High-frequency stimulation of the subthalamic nucleus suppresses oscillatory beta activity in patients with Parkinson's disease in parallel with improvement in motor performance

Entrainment by transcranial alternating current stimulation: Insights from models of cortical oscillations and dynamical systems theory

Signature of neuronal oscillations can be found in nearly every brain function. However, abnormal oscillatory activity is linked with several brain disorders. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that can potentially modulate neuronal oscillations and influence behavior both in health and disease. Yet, a complete understanding of how interacting networks of neurons are affected by tACS remains elusive. Entrainment effects by which tACS synchronizes neuronal oscillations is one of the main hypothesized mechanisms, as evidenced in animals and humans. Computational models of cortical oscillations may shed light on the entrainment effects of tACS, but current modeling studies lack specific guidelines to inform experimental investigations. This study addresses the existing gap in understanding the mechanisms of tACS effects on rhythmogenesis within the brain by providing a comprehensive overview of both theoretical and experimental perspectives. We explore the intricate interactions between oscillators and periodic stimulation through the lens of dynamical systems theory. Subsequently, we present a synthesis of experimental findings that demonstrate the effects of tACS on both individual neurons and collective oscillatory patterns in animal models and humans. Our review extends to computational investigations that elucidate the interplay between tACS and neuronal dynamics across diverse cortical network models. To illustrate these concepts, we conclude with a simple oscillatory neuron model, showcasing how fundamental theories of oscillatory behavior derived from dynamical systems, such as phase response of neurons to external perturbation, can account for the entrainment effects observed with tACS. Studies reviewed here render the necessity of integrated experimental and computational approaches for effective neuromodulation by tACS in health and disease.

Effects of theta burst stimulation on the Parkinsonian gait disorder and cortical gait-network activity

BackgroundThe Parkinsonian gait disorder and freezing of gait (FoG) are challenging symptoms of Parkinson's disease (PD).ObjectiveTo assess the effect of subthalamic theta burst deep brain stimulation (TBS-DBS) on the Parkinsonian gait performance in real-world conditions and cortical activity indexed by mobile EEG.MethodsIn this monocentric, randomised, double-blind, short-term study, 12 age-matched controls (11 male, age 59 ± 8 years) and 15 PD participants (14 male, age 62 ± 9 years, disease duration 15 ± 6 years) with subthalamic stimulation (76 ± 39 months) were assessed with clinical scores (FoG-Course, MDS-UPDRS) and a standardized gait course simulating everyday life situations. Three DBS algorithms were applied in a randomized order with intertrial waiting periods of 30 min: (1) OFF-DBS; (2) cDBS; (3) TBS-DBS (interburst frequency 5 Hz, intraburst frequency 200 Hz) with regular medication. During the standardized gait course a mobile, 24-channel EEG system and 6 wearable axial kinematic sensors were used.ResultsThe primary outcome, the relative change of FoG-Course by DBS, was not superior with TBS-DBS compared to cDBS in the entire sample. Seven of fifteen PD participants rated subjectively TBS-DBS equal or better than cDBS ("TBS-preference group"). EEG recordings revealed movement-induced alpha and beta suppression in premotor and motor cortex in both cDBS and TBS-DBS conditions in PD with slightly different patterns between the DBS modes.ConclusionsIn this pilot trial, TBS-DBS showed benefits in the subjective perception of gait in a subgroup of PD patients accompanied by specific cortical network changes. TBS-DBS merits further investigation in future larger cohort studies with longer observation periods.

AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson's disease for the development of neuronal fingerprints using artificial intelligence

INTRODUCTION

Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current application uses continuous high-frequency stimulation at a constant intensity, which may reduce efficacy and cause side effects. The objective of the AI-DBS study is to identify patient-specific patterns of neuronal activity that are associated with the severity of motor symptoms of PD. This information is essential for the development of advanced responsive stimulation algorithms, which may improve the efficacy of DBS.

METHODS AND ANALYSIS

This longitudinal prospective observational cohort study will enrol 100 patients with PD who are bilaterally implanted with a sensing-enabled DBS system (Percept PC, Medtronic) in the subthalamic nucleus as part of standard clinical care. Local neuronal activity, specifically local field potential (LFP) signals, will be recorded during the first 6 months after DBS implantation. Correlations will be tested between spectral features of LFP data and symptom severity, which will be assessed using (1) inertial sensor data from a wearable smartwatch, (2) clinical rating scales and (3) patient diaries and analysed using conventional descriptive statistics and artificial intelligence algorithms. The primary objective is to identify patient-specific profiles of neuronal activity that are associated with the presence and severity of motor symptoms, forming a 'neuronal fingerprint'.

ETHICS AND DISSEMINATION

Ethical approval was granted by the local ethics committee of the Amsterdam UMC (registration number 2022.0368). Study findings will be disseminated through scientific journals and presented at national and international conferences.

Deep brain stimulation alleviates Parkinsonian motor deficits through desynchronizing GABA release in mice

High-frequency deep brain stimulation (DBS) at subthalamic nucleus (STN) is an effective therapy for Parkinson's disease (PD), but the underlying mechanisms remain unclear. Here we find an important role of asynchronous release (AR) of GABA induced by high-frequency stimulation (HFS) in alleviating motor functions of dopamine-depleted male mice. Electrophysiological recordings reveal that 130-Hz HFS causes an initial inhibition followed by desynchronization of STN neurons, largely attributable to presynaptic GABA release. Low-frequency stimulation at 20 Hz, however, produces much weaker AR and negligible effects on neuronal firing. Further optogenetic and cell-ablation experiments demonstrate that activation of parvalbumin axons, but not non-parvalbumin axons, from external globus pallidus (GPe) is both necessary and sufficient for DBS effects. Reducing AR diminishes the high-frequency DBS effect, while increasing AR allows low-frequency DBS to achieve a therapeutic benefit. Therefore, asynchronous GABA release from GPe PV neurons may contribute significantly to the therapeutic effects of high-frequency DBS.

Shared pathway-specific network mechanisms of dopamine and deep brain stimulation for the treatment of Parkinson's disease

Deep brain stimulation is a brain circuit intervention that can modulate distinct neural pathways for the alleviation of neurological symptoms in patients with brain disorders. In Parkinson's disease, subthalamic deep brain stimulation clinically mimics the effect of dopaminergic drug treatment, but the shared pathway mechanisms on cortex - basal ganglia networks are unknown. To address this critical knowledge gap, we combined fully invasive neural multisite recordings in patients undergoing deep brain stimulation surgery with normative MRI-based whole-brain connectomics. Our findings demonstrate that dopamine and stimulation exert distinct mesoscale effects through modulation of local neural population activity. In contrast, at the macroscale, stimulation mimics dopamine in its suppression of excessive interregional network synchrony associated with indirect and hyperdirect cortex - basal ganglia pathways. Our results provide a better understanding of the circuit mechanisms of dopamine and deep brain stimulation, laying the foundation for advanced closed-loop neurostimulation therapies.

Application and research progress of different frequency tACS in stroke rehabilitation: A systematic review

After a stroke, abnormal changes in neural oscillations that are related to the severity and prognosis of the disease can occur. Resetting these abnormal neural oscillations is a potential approach for stroke rehabilitation. Transcranial alternating current stimulation (tACS) can modulate intrinsic neural oscillations noninvasively and has attracted attention as a possible technique to improve multiple post-stroke symptoms, including deficits in speech, vision, and motor ability and overall neurological recovery. The clinical effect of tACS varies according to the selected frequency. Therefore, choosing an appropriate frequency to optimize outcomes for specific dysfunctions is essential. This review focuses on the current research status and possibilities of tACS with different frequencies in stroke rehabilitation. We also discuss the possible mechanisms of tACS in stroke to provide a theoretical foundation for the method and highlight the controversial aspects that need further exploration. Although tACS has great potential, few clinical studies have applied it in the treatment of stroke, and no consensus has been reached. We analyze limitations in experimental designs and identify potential tACS approaches worthy of exploration in the future.

Long-Term Stability of Spatial Distribution and Peak Dynamics of Subthalamic Beta Power in Parkinson's Disease Patients

BACKGROUND

Subthalamic beta oscillations are a biomarker for bradykinesia and rigidity in Parkinson's disease (PD), incorporated as a feedback signal in adaptive deep brain stimulation with potential for guiding electrode contact selection. Understanding their longitudinal stability is essential for successful clinical implementation.

OBJECTIVES

We aimed to analyze the long-term dynamics of beta peak parameters and beta power distribution along electrodes.

METHODS

We recorded local field potentials from 12 channels per hemisphere of 33 PD patients at rest, in a therapy-off state at two to four sessions (0, 3, 12, 18-44 months) post-surgery. We analyzed bipolar beta power (13-35 Hz) and estimated monopolar beta power in subgroups with consistent recordings.

RESULTS

During the initial 3 months, beta peak power increased (P < 0.0001). While detection of high-beta peaks was more consistent, low- and high-beta peak frequencies shifted substantially in some hemispheres during all periods. Spatial distribution of beta power correlated over time. Maximal beta power across segmented contact levels and directions was significantly stable compared with chance and increased in stability over time. Active contacts for therapeutic stimulation showed consistently higher normalized beta power than inactive contacts (P < 0.0001).

CONCLUSIONS

Our findings indicate that beta power is a stable chronic biomarker usable for beta-guided programming. For adaptive stimulation, high-beta peaks might be more reliable over time. Greater stability of beta power, center frequency, and spatial distribution beyond an initial stabilization period suggests that the microlesional effect significantly impacts neuronal oscillations, which should be considered in routine clinical practice when using beta activity for automated programming algorithms. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Alpha and high beta subthalamic intermittent activity correlates with freezing of gait severity in Parkinson's disease

INTRODUCTION

Freezing of gait (FOG) is a disabling symptom that affects over half of Parkinson's disease patients (PD) and hinders the ability to walk. Subthalamic nucleus (STN) deep brain stimulation (DBS) effectiveness in ameliorating the FOG remains controversial, lacking a reliable electrophysiological biomarker from local field potentials (LFP).

METHODS

The LFP-STN rhythms bandpower and dynamics were characterized at rest across groups in a cohort of 23 patients (14 with FOG, and 9 without, n-FOG).

RESULTS

FOG patients presented enhanced alpha bandpower (FOG vs. n-FOG: 0.331 ± 0.087 vs. 0.248 ± 0.089; p = 0.011) and intermittent (burst) alpha amplitude (FOG vs. n-FOG: 0.610 ± 0.068 vs. 0.524 ± 0.086; p = 0.005). Both intermittent alpha (r = 0.330, p = 0.046) and intermittent high beta amplitude (r = 0.415, p = 0.011) correlated with the FOG score. Alpha burst amplitude correlated with FOG severity (r = 0.479, p = 0.003), and high beta burst amplitude inversely correlated (r = -0.411, p = 0.014) with the performance-oriented mobility assessment (POMA) index.

CONCLUSION

These results suggest that alpha and high beta subthalamic oscillations impact FOG symptoms.

SIGNIFICANCE

The investigation suggests potentially newer co-biomarkers of FOG to guide multi-rhythm paradigms in DBS treatment.

Local Field Potential Biomarkers of Non-Motor Symptoms in Parkinson's Disease: Insights From the Subthalamic Nucleus in Deep Brain Stimulation

Non-motor symptoms can severely affect the quality of life of Parkinson's disease-afflicted patients, with the most common ones being pain, sleep impairments, and neuropsychiatric manifestations. In advanced cases, complex fluctuations of motor and non-motor symptoms can occur despite optimal medication. Research on deep brain stimulation of the subthalamic nucleus suggests that it may provide benefits for treating non-motor symptoms in addition to improving motor symptoms. With recent advancements in deep brain stimulation technology, simultaneous recording of local field potentials and delivery of therapeutic stimulation is possible. This opens new possibilities for better understanding the pathophysiology of non-motor symptoms in Parkinson's disease and for identifying potential electrophysiological biomarkers that accurately represent these symptoms. Specifically, this review aims to highlight potential local field potential biomarkers of non-motor symptoms in the subthalamic nucleus. The main findings indicate that activities in the beta frequency band are associated with nociception and sleep impairments such as insomnia and rapid eye movement sleep behavior disorders. Additionally, activities in the theta and alpha frequency bands seem to reflect neurocognitive manifestations, including depression and impulse control disorders. A better understanding of these biomarkers could improve the clinical management of non-motor symptoms in Parkinson's disease. They hold promise for adjusting deep brain stimulation parameters in open-loop settings and might eventually be applied in closed-loop deep brain stimulation systems, though their true impact remains uncertain.

Subthalamic Activity Is Associated With Proactive Inhibition in Parkinson's Disease Patients

The subthalamic nucleus (STN) is a key element of the indirect pathway of the basal ganglia (BG) and an effective target for improving motor symptoms in Parkinson's disease (PD) using deep brain stimulation (DBS). While dopamine neuron loss in PD results in a net shift towards increased inhibitory output from the BG, the precise mechanisms by which STN contributes to diminished movement remain unclear due to the complexity and multiplicity of processes underlying response inhibition. We used a modified Go/NoGo task varying uncertainty about Go or NoGo responses to determine how changes in response inhibition are related to STN local field potentials measured in 19 PD patients operated for STN-DBS. When engaged in the task, low-frequency band (LFB, 2-7 Hz; including the theta band, 4-7 Hz) power was significantly increased by dopamine treatment. LFB power significantly increased when there was uncertainty about the requirement of executing or withholding a response compared to when a response was certain. Increases in LFB power in individual trials were also significantly associated with faster reaction times. By contrast, beta band (12-30 Hz) power exhibited an inverted profile: It was significantly decreased by dopamine treatment, increased by response certainty and associated with slower reaction times. Our results suggest that STN low-frequency activity during voluntary behaviour may complement and enhance information obtained from the beta band and should be considered as a possible biomarker for the regulation of inhibition in uncertain contexts.

Subthalamic Nucleus Deep Brain Stimulation in the Beta Frequency Range Boosts Cortical Beta Oscillations and Slows Down Movement

Recordings from Parkinson's disease (PD) patients show strong beta-band oscillations (13-35 Hz), which can be modulated by deep brain stimulation (DBS). While high-frequency DBS (>100 Hz) ameliorates motor symptoms and reduces beta activity in the basal ganglia and motor cortex, the effects of low-frequency DBS (<30 Hz) are less clear. Clarifying these effects is relevant for the debate about the role of beta oscillations in motor slowing, which might be causal or epiphenomenal. Here, we investigated how subthalamic nucleus (STN) beta-band DBS affects cortical beta oscillations and motor performance. We recorded the magnetoencephalogram of 14 PD patients (nine males) with DBS implants while on their usual medication. Following a baseline recording (DBS OFF), we applied bipolar DBS at beta frequencies (10, 16, 20, 26, and 30 Hz) via the left electrode in a cyclic fashion, turning stimulation on (5 s) and off (3 s) repeatedly. Cyclic stimulation was applied at rest and during right-hand finger tapping. In the baseline recording, we observed a negative correlation between the strength of hemispheric beta power lateralization and the tap rate. Importantly, beta-band DBS accentuated the lateralization and reduced the tap rate proportionally. The change in lateralization was specific to the alpha/beta range (8-26 Hz), outlasted stimulation, and did not depend on the stimulation frequency, suggesting a remote-induced response rather than entrainment. Our study demonstrates that cortical beta oscillations can be manipulated by STN beta-band DBS. This manipulation has consequences for motor performance, supporting a causal role of beta oscillations.

Motor cortex stimulation ameliorates parkinsonian locomotor deficits: effectual and mechanistic differences from subthalamic modulation

Subthalamic deep brain stimulation (STN DBS) has been a therapeutic choice for Parkinson's disease (PD). We found that epidural motor cortex stimulation (MCS) with sustained positive (hyperpolarizing) currents could also consistently ameliorate the locomotor deficits in parkinsonian animals, rectifying the pathological paucity in both discharging unit varieties and movement-dependent spatiotemporal activity pattern changes in motor cortex (MC). Mechanistically, MCS hyperpolarizes both glutamatergic pyramidal neurons (PN) and GABAergic interneurons (IN) and consequently partly relieves PN from IN's control. MC discharging units are thus enlarged with enhanced PN burst discharges against a relatively silenced background, presumably compensating for the hypoactive striatal selection to restore the MC activity changes upon movement. Behaviorally, MCS retains interim short pauses like normal locomotor behaviors, in contrast to the propensity of abnormal "restlessness" with STN DBS. Individually designed MCS, alone or in combination with STN DBS and dopaminergic therapy, may provide an optimal therapeutic approach for PD.

Field-Programmable Gate Array-Based Ultra-Low Power Discrete Fourier Transforms for Closed-Loop Neural Sensing

Digital implementations of discrete Fourier transforms (DFT) are a mainstay in feature assessment of recorded biopotentials, particularly in the quantification of biomarkers of neurological disease state for adaptive deep brain stimulation. Fast Fourier transform (FFT) algorithms and architectures present a substantial power demand from onboard batteries in implantable medical devices, necessitating the development of ultra-low power Fourier transform methods in resource-constrained environments. Numerous FFT architectures aim to optimize power and resource demand through computational efficiency; however, prioritizing the reduction of logic complexity at the cost of additional computations can be equally or more effective. This paper introduces a minimal architecture single-delay feedback discrete Fourier transform (mSDF-DFT) for use in ultra-low-power field programmable gate array applications and shows energy and power improvements over state-of-the-art FFT methods. We observe a 33% reduction in dynamic power and 4% reduction in resource utilization in a neural sensing application when compared to state-of-the-art FFT algorithms. While designed for use in closed-loop deep brain stimulation and medical device implementations, the mSDF-DFT is also easily extendable to any ultra-low power embedded application.

Electrophysiological approaches to informing therapeutic interventions with deep brain stimulation

Neuromodulation therapy comprises a range of non-destructive and adjustable methods for modulating neural activity using electrical stimulations, chemical agents, or mechanical interventions. Here, we discuss how electrophysiological brain recording and imaging at multiple scales, from cells to large-scale brain networks, contribute to defining the target location and stimulation parameters of neuromodulation, with an emphasis on deep brain stimulation (DBS).

Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field

To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems. The Detrended Fluctuation Analysis (DFA) exponent is chosen as the classification exponent, and the disparities between indicators representing distinct seizure states and the classification efficacy of rudimentary machine learning models are computed. The DFA exponent exhibited a statistically significant variation among the pre-ictal, ictal period, and post-ictal stages. The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models, whereas the Naive Bayesian model necessitates the least amount of computational and storage space. The set of DFA exponents is employed as an intermediary variable in the machine learning process. The resultant model possesses the capability to function as a feedback trigger program for electrical stimulation systems of the feedback variety, specifically within the domain of neural modulation in epilepsy.

Supraspinal contributions to defective antagonistic inhibition and freezing of gait in Parkinson's disease

The neuromuscular circuit mechanisms of freezing of gait in Parkinson's disease have received little study. Technological progress enables researchers chronically to sense local field potential activity of the basal ganglia in patients while walking. To study subthalamic activity and the circuit processes of supraspinal contributions to spinal motor integration, we recorded local field potentials, surface EMG of antagonistic leg muscles and gait kinematics in patients while walking and freezing. To evaluate the specificity of our findings, we controlled our findings to internally generated volitional stops. We found specific activation-deactivation abnormalities of oscillatory activity of the subthalamic nucleus both before and during a freeze. Furthermore, we were able to show with synchronization analyses that subthalamo-spinal circuits entrain the spinal motor neurons to a defective timing and activation pattern. The main neuromuscular correlates when turning into freezing were as follows: (i) disturbed reciprocity between antagonistic muscles; (ii) increased co-contraction of the antagonists; (iii) defective activation and time pattern of the gastrocnemius muscle; and (iv) increased subthalamo-muscular coherence with the gastrocnemius muscles before the freeze. Beyond the pathophysiological insights into the supraspinal mechanisms contributing to freezing of gait, our findings have potential to inform the conceptualization of future neurorestorative therapies.

A framework for translational therapy development in deep brain stimulation

Deep brain stimulation (DBS) is an established treatment for motor disorders like Parkinson's disease, but its mechanisms and effects on neurons and networks are not fully understood, limiting research-driven progress. This review presents a framework that combines neurophysiological insights and translational research to enhance DBS therapy, emphasizing biomarkers, device technology, and symptom-specific neuromodulation. It also examines the role of animal research in improving DBS, while acknowledging challenges in clinical translation.

Subthalamic stimulation causally modulates human voluntary decision-making to stay or go

The voluntary nature of decision-making is fundamental to human behavior. The subthalamic nucleus is important in reactive decision-making, but its role in voluntary decision-making remains unclear. We recorded from deep brain stimulation subthalamic electrodes time-locked with acute stimulation using a Go/Nogo task to assess voluntary action and inaction. Beta oscillations during voluntary decision-making were temporally dissociated from motor function. Parkinson's patients showed an inaction bias with high beta and intermediate physiological states. Stimulation reversed the inaction bias highlighting its causal nature, and shifting physiology closer to reactive choices. Depression was associated with higher alpha during Voluntary-Nogo characterized by inaction or inertial status quo maintenance whereas apathy had higher beta-gamma during voluntary action or impaired effortful initiation of action. Our findings suggest the human subthalamic nucleus causally contributes to voluntary decision-making, possibly through threshold gating or toggling mechanisms, with stimulation shifting towards voluntary action and suggest biomarkers as potential clinical predictors.

Chronic adaptive deep brain stimulation versus conventional stimulation in Parkinson's disease: a blinded randomized feasibility trial

Deep brain stimulation (DBS) is a widely used therapy for Parkinson's disease (PD) but lacks dynamic responsiveness to changing clinical and neural states. Feedback control might improve therapeutic effectiveness, but the optimal control strategy and additional benefits of 'adaptive' neurostimulation are unclear. Here we present the results of a blinded randomized cross-over pilot trial aimed at determining the neural correlates of specific motor signs in individuals with PD and the feasibility of using these signals to drive adaptive DBS. Four male patients with PD were recruited from a population undergoing DBS implantation for motor fluctuations, with each patient receiving adaptive DBS and continuous DBS. We identified stimulation-entrained gamma oscillations in the subthalamic nucleus or motor cortex as optimal markers of high versus low dopaminergic states and their associated residual motor signs in all four patients. We then demonstrated improved motor symptoms and quality of life with adaptive compared to clinically optimized standard stimulation. The results of this pilot trial highlight the promise of personalized adaptive neurostimulation in PD based on data-driven selection of neural signals. Furthermore, these findings provide the foundation for further larger clinical trials to evaluate the efficacy of personalized adaptive neurostimulation in PD and other neurological disorders. ClinicalTrials.gov registration: NCT03582891 .

Beta bursts in the parkinsonian cortico-basal ganglia network form spatially discrete ensembles

Defining spatial synchronisation of pathological beta oscillations is important, given that many theories linking them to parkinsonian symptoms propose a reduction in the dimensionality of the coding space within and/or across cortico-basal ganglia structures. Such spatial synchronisation could arise from a single process, with widespread entrainment of neurons to the same oscillation. Alternatively, the partially segregated structure of cortico-basal ganglia loops could provide a substrate for multiple ensembles that are independently synchronized at beta frequencies. Addressing this question requires an analytical approach that identifies groups of signals with a statistical tendency for beta synchronisation, which is unachievable using standard pairwise measures. Here, we utilized such an approach on multichannel recordings of background unit activity (BUA) in the external globus pallidus (GP) and subthalamic nucleus (STN) in parkinsonian rats. We employed an adapted version of a principle and independent component analysis-based method commonly used to define assemblies of single neurons (i.e., neurons that are synchronized over short timescales). This analysis enabled us to define whether changes in the power of beta oscillations in local ensembles of neurons (i.e., the BUA recorded from single contacts) consistently covaried over time, forming a "beta ensemble". Multiple beta ensembles were often present in single recordings and could span brain structures. Membership of a beta ensemble predicted significantly higher levels of short latency (<5 ms) synchrony in the raw BUA signal and phase synchronisation with cortical beta oscillations, suggesting that they comprised clusters of neurons that are functionally connected at multiple levels, despite sometimes being non-contiguous in space. Overall, these findings suggest that beta oscillations do not comprise of a single synchronisation process, but rather multiple independent activities that can bind both spatially contiguous and non-contiguous pools of neurons within and across structures. As previously proposed, such ensembles provide a substrate for beta oscillations to constrain the coding space of cortico-basal ganglia circuits.

Adaptive vs. Conventional Deep Brain Stimulation: One-Year Subthalamic Recordings and Clinical Monitoring in a Patient with Parkinson's Disease

Conventional DBS (cDBS) for Parkinson's disease uses constant, predefined stimulation parameters, while the currently available adaptive DBS (aDBS) provides the possibility of adjusting current amplitude with respect to subthalamic activity in the beta band (13-30 Hz). This preliminary study on one patient aims to describe how these two stimulation modes affect basal ganglia dynamics and, thus, behavior in the long term. We collected clinical data (UPDRS-III and -IV) and subthalamic recordings of one patient with Parkinson's disease treated for one year with aDBS, alternated with short intervals of cDBS. Moreover, after nine months, the patient discontinued all dopaminergic drugs while keeping aDBS. Clinical benefits of aDBS were superior to those of cDBS, both with and without medications. This improvement was paralleled by larger daily fluctuations of subthalamic beta activity. Moreover, with aDBS, subthalamic beta activity decreased during asleep with respect to awake hours, while it remained stable in cDBS. These preliminary data suggest that aDBS might be more effective than cDBS in preserving the functional role of daily beta fluctuations, thus leading to superior clinical benefit. Our results open new perspectives for a restorative brain network effect of aDBS as a more physiological, bidirectional, brain-computer interface.

Reduced subthalamic and subthalamic-cortical coherences associated with the therapeutic carryover effect of coordinated reset deep brain stimulation

Coordinated reset deep brain stimulation (CR DBS), a promising treatment for Parkinson's disease (PD), is hypothesized to desynchronize neuronal populations. However, little in vivo data probes this hypothesis. In a parkinsonian nonhuman primate, we found that subthalamic CR DBS suppressed subthalamic and cortical-subthalamic coherences in the beta band, correlating with motor improvements. Our results support the desynchronizing mechanism of CR DBS and propose potential biomarkers for closed-loop CR DBS.

Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) clinical trial

Adaptive deep brain stimulation (aDBS) is an emerging advancement in DBS technology; however, local field potential (LFP) signal rate detection sufficient for aDBS algorithms and the methods to set-up aDBS have yet to be defined. Here we summarize sensing data and aDBS programming steps associated with the ongoing Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) pivotal trial (NCT04547712). Sixty-eight patients were enrolled with either subthalamic nucleus or globus pallidus internus DBS leads connected to a Medtronic PerceptTM PC neurostimulator. During the enrollment and screening procedures, a LFP (8-30 Hz, ≥1.2 µVp) control signal was identified by clinicians in 84.8% of patients on medication (65% bilateral signal), and in 92% of patients off medication (78% bilateral signal). The ADAPT-PD trial sensing data indicate a high LFP signal presence in both on and off medication states of these patients, with bilateral signal in the majority, regardless of PD phenotype.

Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents

Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.

Transient Increases in Neural Oscillations and Motor Deficits in a Mouse Model of Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms like tremors and bradykinesia. PD's pathology involves the aggregation of α-synuclein and loss of dopaminergic neurons, leading to altered neural oscillations in the cortico-basal ganglia-thalamic network. Despite extensive research, the relationship between the motor symptoms of PD and transient changes in brain oscillations before and after motor tasks in different brain regions remain unclear. This study aimed to investigate neural oscillations in both healthy and PD model mice using local field potential (LFP) recordings from multiple brain regions during rest and locomotion. The histological evaluation confirmed the significant dopaminergic neuron loss in the injection side in 6-OHDA lesioned mice. Behavioral tests showed motor deficits in these mice, including impaired coordination and increased forelimb asymmetry. The LFP analysis revealed increased delta, theta, alpha, beta, and gamma band activity in 6-OHDA lesioned mice during movement, with significant increases in multiple brain regions, including the primary motor cortex (M1), caudate-putamen (CPu), subthalamic nucleus (STN), substantia nigra pars compacta (SNc), and pedunculopontine nucleus (PPN). Taken together, these results show that the motor symptoms of PD are accompanied by significant transient increases in brain oscillations, especially in the gamma band. This study provides potential biomarkers for early diagnosis and therapeutic evaluation by elucidating the relationship between specific neural oscillations and motor deficits in PD.

Subthalamic DBS does not restore deficits in corticospinal suppression during movement preparation in Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) patients exhibit changes in mechanisms underlying movement preparation, particularly the suppression of corticospinal excitability - termed "preparatory suppression" - which is thought to facilitate movement execution in healthy individuals. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) being an attractive treatment for advanced PD, we aimed to study the potential contribution of this nucleus to PD-related changes in such corticospinal dynamics.

METHODS

On two consecutive days, we applied single-pulse transcranial magnetic stimulation to the primary motor cortex of 20 advanced PD patients treated with bilateral STN-DBS (ON vs. OFF), as well as 20 healthy control subjects. Motor-evoked potentials (MEPs) were elicited at rest or during movement preparation in an instructed-delay choice reaction time task including left- or right-hand responses. Preparatory suppression was assessed by expressing MEPs during movement preparation relative to rest.

RESULTS

PD patients exhibited a deficit in preparatory suppression when it was probed on the responding hand side, particularly when this corresponded to their most-affected hand, regardless of their STN-DBS status.

CONCLUSIONS

Advanced PD patients displayed a reduction in preparatory suppression which was not restored by STN-DBS.

SIGNIFICANCE

The current findings confirm that PD patients lack preparatory suppression, as previously reported. Yet, the fact that this deficit was not responsive to STN-DBS calls for future studies on the neural source of this regulatory mechanism during movement preparation.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

SIGNIFICANCE

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

Deep Brain Stimulation restores information processing in parkinsonian cortical networks

Parkinson's disease (PD) is a neurodegenerative disorder associated with alterations of neural activity and information processing primarily in the basal ganglia and cerebral cortex. Deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) is the most effective therapy when patients experience levodopa-induced motor complications. A growing body of evidence points towards a cortical effect of STN-DBS, restoring key electrophysiological markers, such as excessive beta band oscillations, commonly observed in PD. However, the mechanisms of STN-DBS remain elusive. Here, we aim to better characterize the cortical substrates underlying STN-DBS-induced improvement in motor symptoms. We recorded electroencephalograms (EEG) from PD patients and found that, although apparent EEG features were not different with or without therapy, EEG signals could more accurately predict limb movements under STN-DBS. To understand the origins of this enhanced information transmission under STN-DBS in the human EEG data, we investigated the information capacity and dynamics of a variety of computational models of cortical networks. The extent of improvement in decoding accuracy of complex naturalistic inputs under STN-DBS depended on the synaptic parameters of the network as well as its excitability and synchronization levels. Additionally, decoding accuracy could be optimized by adjusting STN-DBS parameters. Altogether, this work draws a comprehensive link between known alterations in cortical activity and the degradation of information processing capacity, as well as its restoration under DBS. These results also offer new perspectives for optimizing STN-DBS parameters based on clinically accessible measures of cortical information processing capacity.

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

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

Pain-Insomnia-Depression Syndrome: Triangular Relationships, Pathobiological Correlations, Current Treatment Modalities, and Future Direction

Pain-insomnia-depression syndrome (PIDS) is a complex triad of chronic pain, insomnia, and depression that has profound effects on an individual's quality of life and mental health. The pathobiological context of PIDS involves complex neurobiological and physiological mechanisms, including alterations in neurotransmitter systems and impaired pain processing pathways. The first-line therapeutic approaches for the treatment of chronic pain, depression, and insomnia are a combination of pharmacological and non-pharmacological therapies. In cases where patients do not respond adequately to these treatments, additional interventions such as deep brain stimulation (DBS) may be required. Despite advances in understanding and treatment, there are still gaps in knowledge that need to be addressed. To improve our understanding, future research should focus on conducting longitudinal studies to uncover temporal associations, identify biomarkers and genetic markers associated with PIDS, examine the influence of psychosocial factors on treatment responses, and develop innovative interventions that address the complex nature of PIDS. The aim of this study is to provide a comprehensive overview of these components and to discuss their underlying pathobiological relationships.

Why so slow? Models of parkinsonian bradykinesia

Bradykinesia, or slowness of movement, is a defining feature of Parkinson disease (PD) and a major contributor to the negative effects on quality of life associated with this disorder and related conditions. A dominant pathophysiological model of bradykinesia in PD has existed for approximately 30 years and has been the basis for the development of several therapeutic interventions, but accumulating evidence has made this model increasingly untenable. Although more recent models have been proposed, they also appear to be flawed. In this Perspective, I consider the leading prior models of bradykinesia in PD and argue that a more functionally related model is required, one that considers changes that disrupt the fundamental process of accurate information transmission. In doing so, I review emerging evidence of network level functional connectivity changes, information transfer dysfunction and potential motor code transmission error and present a novel model of bradykinesia in PD that incorporates this evidence. I hope that this model may reconcile inconsistencies in its predecessors and encourage further development of therapeutic interventions.

Computational models advance deep brain stimulation for Parkinson's disease

Deep brain stimulation(DBS) has become an effective intervention for advanced Parkinson's disease(PD), but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia (BG), the abnormal pathological changes of the BG in PD, and how computational models can help understand and advance DBS. We also describe two types of models: mathematical theoretical models and clinical predictive models. Mathematical theoretical models simulate neurons or neural networks of BG to shed light on the mechanistic principle underlying DBS, while clinical predictive models focus more on patients' outcomes, helping to adapt treatment plans for each patient and advance novel electrode designs. Finally, we provide insights and an outlook on future technologies.

A Computational Model of Deep Brain Stimulation for Parkinson's Disease Tremor and Bradykinesia

Parkinson's disease (PD) is a progressive neurological disorder that is typically characterized by a range of motor dysfunctions, and its impact extends beyond physical abnormalities into emotional well-being and cognitive symptoms. The loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) leads to an array of dysfunctions in the functioning of the basal ganglia (BG) circuitry that manifests into PD. While active research is being carried out to find the root cause of SNc cell death, various therapeutic techniques are used to manage the symptoms of PD. The most common approach in managing the symptoms is replenishing the lost dopamine in the form of taking dopaminergic medications such as levodopa, despite its long-term complications. Another commonly used intervention for PD is deep brain stimulation (DBS). DBS is most commonly used when levodopa medication efficacy is reduced, and, in combination with levodopa medication, it helps reduce the required dosage of medication, prolonging the therapeutic effect. DBS is also a first choice option when motor complications such as dyskinesia emerge as a side effect of medication. Several studies have also reported that though DBS is found to be effective in suppressing severe motor symptoms such as tremors and rigidity, it has an adverse effect on cognitive capabilities. Henceforth, it is important to understand the exact mechanism of DBS in alleviating motor symptoms. A computational model of DBS stimulation for motor symptoms will offer great insights into understanding the mechanisms underlying DBS, and, along this line, in our current study, we modeled a cortico-basal ganglia circuitry of arm reaching, where we simulated healthy control (HC) and PD symptoms as well as the DBS effect on PD tremor and bradykinesia. Our modeling results reveal that PD tremors are more correlated with the theta band, while bradykinesia is more correlated with the beta band of the frequency spectrum of the local field potential (LFP) of the subthalamic nucleus (STN) neurons. With a DBS current of 220 pA, 130 Hz, and a 100 microsecond pulse-width, we could found the maximum therapeutic effect for the pathological dynamics simulated using our model using a set of parameter values. However, the exact DBS characteristics vary from patient to patient, and this can be further studied by exploring the model parameter space. This model can be extended to study different DBS targets and accommodate cognitive dynamics in the future to study the impact of DBS on cognitive symptoms and thereby optimize the parameters to produce optimal performance effects across modalities. Combining DBS with rehabilitation is another frontier where DBS can reduce symptoms such as tremors and rigidity, enabling patients to participate in their therapy. With DBS providing instant relief to patients, a combination of DBS and rehabilitation can enhance neural plasticity. One of the key motivations behind combining DBS with rehabilitation is to expect comparable results in motor performance even with milder DBS currents.

Asymmetries of the subthalamic activity in Parkinson's disease: phase-amplitude coupling among local field potentials

The role of brain asymmetries of dopaminergic neurons in motor symptoms of Parkinson's disease is still undefined. Local field recordings from the subthalamic nucleus revealed some neurophysiological biomarkers of the disease: increased beta activity, increased low-frequency activity and high-frequency oscillations. Phase-amplitude coupling coordinates the timing of neuronal activity and allows determining the mechanism for communication within distinct regions of the brain. In this study, we discuss the use of phase-amplitude coupling to assess the differences between the two hemispheres in a cohort of 24 patients with Parkinson's disease before and after levodopa administration. Subthalamic low- (12-20 Hz) and high-beta (20-30 Hz) oscillations were compared with low- (30-45 Hz), medium- (70-100 Hz) and high-frequency (260-360 Hz) bands. We found a significant beta-phase-amplitude coupling asymmetry between left and right and an opposite-side-dependent effect of the pharmacological treatment, which is associated with the reduction of motor symptoms. In particular, high coupling between high frequencies and high-beta oscillations was found during the OFF condition (P < 0.01) and a low coupling during the ON state (P < 0.0001) when the right subthalamus was assessed; exactly the opposite happened when the left subthalamus was considered in the analysis, showing a lower coupling between high frequencies and high-beta oscillations during the OFF condition (P < 0.01), followed by a higher one during the ON state (P < 0.01). Interestingly, these asymmetries are independent of the motor onset side, either left or right. These findings have important implications for neural signals that may be used to trigger adaptive deep brain stimulation in Parkinson's and could provide more exhaustive insights into subthalamic dynamics.

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.

The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition

Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD.

Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson's disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson's disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Subthalamic Nucleus Deep Brain Stimulation Restores Motor and Sensorimotor Cortical Neuronal Oscillatory Activity in the Free-Moving 6-Hydroxydopamine Lesion Rat Parkinson Model

OBJECTIVES

Enhanced beta oscillations in cortical-basal ganglia (BG) thalamic circuitries have been linked to clinical symptoms of Parkinson's disease. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces beta band activity in BG regions, whereas little is known about activity in cortical regions. In this study, we investigated the effect of STN DBS on the spectral power of oscillatory activity in the motor cortex (MCtx) and sensorimotor cortex (SMCtx) by recording via an electrocorticogram (ECoG) array in free-moving 6-hydroxydopamine (6-OHDA) lesioned rats and sham-lesioned controls.

MATERIALS AND METHODS

Male Sprague-Dawley rats (250-350 g) were injected either with 6-OHDA or with saline in the right medial forebrain bundle, under general anesthesia. A stimulation electrode was then implanted in the ipsilateral STN, and an ECoG array was placed subdurally above the MCtx and SMCtx areas. Six days after the second surgery, the free-moving rats were individually recorded in three conditions: 1) basal activity, 2) during STN DBS, and 3) directly after STN DBS.

RESULTS

In 6-OHDA-lesioned rats (N = 8), the relative power of theta band activity was reduced, whereas activity of broad-range beta band (12-30 Hz) along with two different subbeta bands, that is, low (12-30 Hz) and high (20-30 Hz) beta band and gamma band, was higher in MCtx and SMCtx than in sham-lesioned controls (N = 7). This was, to some extent, reverted toward control level by STN DBS during and after stimulation. No major differences were found between contacts of the electrode grid or between MCtx and SMCtx.

CONCLUSION

Loss of nigrostriatal dopamine leads to abnormal oscillatory activity in both MCtx and SMCtx, which is compensated by STN stimulation, suggesting that parkinsonism-related oscillations in the cortex and BG are linked through their anatomic connections.

A framework for quantifying the coupling between brain connectivity and heartbeat dynamics: Insights into the disrupted network physiology in Parkinson's disease

Parkinson's disease (PD) often shows disrupted brain connectivity and autonomic dysfunctions, progressing alongside with motor and cognitive decline. Recently, PD has been linked to a reduced sensitivity to cardiac inputs, that is, cardiac interoception. Altogether, those signs suggest that PD causes an altered brain-heart connection whose mechanisms remain unclear. Our study aimed to explore the large-scale network disruptions and the neurophysiology of disrupted interoceptive mechanisms in PD. We focused on examining the alterations in brain-heart coupling in PD and their potential connection to motor symptoms. We developed a proof-of-concept method to quantify relationships between the co-fluctuations of brain connectivity and cardiac sympathetic and parasympathetic activities. We quantified the brain-heart couplings from electroencephalogram and electrocardiogram recordings from PD patients on and off dopaminergic medication, as well as in healthy individuals at rest. Our results show that the couplings of fluctuating alpha and gamma connectivity with cardiac sympathetic dynamics are reduced in PD patients, as compared to healthy individuals. Furthermore, we show that PD patients under dopamine medication recover part of the brain-heart coupling, in proportion with the reduced motor symptoms. Our proposal offers a promising approach to unveil the physiopathology of PD and promoting the development of new evaluation methods for the early stages of the disease.

Fundamentals of deep brain stimulation for Parkinson's disease in clinical practice: part 2

The field of neuromodulation has evolved significantly over the past decade. Developments include novel indications and innovations of hardware, software, and stimulation techniques leading to an expansion in scope and role of these techniques as powerful therapeutic interventions. In this review, which is the second part of an effort to document and integrate the basic fundamentals and recent successful developments in the field, we will focus on classic paradigms for electrode placement as well as new exploratory targets, mechanisms of neuromodulation using this technique and new developments, including focused ultrasound driven ablative procedures.

Towards therapeutic electrophysiological neurofeedback in Parkinson's disease

Neurofeedback (NF) techniques support individuals to self-regulate specific features of brain activity, which has been shown to impact behavior and potentially ameliorate clinical symptoms. Electrophysiological NF (epNF) may be particularly impactful for patients with Parkinson's disease (PD), as evidence mounts to suggest a central role of pathological neural oscillations underlying symptoms in PD. Exaggerated beta oscillations (12-30 Hz) in the basal ganglia-cortical network are linked to motor symptoms (e.g., bradykinesia, rigidity), and beta is reduced by successful therapy with dopaminergic medication and Deep Brain Stimulation (DBS). PD patients also experience non-motor symptoms related to sleep, mood, motivation, and cognitive control. Although less is known about the mechanisms of non-motor symptoms in PD and how to successfully treat them, low frequency neural oscillations (1-12 Hz) in the basal ganglia-cortical network are particularly implicated in non-motor symptoms. Here, we review how cortical and subcortical epNF could be used to target motor and non-motor specific oscillations, and potentially serve as an adjunct therapy that enables PD patients to endogenously control their own pathological neural activities. Recent studies have demonstrated that epNF protocols can successfully support volitional control of cortical and subcortical beta rhythms. Importantly, this endogenous control of beta has been linked to changes in motor behavior. epNF for PD, as a casual intervention on neural signals, has the potential to increase understanding of the neurophysiology of movement, mood, and cognition and to identify new therapeutic approaches for motor and non-motor symptoms.

Transcranial alternating current stimulation improves quality of life in Parkinson's disease: study protocol for a randomized, double-blind, controlled trial

BACKGROUND

The neural cells in the brains of patients with Parkinson's disease (PWP) display aberrant synchronized oscillatory activity within the beta frequency range. Additionally, enhanced gamma oscillations may serve as a compensatory mechanism for motor inhibition mediated by beta activity and also reinstate plasticity in the primary motor cortex affected by Parkinson's disease. Transcranial alternating current stimulation (tACS) can synchronize endogenous oscillations with exogenous rhythms, thereby modulating cortical activity. The objective of this study is to investigate whether the addition of tACS to multidisciplinary intensive rehabilitation treatment (MIRT) can improve symptoms of PWP so as to enhance the quality of life in individuals with Parkinson's disease based on the central-peripheral-central theory.

METHODS

The present study was a randomized, double-blind trial that enrolled 60 individuals with Parkinson's disease aged between 45 and 70 years, who had Hoehn-Yahr scale scores ranging from 1 to 3. Participants were randomly assigned in a 1:1 ratio to either the tACS + MIRT group or the sham-tACS + MIRT group. The trial consisted of a two-week double-blind treatment period followed by a 24-week follow-up period, resulting in a total duration of twenty-six weeks. The primary outcome measured the change in PDQ-39 scores from baseline (T0) to 4 weeks (T2), 12 weeks (T3), and 24 weeks (T4) after completion of the intervention. The secondary outcome assessed changes in MDS-UPDRS III scores at T0, the end of intervention (T1), T2, T3, and T4. Additional clinical assessments and mechanistic studies were conducted as tertiary outcomes.

DISCUSSION

The objective of this study is to demonstrate that tACS can enhance overall functionality and improve quality of life in PWP, based on the framework of MIRT. Additionally, it seeks to establish a potential correlation between these therapeutic effects and neuroplasticity alterations in relevant brain regions. The efficacy of tACS will be assessed during the follow-up period in order to optimize neuroplasticity and enhance its potential impact on rehabilitation efficiency for PWP.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2300071969. Registered on 30 May 2023.

Modulation of DBS-induced cortical responses and movement by the directionality and magnitude of current administered

Subthalamic deep brain stimulation (STN-DBS) is an effective therapy for alleviating motor symptoms in people with Parkinson's disease (PwP), although some may not receive optimal clinical benefits. One potential mechanism of STN-DBS involves antidromic activation of the hyperdirect pathway (HDP), thus suppressing cortical beta synchrony to improve motor function, albeit the precise mechanisms underlying optimal DBS parameters are not well understood. To address this, 18 PwP with STN-DBS completed a 2 Hz monopolar stimulation of the left STN during MEG. MEG data were imaged in the time-frequency domain using minimum norm estimation. Peak vertex time series data were extracted to interrogate the directional specificity and magnitude of DBS current on evoked and induced cortical responses and accelerometer metrics of finger tapping using linear mixed-effects models and mediation analyses. We observed increases in evoked responses (HDP ~ 3-10 ms) and synchronization of beta oscillatory power (14-30 Hz, 10-100 ms) following DBS pulse onset in the primary sensorimotor cortex (SM1), supplementary motor area (SMA) and middle frontal gyrus (MFG) ipsilateral to the site of stimulation. DBS parameters significantly modulated neural and behavioral outcomes, with clinically effective contacts eliciting significant increases in medium-latency evoked responses, reductions in induced SM1 beta power, and better movement profiles compared to suboptimal contacts, often regardless of the magnitude of current applied. Finally, HDP-related improvements in motor function were mediated by the degree of SM1 beta suppression in a setting-dependent manner. Together, these data suggest that DBS-evoked brain-behavior dynamics are influenced by the level of beta power in key hubs of the basal ganglia-cortical loop, and this effect is exacerbated by the clinical efficacy of DBS parameters. Such data provides novel mechanistic and clinical insight, which may prove useful for characterizing DBS programming strategies to optimize motor symptom improvement in the future.

Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction

Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

Real-time field-programmable gate array-based closed-loop deep brain stimulation platform targeting cerebellar circuitry rescues motor deficits in a mouse model of cerebellar ataxia

AIMS

The open-loop nature of conventional deep brain stimulation (DBS) produces continuous and excessive stimulation to patients which contributes largely to increased prevalence of adverse side effects. Cerebellar ataxia is characterized by abnormal Purkinje cells (PCs) dendritic arborization, loss of PCs and motor coordination, and muscle weakness with no effective treatment. We aim to develop a real-time field-programmable gate array (FPGA) prototype targeting the deep cerebellar nuclei (DCN) to close the loop for ataxia using conditional double knockout mice with deletion of PC-specific LIM homeobox (Lhx)1 and Lhx5, resulting in abnormal dendritic arborization and motor deficits.

METHODS

We implanted multielectrode array in the DCN and muscles of ataxia mice. The beneficial effect of open-loop DCN-DBS or closed-loop DCN-DBS was compared by motor behavioral assessments, electromyography (EMG), and neural activities (neurospike and electroencephalogram) in freely moving mice. FPGA board, which performed complex real-time computation, was used for closed-loop DCN-DBS system.

RESULTS

Closed-loop DCN-DBS was triggered only when symptomatic muscle EMG was detected in a real-time manner, which restored motor activities, electroencephalogram activities and neurospike properties completely in ataxia mice. Closed-loop DCN-DBS was more effective than an open-loop paradigm as it reduced the frequency of DBS.

CONCLUSION

Our real-time FPGA-based DCN-DBS system could be a potential clinical strategy for alleviating cerebellar ataxia and other movement disorders.

Detection of evoked resonant neural activity in Parkinson's disease

Objective. This study investigated a machine-learning approach to detect the presence of evoked resonant neural activity (ERNA) recorded during deep brain stimulation (DBS) of the subthalamic nucleus (STN) in people with Parkinson's disease.Approach. Seven binary classifiers were trained to distinguish ERNA from the background neural activity using eight different time-domain signal features.Main results. Nested cross-validation revealed a strong classification performance of 99.1% accuracy, with 99.6% specificity and 98.7% sensitivity to detect ERNA. Using a semi-simulated ERNA dataset, the results show that a signal-to-noise ratio of 15 dB is required to maintain a 90% classifier sensitivity. ERNA detection is feasible with an appropriate combination of signal processing, feature extraction and classifier. Future work should consider reducing the computational complexity for use in real-time applications.Significance. The presence of ERNA can be used to indicate the location of a DBS electrode array during implantation surgery. The confidence score of the detector could be useful for assisting clinicians to adjust the position of the DBS electrode array inside/outside the STN.

Slow-wave sleep dysfunction in mild parkinsonism is associated with excessive beta and reduced delta oscillations in motor cortex

Increasing evidence suggests slow-wave sleep (SWS) dysfunction in Parkinson's disease (PD) is associated with faster disease progression, cognitive impairment, and excessive daytime sleepiness. Beta oscillations (8-35 Hz) in the basal ganglia thalamocortical (BGTC) network are thought to play a role in the development of cardinal motor signs of PD. The role cortical beta oscillations play in SWS dysfunction in the early stage of parkinsonism is not understood, however. To address this question, we used a within-subject design in a nonhuman primate (NHP) model of PD to record local field potentials from the primary motor cortex (MC) during sleep across normal and mild parkinsonian states. The MC is a critical node in the BGTC network, exhibits pathological oscillations with depletion in dopamine tone, and displays high amplitude slow oscillations during SWS. The MC is therefore an appropriate recording site to understand the neurophysiology of SWS dysfunction in parkinsonism. We observed a reduction in SWS quantity (p = 0.027) in the parkinsonian state compared to normal. The cortical delta (0.5-3 Hz) power was reduced (p = 0.038) whereas beta (8-35 Hz) power was elevated (p = 0.001) during SWS in the parkinsonian state compared to normal. Furthermore, SWS quantity positively correlated with delta power (r = 0.43, p = 0.037) and negatively correlated with beta power (r = -0.65, p < 0.001). Our findings support excessive beta oscillations as a mechanism for SWS dysfunction in mild parkinsonism and could inform the development of neuromodulation therapies for enhancing SWS in people with PD.

Impact of Network Topology on Neural Synchrony in a Model of the Subthalamic Nucleus-Globus Pallidus Circuit

Synchronous neural oscillations within the beta frequency range are observed across the parkinsonian basal ganglia network, including within the subthalamic nucleus (STN) - globus pallidus (GPe) subcircuit. The emergence of pathological synchrony in Parkinson's disease is often attributed to changes in neural properties or connection strength, and less often to the network topology, i.e. the structural arrangement of connections between neurons. This study investigates the relationship between network structure and neural synchrony in a model of the STN-GPe circuit comprised of conductance-based spiking neurons. Changes in net synaptic input were controlled for through a synaptic scaling rule, which facilitated separation of the effects of network structure from net synaptic input. Five topologies were examined as structures for the STN-GPe circuit: Watts-Strogatz, preferential attachment, spatial, stochastic block, k-regular random. Beta band synchrony generally increased as the number of connections increased, however the exact relationship was topology specific. Varying the wiring pattern while maintaining a constant number of connections caused network synchrony to be enhanced or suppressed, demonstrating the ability of purely structural changes to alter synchrony. This relationship was well-captured by the algebraic connectivity of the network, the second smallest eigenvalue of the network's Laplacian matrix. The structure-synchrony relationship was further investigated in a network model designed to emulate the action selection role of the STN-GPe circuit. It was found that increasing the number of connections and/or the overlap of action selection channels could lead to a rapid transition to synchrony, which was also predicted by the algebraic connectivity.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.