muscle Activity in Tonic and Phasic Motor Activity Patterns in Parkinson's Disease

Introduction: Striatal dopamine depletion disrupts basal ganglia function and causes Parkinson's disease (PD). The pathophysiology of the dopamine-dependent relationship between basal ganglia signaling and motor control, however, is not fully understood. We obtained simultaneous recordings of local field potentials (LFPs) from the subthalamic nucleus (STN) and electromyograms (EMGs) in patients with PD to investigate the impact of dopaminergic state and movement on long-range beta functional connectivity between basal ganglia and lower motor neurons. Methods: Eight PD patients were investigated 3 months after implantation of a deep brain stimulation (DBS)-system capable of recording LFPs via chronically-implanted leads (Medtronic, ACTIVA PC+S^®). We analyzed STN spectral power and its coherence with EMG in the context of two different movement paradigms (tonic wrist extension vs. alternating wrist extension and flexion) and the effect of levodopa (L-Dopa) intake using an unbiased data-driven approach to determine regions of interest (ROI). Results: Two ROIs capturing prominent coherence within a grand average coherogram were identified. A trend of a dopamine effect was observed for the first ROI (50-150 ms after movement start) with higher STN-EMG coherence in medicated patients. Concerning the second ROI (300-500 ms after movement start), an interaction effect of L-Dopa medication and movement task was observed with higher coherence in the isometric contraction task compared to alternating movements in the medication ON state, a pattern which was reversed in L-Dopa OFF. Discussion: L-Dopa medication may normalize functional connectivity between remote structures of the motor system with increased upper beta coherence reflecting a physiological restriction of the amount of information conveyed between remote structures. This may be necessary to maintain simple movements like isometric contraction. Our study adds dynamic properties to the complex interplay between STN spectral beta power and the nucleus' functional connectivity to remote structures of the motor system as a function of movement and dopaminergic state. This may help to identify markers of neuronal activity relevant for more individualized programming of DBS therapy.

Evaluation of Spike Sorting Algorithms: Application to Human Subthalamic Nucleus Recordings and Simulations

An important prerequisite for the analysis of spike synchrony in extracellular recordings is the extraction of single-unit activity from the multi-unit signal. To identify single units, potential spikes are separated with respect to their potential neuronal origins ('spike sorting'). However, different sorting algorithms yield inconsistent unit assignments, which seriously influences subsequent spike train analyses. We aim to identify the best sorting algorithm for subthalamic nucleus recordings of patients with Parkinson's disease (experimental data ED). Therefore, we apply various prevalent algorithms offered by the 'Plexon Offline Sorter' and evaluate the sorting results. Since this evaluation leaves us unsure about the best algorithm, we apply all methods again to artificial data (AD) with known ground truth. AD consists of pairs of single units with different shape similarity embedded in the background noise of the ED. The sorting evaluation depicts a significant influence of the respective methods on the single unit assignments. We find a high variability in the sortings obtained by different algorithms that increases with single units shape similarity. We also find significant differences in the resulting firing characteristics. We conclude that Valley-Seeking algorithms produce the most accurate result if the exclusion of artifacts as unsorted events is important. If the latter is less important ('clean' data) the K-Means algorithm is a better option. Our results strongly argue for the need of standardized validation procedures based on ground truth data. The recipe suggested here is simple enough to become a standard procedure.

Mapping stimulation-induced beneficial and adverse effects in the subthalamic area of essential tremor patients

BACKGROUND

Stimulation of the subthalamic area (STA) is an effective treatment in essential tremor patients, but limited by stimulation induced adverse effects. The aim of this study was to determine the spatial distribution of stimulus related tremor suppression, ataxia induction and paresthesia of the upper limb in the subthalamic area (STA) of essential tremor patients.

METHODS

We recruited eight patients with essential tremor in a stable postoperative condition (>3 months after surgery). Stimulation-induced effects were assessed with suprathreshold stimulation. Tremor severity was assessed with the Fahn-Tolosa-Marin tremor rating scale (TRS) and cerebellar impairment was evaluated using the international cooperative ataxia rating scale (ICARS). Patients rated paresthesia intensity with a visual analog scale. Linear regression analysis was performed to associate stereotactic coordinates with tremor, ataxia and paresthesia.

RESULTS

Suprathreshold stimulation significantly decreased tremor and elicited ataxia and paresthesia in all patients (P < 0.001). Tremor rating scale (TRS) total score was positively correlated with y-coordinates (r = 0.44, P < 0.05), i.e. anterior stimulation sites were more effective to suppress tremor. Concerning adverse effects, ataxia induction was positively correlated with z-coordinates almost reaching statistical significance (r = 0.50, P = 0.07), i.e. inferior stimulation sites elicit stronger ataxia. Furthermore, paresthesia was positively correlated with y-coordinates (r = 0.66; P < 0.01) and to a lesser degree with x-coordinates (r = 0.32; P = 0.08), i.e. posterior and lateral stimulation sites within the STA caused more paresthesia.

CONCLUSION

Antero-dorso-medial stimulation site in the STA were associated with less tremor and adverse effects in our small single-center cohort of ET patients with thalamic DBS.

Synchronised spiking activity underlies phase amplitude coupling in the subthalamic nucleus of Parkinson's disease patients

Both phase-amplitude coupling (PAC) and beta-bursts in the subthalamic nucleus have been significantly linked to symptom severity in Parkinson's disease (PD) in humans and emerged independently as competing biomarkers for closed-loop deep brain stimulation (DBS). However, the underlying nature of subthalamic PAC is poorly understood and its relationship with transient beta burst-events has not been investigated. To address this, we studied macro- and micro electrode recordings of local field potentials (LFPs) and single unit activity from 15 hemispheres in 10 PD patients undergoing DBS surgery. PAC between beta phase and high frequency oscillation (HFO) amplitude was compared to single unit firing rates, spike triggered averages, power spectral densities, inter spike intervals and phase-spike locking, and was studied in periods of beta-bursting. We found a significant synchronisation of spiking to HFOs and correlation of mean firing rates with HFO-amplitude when the latter was coupled to beta phase (i.e. in the presence of PAC). In the presence of PAC, single unit power spectra displayed peaks in the beta and HFO frequency range and the HFO frequency was correlated with that in the LFP. Furthermore, inter spike interval frequencies peaked in the same frequencies for which PAC was observed. Finally, PAC significantly increased with beta burst-duration. Our findings offer new insight in the pathology of Parkinson's disease by providing evidence that subthalamic PAC reflects the locking of spiking activity to network beta oscillations and that this coupling progressively increases with beta-burst duration. These findings suggest that beta-bursts capture periods of increased subthalamic input/output synchronisation in the beta frequency range and have important implications for therapeutic closed-loop DBS.

Histamine and deep brain stimulation: the pharmacology of regularizing a brain

Parkinson's disease (PD) patients have increased histamine in their basal ganglia, but the role of this neurotransmitter in PD is poorly understood. In this issue of the JCI, Zhuang et al. demonstrate that histamine levels rise in the subthalamic nucleus (STN) to compensate for abnormal firing patterns. Injection of histamine into the STN restores normal firing patterns and motor activity, whereas merely changing firing rates has no behavioral effect. Moreover, STN deep brain stimulation, a widespread therapy for PD, regularizes firing through endogenous histamine release. This suggests that abnormal firing patterns, rather than rates, cause PD symptoms, and this histaminergic pathway may lead to new treatments for the disease.

Robust desynchronization of Parkinson's disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation

The hyperkinetic symptoms of Parkinson's Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.

Properties of oscillatory neuronal activity in the basal ganglia and thalamus in patients with Parkinson's disease

Background

The cardinal features of Parkinson’s disease (PD) are bradykinesia, rigidity and rest tremor. Abnormal activity in the basal ganglia is predicted to underlie the mechanism of motor symptoms. This study aims to characterize properties of oscillatory activity in the basal ganglia and motor thalamus in patients with PD.

Methods

Twenty-nine patients with PD who underwent bilateral or unilateral electrode implantation for subthalamic nucleus (STN) DBS (n = 11), unilateral pallidotomy (n = 9) and unilateral thalamotomy (n = 9) were studied. Microelectrode recordings in the STN, globus pallidus internus (GPi) and ventral oral posterior/ventral intermediate of thalamus (Vop/Vim) were performed. Electromyography of the contralateral limbs was recorded. Single unit characteristics including interspike intervals were analyzed. Spectral and coherence analyses were assessed. Mean spontaneous firing rate (MSFR) of neurons was calculated. Analysis of variance and X² test were performed.

Results

Of 76 STN neurons, 39.5% were 4–6 Hz band oscillatory neurons and 28.9% were β frequency band (βFB) oscillatory neurons. The MSFR was 44.2 ± 7.6 Hz. Of 62 GPi neurons, 37.1% were 4–6 Hz band oscillatory neurons and 27.4% were βFB neurons. The MSFR was 80.9 ± 9.6 Hz. Of 44 Vop neurons, 65.9% were 4–6 Hz band oscillatory neurons and 9% were βFB neurons. The MSFR was 24.4 ± 4.2 Hz. Of 30 Vim oscillatory neurons, 70% were 4–6 Hz band oscillatory neurons and 13.3% were βFB neurons. The MSFR was 30.3 ± 3.6 Hz. Further analysis indicated that proportion of βFB oscillatory neurons in STN and GPi was higher than that of similar neurons in the Vop and Vim (P < 0.05). Conversely, the proportion of 4–6 Hz band oscillatory neurons and tremor related neurons in the Vim and Vop was higher than that of STN and GPi (P < 0.05). The highest MSFR was for GPi oscillatory neurons whereas the lowest MSFR was for Vop oscillatory neurons (P < 0.005).

Conclusion

The alterations in neuronal activity in basal ganglia play a critical role in generation of parkinsonism. β oscillatory activity is more prominent in basal ganglia than in thalamus suggesting that the activity likely results from dopaminergic depletion. While both basal ganglia and thalamus have tremor activity, the thalamus appears to play a more important role in tremor production, and basal ganglia β oscillatory activity might be the trigger.

Thalamic short pulse stimulation diminishes adverse effects in essential tremor patients

OBJECTIVE

To investigate the effect of directional current steering and short pulse stimulation in the ventral intermediate thalamic nucleus (VIM) on stimulation-induced side effects in patients with essential tremor.

METHODS

We recruited 8 patients with essential tremor in a stable postoperative condition (>3 months after electrode implantation of deep brain stimulation [DBS] electrodes) with segmented contacts implanted in the VIM. Tremor severity on acute stimulation was assessed by the Fahn-Tolosa-Marin Tremor Rating Scale. Cerebellar impairment was evaluated with the International Cooperative Ataxia Rating Scale. Patients rated paresthesia intensity with a visual analog scale.

RESULTS

In all patients, tremor was reduced to the same extent by VIM stimulation regardless of pulse width using energy dose-equivalent amplitudes. Short pulse stimulation diminished stimulation-induced ataxia of the upper extremities and paresthesia compared with conventional parameters. Directional steering with monopolar stimulation of single segments successfully suppressed tremor but also induced ataxia. No differences in adverse effects were found between single-segment stimulation conditions.

CONCLUSION

These proof-of-principle findings provide evidence that acute short pulse stimulation is superior to directional steering in the subthalamic area to decrease stimulation-induced side effects while preserving tremor suppression effects in patients with tremor.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that for patients with tremor with thalamic DBS, acute short pulse stimulation reduces adverse effects, while directional steering does not provide a generalizable benefit regarding adverse effects.

Phase matters: A role for the subthalamic network during gait

The role of the subthalamic nucleus in human locomotion is unclear although relevant, given the troublesome management of gait disturbances with subthalamic deep brain stimulation in patients with Parkinson’s disease. We investigated the subthalamic activity and inter-hemispheric connectivity during walking in eight freely-moving subjects with Parkinson’s disease and bilateral deep brain stimulation. In particular, we compared the subthalamic power spectral densities and coherence, amplitude cross-correlation and phase locking value between resting state, upright standing, and steady forward walking. We observed a phase locking value drop in the β-frequency band (≈13-35Hz) during walking with respect to resting and standing. This modulation was not accompanied by specific changes in subthalamic power spectral densities, which was not related to gait phases or to striatal dopamine loss measured with [¹²³I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane and single-photon computed tomography. We speculate that the subthalamic inter-hemispheric desynchronization in the β-frequency band reflects the information processing of each body side separately, which may support linear walking. This study also suggests that in some cases (i.e. gait) the brain signal, which could allow feedback-controlled stimulation, might derive from network activity.