Neuronal inhibition and synaptic plasticity of basal ganglia neurons in Parkinson's disease

Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA (over hundreds of seconds) with a single neuronal population, and, crucially, with vesicle depletion as one of the key mechanisms behind the ERNA frequency decay in our model. We further validate the proposed model against experimental data from Parkinson's disease patients, where it captures the variations in ERNA frequency and amplitude in response to variable stimulation frequency, amplitude, and to stimulation pulse bursting. We provide a series of predictions from the model that could be the subject of future studies for further validation.

Interrogating basal ganglia circuit function in people with Parkinson's disease and dystonia

Background

The dichotomy between the hypo- versus hyperkinetic nature of Parkinson's disease (PD) and dystonia, respectively, is thought to be reflected in the underlying basal ganglia pathophysiology. In this study, we investigated differences in globus pallidus internus (GPi) neuronal activity, and short- and long-term plasticity of direct pathway projections.

Methods

Using microelectrode recording data collected from the GPi during deep brain stimulation surgery, we compared neuronal spiketrain features between people with PD and those with dystonia, as well as correlated neuronal features with respective clinical scores. Additionally, we characterized and compared readouts of short- and long-term synaptic plasticity using measures of inhibitory evoked field potentials.

Results

GPi neurons were slower, bustier, and less regular in dystonia. In PD, symptom severity positively correlated with the power of low-beta frequency spiketrain oscillations. In dystonia, symptom severity negatively correlated with firing rate and positively correlated with neuronal variability and the power of theta frequency spiketrain oscillations. Dystonia was moreover associated with less long-term plasticity and slower synaptic depression.

Conclusions

We substantiated claims of hyper- versus hypofunctional GPi output in PD versus dystonia, and provided cellular-level validation of the pathological nature of theta and low-beta oscillations in respective disorders. Such circuit changes may be underlain by disease-related differences in plasticity of striato-pallidal synapses.

Funding

This project was made possible with the financial support of Health Canada through the Canada Brain Research Fund, an innovative partnership between the Government of Canada (through Health Canada) and Brain Canada, and of the Azrieli Foundation (LM), as well as a grant from the Banting Research Foundation in partnership with the Dystonia Medical Research Foundation (LM).

Neuroplasticity in Parkinson's disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder, affecting millions of people and rapidly increasing over the last decades. Even though there is no intervention yet to stop the neurodegenerative pathology, many efficient treatment methods are available, including for patients with advanced PD. Neuroplasticity is a fundamental property of the human brain to adapt both to external changes and internal insults and pathological processes. In this paper we examine the current knowledge and concepts concerning changes at network level, cellular level and molecular level as parts of the neuroplastic response to protein aggregation pathology, synapse loss and neuronal loss in PD. We analyse the beneficial, compensatory effects, such as augmentation of nigral neurons efficacy, as well as negative, maladaptive effects, such as levodopa-induced dyskinesia. Effects of physical activity and different treatments on neuroplasticity are considered and the opportunity of biomarkers identification and use is discussed.

Circuit-Specific Deep Brain Stimulation Provides Insights into Movement Control

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

Neuroscience fundamentals relevant to neuromodulation: Neurobiology of deep brain stimulation in Parkinson's disease

Deep Brain Stimulation (DBS) has become a pivotal therapeutic approach for Parkinson's Disease (PD) and various neuropsychiatric conditions, impacting over 200,000 patients. Despite its widespread application, the intricate mechanisms behind DBS remain a subject of ongoing investigation. This article provides an overview of the current knowledge surrounding the local, circuit, and neurobiochemical effects of DBS, focusing on the subthalamic nucleus (STN) as a key target in PD management. The local effects of DBS, once thought to mimic a reversible lesion, now reveal a more nuanced interplay with myelinated axons, neurotransmitter release, and the surrounding microenvironment. Circuit effects illuminate the modulation of oscillatory activities within the basal ganglia and emphasize communication between the STN and the primary motor cortex. Neurobiochemical effects, encompassing changes in dopamine levels and epigenetic modifications, add further complexity to the DBS landscape. Finally, within the context of understanding the mechanisms of DBS in PD, the article highlights the controversial question of whether DBS exerts disease-modifying effects in PD. While preclinical evidence suggests neuroprotective potential, clinical trials such as EARLYSTIM face challenges in assessing long-term disease modification due to enrollment timing and methodology limitations. The discussion underscores the need for robust biomarkers and large-scale prospective trials to conclusively determine DBS's potential as a disease-modifying therapy in PD.

Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus

OBJECTIVE

Deep brain stimulation (DBS) is an effective treatment for movement disorders, including Parkinson disease and essential tremor. However, the underlying mechanisms of DBS remain elusive. Despite the capability of existing models in interpreting experimental data qualitatively, there are very few unified computational models that quantitatively capture the dynamics of the neuronal activity of varying stimulated nuclei-including subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate nucleus (Vim)-across different DBS frequencies.

MATERIALS AND METHODS

Both synthetic and experimental data were used in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work, and the experimental data were provided using single-unit microelectrode recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we developed a novel mathematical model to represent the firing rate of neurons receiving DBS, including neurons in STN, SNr, and Vim-across different DBS frequencies. In our model, the DBS pulses were filtered through a synapse model and a nonlinear transfer function to formulate the firing rate variability. For each DBS-targeted nucleus, we fitted a single set of optimal model parameters consistent across varying DBS frequencies.

RESULTS

Our model accurately reproduced the firing rates observed and calculated from both synthetic and experimental data. The optimal model parameters were consistent across different DBS frequencies.

CONCLUSIONS

The result of our model fitting was in agreement with experimental single-unit MER data during DBS. Reproducing neuronal firing rates of different nuclei of the basal ganglia and thalamus during DBS can be helpful to further understand the mechanisms of DBS and to potentially optimize stimulation parameters based on their actual effects on neuronal activity.

Dopaminergic reinforcement in the motor system: Implications for Parkinson's disease and deep brain stimulation

Millions of people suffer from dopamine-related disorders spanning disturbances in movement, cognition and emotion. These changes are often attributed to changes in striatal dopamine function. Thus, understanding how dopamine signalling in the striatum and basal ganglia shapes human behaviour is fundamental to advancing the treatment of affected patients. Dopaminergic neurons innervate large-scale brain networks, and accordingly, many different roles for dopamine signals have been proposed, such as invigoration of movement and tracking of reward contingencies. The canonical circuit architecture of cortico-striatal loops sparks the question, of whether dopamine signals in the basal ganglia serve an overarching computational principle. Such a holistic understanding of dopamine functioning could provide new insights into symptom generation in psychiatry to neurology. Here, we review the perspective that dopamine could bidirectionally control neural population dynamics, increasing or decreasing their strength and likelihood to reoccur in the future, a process previously termed neural reinforcement. We outline how the basal ganglia pathways could drive strengthening and weakening of circuit dynamics and discuss the implication of this hypothesis on the understanding of motor signs of Parkinson's disease (PD), the most frequent dopaminergic disorder. We propose that loss of dopamine in PD may lead to a pathological brain state where repetition of neural activity leads to weakening and instability, possibly explanatory for the fact that movement in PD deteriorates with repetition. Finally, we speculate on how therapeutic interventions such as deep brain stimulation may be able to reinstate reinforcement signals and thereby improve treatment strategies for PD in the future.

Kinematic Effects of Combined Subthalamic and Dorsolateral Nigral Deep Brain Stimulation in Parkinson's Disease

Background

Additional stimulation of the substantia nigra (SNr) has been proposed to target axial symptoms and gait impairment in patients with Parkinson's disease (PD).

Objective

This study aimed to characterize effects of combined deep brain stimulation (DBS) of the subthalamic nucleus (STN) and SNr on gait performance in PD and to map stimulation sites within the SNr.

Methods

In a double-blinded crossover design, 10 patients with PD and gait impairment underwent clinical examination and kinematic assessment with STN DBS, combined STN+SNr DBS and OFF DBS 30 minutes after reprogramming. To confirm stimulation within the SNr, electrodes, active contacts, and stimulation volumes were modeled in a common space and overlap with atlases of SNr was computed.

Results

Overlap of stimulation volumes with dorsolateral SNr was confirmed for all patients. UPDRS III, scoring of freezing during turning and transitioning, stride length, stride velocity, and range of motion of shank, knee, arm, and trunk as well as peak velocities during turning and transitions and turn duration were improved with STN DBS compared to OFF. On cohort level, no further improvement was observed with combined STN+SNr DBS but additive improvement of spatiotemporal gait parameters was observed in individual subjects.

Conclusions

Combined high frequency DBS of the STN and dorsolateral SNr did not consistently result in additional short-term kinematic or clinical benefit compared to STN DBS. Stimulation intervals, frequency, and patient selection for target symptoms as well as target region within the SNr need further refinement in future trials.

Neuroplasticity in levodopa-induced dyskinesias: An overview on pathophysiology and therapeutic targets

Levodopa-induced dyskinesias (LIDs) are a common complication in patients with Parkinson's disease (PD). A complex cascade of electrophysiological and molecular events that induce aberrant plasticity in the cortico-basal ganglia system plays a key role in the pathophysiology of LIDs. In the striatum, multiple neurotransmitters regulate the different forms of physiological synaptic plasticity to provide it in a bidirectional and Hebbian manner. In PD, impairment of both long-term potentiation (LTP) and long-term depression (LTD) progresses with disease and dopaminergic denervation of striatum. The altered balance between LTP and LTD processes leads to unidirectional changes in plasticity that cause network dysregulation and the development of involuntary movements. These alterations have been documented, in both experimental models and PD patients, not only in deep brain structures but also at motor cortex. Invasive and non-invasive neuromodulation treatments, as deep brain stimulation, transcranial magnetic stimulation, or transcranial direct current stimulation, may provide strategies to modulate the aberrant plasticity in the cortico-basal ganglia network of patients affected by LIDs, thus restoring normal neurophysiological functioning and treating dyskinesias. In this review, we discuss the evidence for neuroplasticity impairment in experimental PD models and in patients affected by LIDs, and potential neuromodulation strategies that may modulate aberrant plasticity.

Neuronal and synaptic adaptations underlying the benefits of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) is a well-established and effective treatment for patients with advanced Parkinson's disease (PD), yet its underlying mechanisms remain enigmatic. Optogenetics, primarily conducted in animal models, provides a unique approach that allows cell type- and projection-specific modulation that mirrors the frequency-dependent stimulus effects of DBS. Opto-DBS research in animal models plays a pivotal role in unraveling the neuronal and synaptic adaptations that contribute to the efficacy of DBS in PD treatment. DBS-induced neuronal responses rely on a complex interplay between the distributions of presynaptic inputs, frequency-dependent synaptic depression, and the intrinsic excitability of postsynaptic neurons. This orchestration leads to conversion of firing patterns, enabling both antidromic and orthodromic modulation of neural circuits. Understanding these mechanisms is vital for decoding position- and programming-dependent effects of DBS. Furthermore, patterned stimulation is emerging as a promising strategy yielding long-lasting therapeutic benefits. Research on the neuronal and synaptic adaptations to DBS may pave the way for the development of more enduring and precise modulation patterns. Advanced technologies, such as adaptive DBS or directional electrodes, can also be integrated for circuit-specific neuromodulation. These insights hold the potential to greatly improve the effectiveness of DBS and advance PD treatment to new levels.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.

Functional brain network features specify DBS outcome for patients with treatment resistant depression

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.

A common neuronal ensemble in nucleus accumbens regulates pain-like behaviour and sleep

A comorbidity of chronic pain is sleep disturbance. Here, we identify a dual-functional ensemble that regulates both pain-like behaviour induced by chronic constrictive injury or complete Freund's adjuvant, and sleep wakefulness, in the nucleus accumbens (NAc) in mice. Specifically, a select population of NAc neurons exhibits increased activity either upon nociceptive stimulation or during wakefulness. Experimental activation of the ensemble neurons exacerbates pain-like (nociceptive) responses and reduces NREM sleep, while inactivation of these neurons produces the opposite effects. Furthermore, NAc ensemble primarily consists of D1 neurons and projects divergently to the ventral tegmental area (VTA) and preoptic area (POA). Silencing an ensemble innervating VTA neurons selectively increases nociceptive responses without affecting sleep, whereas inhibiting ensemble-innervating POA neurons decreases NREM sleep without affecting nociception. These results suggest a common NAc ensemble that encodes chronic pain and controls sleep, and achieves the modality specificity through its divergent downstream circuit targets.

Basal ganglia for beginners: the basic concepts you need to know and their role in movement control

The basal ganglia are a subcortical collection of interacting clusters of cell bodies, and are involved in reward, emotional, and motor circuits. Within all the brain processing necessary to carry out voluntary movement, the basal nuclei are fundamental, as they modulate the activity of the motor regions of the cortex. Despite being much studied, the motor circuit of the basal ganglia is still difficult to understand for many people at all, especially undergraduate and graduate students. This review article seeks to bring the functioning of this circuit with a simple and objective approach, exploring the functional anatomy, neurochemistry, neuronal pathways, related diseases, and interactions with other brain regions to coordinate voluntary movement.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

Differential remodeling of subthalamic projections to basal ganglia output nuclei and locomotor deficits in 6-OHDA-induced hemiparkinsonian mice

The subthalamic nucleus (STN) controls basal ganglia outputs via the substantia nigra pars reticulata (SNr) and the globus pallidus internus (GPi). However, the synaptic properties of these projections and their roles in motor control remain unclear. We show that the STN-SNr and STN-GPi projections differ markedly in magnitude and activity-dependent plasticity despite the existence of collateral STN neurons projecting to both the SNr and GPi. Stimulation of either STN projection reduces locomotion; in contrast, inhibition of either the STN-SNr projection or collateral STN neurons facilitates locomotion. In 6-OHDA-hemiparkinsonian mice, the STN-SNr projection is dramatically attenuated, but the STN-GPi projection is robustly enhanced; apomorphine inhibition of the STN-GPi projection through D2 receptors is significantly augmented and improves locomotion. Optogenetic inhibition of either the STN-SNr or STN-GPi projection improves parkinsonian bradykinesia. These results suggest that the STN-GPi and STN-SNr projections are differentially involved in motor control in physiological and parkinsonian conditions.

Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity

The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.

Transcranial low-intensity ultrasound stimulation for treating central nervous system disorders: A promising therapeutic application

Transcranial ultrasound stimulation is a neurostimulation technique that has gradually attracted the attention of researchers, especially as a potential therapy for neurological disorders, because of its high spatial resolution, its good penetration depth, and its non-invasiveness. Ultrasound can be categorized as high-intensity and low-intensity based on the intensity of its acoustic wave. High-intensity ultrasound can be used for thermal ablation by taking advantage of its high-energy characteristics. Low-intensity ultrasound, which produces low energy, can be used as a means to regulate the nervous system. The present review describes the current status of research on low-intensity transcranial ultrasound stimulation (LITUS) in the treatment of neurological disorders, such as epilepsy, essential tremor, depression, Parkinson's disease (PD), and Alzheimer's disease (AD). This review summarizes preclinical and clinical studies using LITUS to treat the aforementioned neurological disorders and discusses their underlying mechanisms.

Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus

Deep brain stimulation (DBS) is a promising neuromodulation therapy, but the neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high-speed membrane voltage fluorescence imaging of individual hippocampal CA1 neurons during DBS delivered at 40 Hz or 140 Hz, free of electrical interference. DBS powerfully depolarized somatic membrane potentials without suppressing spike rate, especially at 140 Hz. Further, DBS paced membrane voltage and spike timing at the stimulation frequency and reduced timed spiking output in response to hippocampal network theta-rhythmic (3-12 Hz) activity patterns. To determine whether DBS directly impacts cellular processing of inputs, we optogenetically evoked theta-rhythmic membrane depolarization at the soma. We found that DBS-evoked membrane depolarization was correlated with DBS-mediated suppression of neuronal responses to optogenetic inputs. These results demonstrate that DBS produces powerful membrane depolarization that interferes with the ability of individual neurons to respond to inputs, creating an informational lesion.

The role of neurotransmitter systems in mediating deep brain stimulation effects in Parkinson’s disease

Deep brain stimulation (DBS) is among the most successful paradigms in both translational and reverse translational neuroscience. DBS has developed into a standard treatment for movement disorders such as Parkinson’s disease (PD) in recent decades, however, specific mechanisms behind DBS’s efficacy and side effects remain unrevealed. Several hypotheses have been proposed, including neuronal firing rate and pattern theories that emphasize the impact of DBS on local circuitry but detail distant electrophysiological readouts to a lesser extent. Furthermore, ample preclinical and clinical evidence indicates that DBS influences neurotransmitter dynamics in PD, particularly the effects of subthalamic nucleus (STN) DBS on striatal dopaminergic and glutamatergic systems; pallidum DBS on striatal dopaminergic and GABAergic systems; pedunculopontine nucleus DBS on cholinergic systems; and STN-DBS on locus coeruleus (LC) noradrenergic system. DBS has additionally been associated with mood-related side effects within brainstem serotoninergic systems in response to STN-DBS. Still, addressing the mechanisms of DBS on neurotransmitters’ dynamics is commonly overlooked due to its practical difficulties in monitoring real-time changes in remote areas. Given that electrical stimulation alters neurotransmitter release in local and remote regions, it eventually exhibits changes in specific neuronal functions. Consequently, such changes lead to further modulation, synthesis, and release of neurotransmitters. This narrative review discusses the main neurotransmitter dynamics in PD and their role in mediating DBS effects from preclinical and clinical data.

Inferring stimulation induced short-term synaptic plasticity dynamics using novel dual optimization algorithm

Experimental evidence in both human and animal studies demonstrated that deep brain stimulation (DBS) can induce short-term synaptic plasticity (STP) in the stimulated nucleus. Given that DBS-induced STP may be connected to the therapeutic effects of DBS, we sought to develop a computational predictive model that infers the dynamics of STP in response to DBS at different frequencies. Existing methods for estimating STP–either model-based or model-free approaches–require access to pre-synaptic spiking activity. However, in the context of DBS, extracellular stimulation (e.g. DBS) can be used to elicit presynaptic activations directly. We present a model-based approach that integrates multiple individual frequencies of DBS-like electrical stimulation as pre-synaptic spikes and infers parameters of the Tsodyks-Markram (TM) model from post-synaptic currents of the stimulated nucleus. By distinguishing between the steady-state and transient responses of the TM model, we develop a novel dual optimization algorithm that infers the model parameters in two steps. First, the TM model parameters are calculated by integrating multiple frequencies of stimulation to estimate the steady state response of post-synaptic current through a closed-form analytical solution. The results of this step are utilized as the initial values for the second step in which a non-derivative optimization algorithm is used to track the transient response of the post-synaptic potential across different individual frequencies of stimulation. Moreover, in order to confirm the applicability of the method, we applied our algorithm–as a proof of concept–to empirical data recorded from acute rodent brain slices of the subthalamic nucleus (STN) during DBS-like stimulation to infer dynamics of STP for inhibitory synaptic inputs.

Persistent synaptic inhibition of the subthalamic nucleus by high frequency stimulation

BACKGROUND

Deep brain stimulation (DBS) provides symptomatic relief in a growing number of neurological indications, but local synaptic dynamics in response to electrical stimulation that may relate to its mechanism of action have not been fully characterized.

OBJECTIVE

The objectives of this study were to (1) study local synaptic dynamics during high frequency extracellular stimulation of the subthalamic nucleus (STN), and (2) compare STN synaptic dynamics with those of the neighboring substantia nigra pars reticulata (SNr).

METHODS

Two microelectrodes were advanced into the STN and SNr of patients undergoing DBS surgery for Parkinson's disease (PD). Neuronal firing and evoked field potentials (fEPs) were recorded with one microelectrode during stimulation from an adjacent microelectrode.

RESULTS

Inhibitory fEPs could be discerned within the STN and their amplitudes predicted bidirectional effects on neuronal firing (p = .013). There were no differences between STN and SNr inhibitory fEP dynamics at low stimulation frequencies (p > .999). However, inhibitory neuronal responses were sustained over time in STN during high frequency stimulation but not in SNr (p < .001) where depression of inhibitory input was coupled with a return of neuronal firing (p = .003).

INTERPRETATION

Persistent inhibitory input to the STN suggests a local synaptic mechanism for the suppression of subthalamic firing during high frequency stimulation. Moreover, differences in the resiliency versus vulnerability of inhibitory inputs to the STN and SNr suggest a projection source- and frequency-specificity for this mechanism. The feasibility of targeting electrophysiologically-identified neural structures may provide insight into how DBS achieves frequency-specific modulation of neuronal projections.

Differential modulation of subthalamic projection neurons by short-term and long-term electrical stimulation in physiological and parkinsonian conditions

The subthalamic nucleus (STN) is one of the best targets for therapeutic deep brain stimulation (DBS) to control motor symptoms in Parkinson's disease. However, the precise circuitry underlying the effects of STN-DBS remains unclear. To understand how electrical stimulation affects STN projection neurons, we used a retrograde viral vector (AAV-retro-hSyn-eGFP) to label STN neurons projecting to the substantia nigra pars reticulata (SNr) (STN-SNr neurons) or the globus pallidus interna (GPi) (STN-GPi neurons) in mice, and performed whole-cell patch-clamp recordings from these projection neurons in ex vivo brain slices. We found that STN-SNr neurons exhibited stronger responses to depolarizing stimulation than STN-GPi neurons. In most STN-SNr and STN-GPi neurons, inhibitory synaptic inputs predominated over excitatory inputs and electrical stimulation at 20-130 Hz inhibited these neurons in the short term; its longer-term effects varied. 6-OHDA lesion of the nigrostriatal dopaminergic pathway significantly reduced inhibitory synaptic inputs in STN-GPi neurons, but did not change synaptic inputs in STN-SNr neurons; it enhanced short-term electrical-stimulation-induced inhibition in STN-SNr neurons but reversed the effect of short-term electrical stimulation on the firing rate in STN-GPi neurons from inhibitory to excitatory; in both STN-SNr and STN-GPi neurons, it increased the inhibition but attenuated the enhancement of firing rate induced by long-term electrical stimulation. Our results suggest that STN-SNr and STN-GPi neurons differ in their synaptic inputs, their responses to electrical stimulation, and their modification under parkinsonian conditions; STN-GPi neurons may play important roles in both the pathophysiology and therapeutic treatment of Parkinson's disease.

Advances in DBS Technology and Novel Applications: Focus on Movement Disorders

PURPOSE OF REVIEW

Deep brain stimulation (DBS) is an established treatment in several movement disorders, including Parkinson's disease, dystonia, tremor, and Tourette syndrome. In this review, we will review and discuss the most recent findings including but not limited to clinical evidence.

RECENT FINDINGS

New DBS technologies include novel hardware design (electrodes, cables, implanted pulse generators) enabling new stimulation patterns and adaptive DBS which delivers potential stimulation tailored to moment-to-moment changes in the patient's condition. Better understanding of movement disorders pathophysiology and functional anatomy has been pivotal for studying the effects of DBS on the mesencephalic locomotor region, the nucleus basalis of Meynert, the substantia nigra, and the spinal cord. Eventually, neurosurgical practice has improved with more accurate target visualization or combined targeting. A rising research domain emphasizes bridging neuromodulation and neuroprotection. Recent advances in DBS therapy bring more possibilities to effectively treat people with movement disorders. Future research would focus on improving adaptive DBS, leading more clinical trials on novel targets, and exploring neuromodulation effects on neuroprotection.

Suppression of Neuronal Firing Following Antidromic High-Frequency Stimulations on the Neuronal Axons in Rat Hippocampal CA1 Region

High-frequency stimulation (HFS) of electrical pulses has been used to treat certain neurological diseases in brain with commonly utilized effects within stimulation periods. Post-stimulation effects after the end of HFS may also have functions but are lack of attention. To investigate the post-stimulation effects of HFS, we performed experiments in the rat hippocampal CA1 region in vivo. Sequences of 1-min antidromic-HFS (A-HFS) were applied at the alveus fibers. To evaluate the excitability of the neurons, separated orthodromic-tests (O-test) of paired pulses were applied at the Schaffer collaterals in the period of baseline, during late period of A-HFS, and following A-HFS. The evoked potentials of A-HFS pulses and O-test pulses were recorded at the stratum pyramidale and the stratum radiatum of CA1 region by an electrode array. The results showed that the antidromic population spikes (APS) evoked by the A-HFS pulses persisted through the entire 1-min period of 100 Hz A-HFS, though the APS amplitudes decreased significantly from the initial value of 9.9 ± 3.3 mV to the end value of 1.6 ± 0.60 mV. However, following the cessation of A-HFS, a silent period without neuronal firing appeared before the firing gradually recovered to the baseline level. The mean lengths of both silent period and recovery period of pyramidal cells (21.9 ± 22.9 and 172.8 ± 91.6 s) were significantly longer than those of interneurons (11.2 ± 8.9 and 45.6 ± 35.9 s). Furthermore, the orthodromic population spikes (OPS) and the field excitatory postsynaptic potentials (fEPSP) evoked by O-tests at ∼15 s following A-HFS decreased significantly, indicating the excitability of pyramidal cells decreased. In addition, when the pulse frequency of A-HFS was increased to 200, 400, and 800 Hz, the suppression of neuronal activity following A-HFS decreased rather than increased. These results indicated that the neurons with axons directly under HFS can generate a post-stimulation suppression of their excitability that may be due to an antidromic invasion of axonal A-HFS to somata and dendrites. The finding provides new clues to utilize post-stimulation effects generated in the intervals to design intermittent stimulations, such as closed-loop or adaptive stimulations.

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

A practical guide to invasive neurophysiology in patients with deep brain stimulation

Deep brain stimulation (DBS) offers the unique opportunity to record human neural population activity as multiunit activity and local field potentials (LFP) directly from the target area in the depth of the brain. This has led to important discoveries through characterization of pathological activity patterns and identification of motor and cognitive correlates of basal ganglia function in patients with movement disorders. These findings have been covered extensively in a large body of literature, but the technical aspects of microelectrode and LFP recordings in DBS patients are rarely reported. This review summarizes the experience from invasive neurophysiology experiments in over 500 DBS cases in the last 20 years in a single centre. It introduces the basics of intraoperative microelectrode recordings, discusses the neurophysiological and technical aspects of LFP signals and gives and outlook on current and next-generation developments - from sensing enabled implantable devices to combined electrocorticography and LFP recordings during adaptive DBS.

Novel targets in deep brain stimulation for movement disorders

The neurosurgical treatment of movement disorders, primarily via deep brain stimulation (DBS), is a rapidly expanding and evolving field. Although conventional targets including the subthalamic nucleus (STN) and internal segment of the globus pallidus (GPi) for Parkinson's disease and ventral intermediate nucleus of the thalams (VIM) for tremor provide substantial benefit in terms of both motor symptoms and quality of life, other targets for DBS have been explored in an effort to maximize clinical benefit and also avoid undesired adverse effects associated with stimulation. These novel targets primarily include the rostral zona incerta (rZI), caudal zona incerta (cZI)/posterior subthalamic area (PSA), prelemniscal radiation (Raprl), pedunculopontine nucleus (PPN), substantia nigra pars reticulata (SNr), centromedian/parafascicular (CM/PF) nucleus of the thalamus, nucleus basalis of Meynert (NBM), dentato-rubro-thalamic tract (DRTT), dentate nucleus of the cerebellum, external segment of the globus pallidus (GPe), and ventral oralis (VO) complex of the thalamus. However, reports of outcomes utilizing these targets are scattered and disparate. In order to provide a comprehensive resource for researchers and clinicians alike, we have summarized the existing literature surrounding these novel targets, including rationale for their use, neurosurgical techniques where relevant, outcomes and adverse effects of stimulation, and future directions for research.

Combined Subthalamic and Nigral Stimulation Modulates Temporal Gait Coordination and Cortical Gait-Network Activity in Parkinson's Disease

Background

Freezing of gait (FoG) is a disabling burden for Parkinson's disease (PD) patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra (STN+SN DBS) moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear.

Methods

Twelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off (STIM OFF), conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes.

Results

Clinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta (4-8 Hz), alpha (9-13 Hz), and high-beta (21-30 Hz) band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas.

Conclusions

STN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD.

Deep brain stimulation for parkinson's disease induces spontaneous cortical hypersynchrony in extended motor and cognitive networks

The mechanism of action of deep brain stimulation (DBS) to the basal ganglia for Parkinson's disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBS's effects on long range corticocortical synchronization. Here, we use machine learning combined with graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and to healthy controls. We found that turning DBS on increased high beta and gamma band synchrony (26 to 50 Hz) in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. The synchrony in this network was greater in DBS on relative to both DBS off and controls, with no significant difference between DBS off and controls. Turning DBS on also increased network efficiency and strength and subnetwork modularity relative to both DBS off and controls in the beta and gamma band. Thus, unlike DBS's subcortical normalization of pathological basal ganglia activity, it introduces greater synchrony relative to healthy controls in cortical circuitry that includes both motor and non-motor systems. This increased high beta/gamma synchronization may reflect compensatory mechanisms related to DBS's clinical benefits, as well as undesirable non-motor side effects.

People With Parkinson’s Disease and Freezing of Gait Show Abnormal Low Frequency Activity of Antagonistic Leg Muscles

Objective

Freezing of gait is detrimental to patients with idiopathic Parkinson’s disease (PD). Its pathophysiology represents a multilevel failure of motor processing in the cortical, subcortical, and brainstem circuits, ultimately resulting in ineffective motor output of the spinal pattern generator. Electrophysiological studies pointed to abnormalities of oscillatory activity in freezers that covered a broad frequency range including the theta, alpha, and beta bands. We explored muscular frequency domain activity with respect to freezing, and used deep brain stimulation to modulate these rhythms thereby evaluating the supraspinal contributions to spinal motor neuron activity.

Methods

We analyzed 9 PD freezers and 16 healthy controls (HC). We studied the patients after overnight withdrawal of dopaminergic medication with stimulation off, stimulation of the subthalamic nucleus (STN-DBS_only) or the substantia nigra pars reticulate (SNr-DBS_only), respectively. Patients performed a walking paradigm passing a narrow obstacle. We analyzed the frequency-domain spectra of the tibialis anterior (TA) and gastrocnemius (GA) muscles in ‘regular gait’ and during the ‘freezing’ episodes.

Results

In stimulation off, PD freezers showed increased muscle activity of the alpha and low-beta band compared to HC in both TA and GA. This activity increase was present during straight walking and during the freezes to similar extent. STN- but not SNr-DBS decreased this activity and paralleled the clinical improvement of freezing.

Conclusion

We found increased muscle activation of the alpha and lower beta band in PD freezers compared to HC, and this was attenuated with STN-DBS. Future studies may use combined recordings of local field potentials, electroencephalography (EEG), and electromyography (EMG) to interrogate the supraspinal circuit mechanisms of the pathological activation pattern of the spinal pattern generator.

Brain oscillatory dysfunctions in dystonia

Dystonia is a hyperkinetic movement disorder associated with loss of inhibition, abnormal plasticity, dysfunctional sensorimotor integration, and brain oscillatory dysfunctions at cortical and subcortical levels of the central nervous system. Hence, dystonia is considered a network disorder that can, in many cases, be efficiently treated by pallidal deep brain stimulation (DBS). Abnormal oscillatory activity has been identified across the motor circuit of patients with dystonia. Increased low frequency (LF) synchronization in the internal pallidum is the most prominent abnormality. LF oscillations have been associated with the severity of dystonic motor symptoms; they are suppressed by DBS and localized to the clinically most effective stimulation site. Although the origin of these pathologic changes in brain activity needs further clarifications, their characterization will help in adjusting DBS parameters for successful clinical outcome.

The Interactions between Adipose Tissue Secretions and Parkinson's disease; The Role of Leptin

Leptin is a hormone that regulates appetite by acting on receptors in the hypothalamus, where it modifies food intake to maintain equilibrium with the body energy resources. Leptin and its receptors are widely distributed in the central nervous system, suggesting that they may give neuronal survival signals. The potential of leptin to decrease/increase neuronal damage and neuronal plasticity in Parkinson's diseases (PD) is the subject of this review, which outlines our current knowledge of how leptin acts in the brain. Although leptin-mediated neuroprotective signaling results in neuronal death prevention, it can affect neuroinflammatory cascades and also neuronal plasticity which contribute to PD pathology. Other neuroprotective molecules, such as insulin and erythropoietin, share leptin-related signaling cascades, and therefore constitute a component of the neurotrophic effects mediated by endogenous hormones. With the evidence that leptin dysregulation causes increased neuronal vulnerability to damage in PD, using leptin as a target for therapeutic modification is an appealing and realistic option.

Sleep Quality Modulates the Association between Dynamic Functional Network Connectivity and Cognitive Function in Healthy Older Adults

Aging is associated with changes in sleep, brain activity, and cognitive function, as well as the association among these factors; however, the precise nature of these changes has not been elucidated. This study systematically investigated the modulatory effect of sleep on the relationship between brain functional network connectivity (FNC) and cognitive function in older adults. In total, 107 community-dwelling healthy older adults were recruited and assigned into poor sleep and good sleep groups based on the Pittsburgh Sleep Quality Index. The static functional network connectivity (sFNC), the temporal variability of dynamic FNC (dFNC) from variance (dFNC-var), and the dFNC from clustering state (dFNC-state) were calculated. Corresponding cognition-predictive models were constructed for each sleep group. dFNC but not sFNC, was able to significantly predict the cognitive function in older adults. Specifically, sleep played a modulatory role in the association between dFNC and cognitive function, with sleep-specific variations at both microscopic (i.e., specific edges) and macroscopic levels (i.e., specific states) of dFNC.

Subthalamic dynamic neural states correlate with motor symptoms in Parkinson's Disease

OBJECTIVE

This study aims to discriminate the dynamic synchronization states from the subthalamic local field potentials and investigate their correlations with the motor symptoms in Parkinson's Disease (PD).

METHODS

The resting-state local field potentials of 10 patients with PD were recorded from the subthalamic nucleus. The dynamic neural states of multiple oscillations were discriminated and analyzed. The Spearman correlation was used to investigate the correlations between occurrence rate or duration of dynamic neural states and the severity of motor symptoms.

RESULTS

The proportion of long low-beta and theta synchronized state was significantly correlated with the general motor symptom and tremor, respectively. The duration of combined low/high-beta state was significantly correlated with rigidity, and the duration of combined alpha/high-beta state was significantly correlated with bradykinesia.

CONCLUSIONS

This study provides evidence that motor symptoms are associated with the neural states coded with multiple oscillations in PD.

SIGNIFICANCE

This study may advance the understanding of the neurophysiological mechanisms of the motor symptoms and provide potential biomarkers for closed-loop deep brain stimulation in PD.

Long-Term Desynchronization by Coordinated Reset Stimulation in a Neural Network Model With Synaptic and Structural Plasticity

Several brain disorders are characterized by abnormal neuronal synchronization. To specifically counteract abnormal neuronal synchrony and, hence, related symptoms, coordinated reset (CR) stimulation was computationally developed. In principle, successive epochs of synchronizing and desynchronizing stimulation may reversibly move neural networks with plastic synapses back and forth between stable regimes with synchronized and desynchronized firing. Computationally derived predictions have been verified in pre-clinical and clinical studies, paving the way for novel therapies. However, as yet, computational models were not able to reproduce the clinically observed increase of desynchronizing effects of regularly administered CR stimulation intermingled by long stimulation-free epochs. We show that this clinically important phenomenon can be computationally reproduced by taking into account structural plasticity (SP), a mechanism that deletes or generates synapses in order to homeostatically adapt the firing rates of neurons to a set point-like target firing rate in the course of days to months. If we assume that CR stimulation favorably reduces the target firing rate of SP, the desynchronizing effects of CR stimulation increase after long stimulation-free epochs, in accordance with clinically observed phenomena. Our study highlights the pivotal role of stimulation- and dosing-induced modulation of homeostatic set points in therapeutic processes.

A theoretical framework for the site-specific and frequency-dependent neuronal effects of deep brain stimulation

BACKGROUND

Deep brain stimulation is an established therapy for several neurological disorders; however, its effects on neuronal activity vary across brain regions and depend on stimulation settings. Understanding these variable responses can aid in the development of physiologically-informed stimulation paradigms in existing or prospective indications.

OBJECTIVE

Provide experimental and computational insights into the brain-region-specific and frequency-dependent effects of extracellular stimulation on neuronal activity.

METHODS

In patients with movement disorders, single-neuron recordings were acquired from the subthalamic nucleus, substantia nigra pars reticulata, ventral intermediate nucleus, or reticular thalamus during microstimulation across various frequencies (1-100 Hz) to assess single-pulse and frequency-response functions. Moreover, a biophysically-realistic computational framework was developed which generated postsynaptic responses under the assumption that electrical stimuli simultaneously activated all convergent presynaptic inputs to stimulation target neurons. The framework took into consideration the relative distributions of excitatory/inhibitory afferent inputs to model site-specific responses, which were in turn embedded within a model of short-term synaptic plasticity to account for stimulation frequency-dependence.

RESULTS

We demonstrated microstimulation-evoked excitatory neuronal responses in thalamic structures (which have predominantly excitatory inputs) and inhibitory responses in basal ganglia structures (predominantly inhibitory inputs); however, higher stimulation frequencies led to a loss of site-specificity and convergence towards neuronal suppression. The model confirmed that site-specific responses could be simulated by accounting for local neuroanatomical/microcircuit properties, while suppression of neuronal activity during high-frequency stimulation was mediated by short-term synaptic depression.

CONCLUSIONS

Brain-region-specific and frequency-dependant neuronal responses could be simulated by considering neuroanatomical (local microcircuitry) and neurophysiological (short-term plasticity) properties.

Safety and Tolerability of Burst-Cycling Deep Brain Stimulation for Freezing of Gait in Parkinson's Disease

Background: Freezing of gait (FOG) is a common symptom in Parkinson’s disease (PD) and can be difficult to treat with dopaminergic medications or with deep brain stimulation (DBS). Novel stimulation paradigms have been proposed to address suboptimal responses to conventional DBS programming methods. Burst-cycling deep brain stimulation (BCDBS) delivers current in various frequencies of bursts (e.g., 4, 10, or 15 Hz), while maintaining an intra-burst frequency identical to conventional DBS.

Objective: To evaluate the safety and tolerability of BCDBS in PD patients with FOG.

Methods: Ten PD subjects with STN or GPi DBS and complaints of FOG were recruited for this single center, single blinded within-subject crossover study. For each subject, we compared 4, 10, and 15 Hz BCDBS to conventional DBS during the PD medication-OFF state.

Results: There were no serious adverse events with BCDBS. It was feasible and straightforward to program BCDBS in the clinic setting. The benefit was comparable to conventional DBS in measures of FOG, functional mobility and in PD motor symptoms. BCDBS had lower battery consumption when compared to conventional DBS.

Conclusions: BCDBS was feasible, safe and well tolerated and it has potential to be a viable future DBS programming strategy.

Kilohertz-frequency stimulation of the nervous system: A review of underlying mechanisms

BACKGROUND

Electrical stimulation in the kilohertz-frequency range has gained interest in the field of neuroscience. The mechanisms underlying stimulation in this frequency range, however, are poorly characterized to date.

OBJECTIVE/HYPOTHESIS

To summarize the manifold biological effects elicited by kilohertz-frequency stimulation in the context of the currently existing literature and provide a mechanistic framework for the neural responses observed in this frequency range.

METHODS

A comprehensive search of the peer-reviewed literature was conducted across electronic databases. Relevant computational, clinical, and mechanistic studies were selected for review.

RESULTS

The effects of kilohertz-frequency stimulation on neural tissue are diverse and yield effects that are distinct from conventional stimulation. Broadly, these can be divided into 1) subthreshold, 2) suprathreshold, 3) synaptic and 4) thermal effects. While facilitation is the dominating mechanism at the subthreshold level, desynchronization, spike-rate adaptation, conduction block, and non-monotonic activation can be observed during suprathreshold kilohertz-frequency stimulation. At the synaptic level, kilohertz-frequency stimulation has been associated with the transient depletion of the available neurotransmitter pool - also known as synaptic fatigue. Finally, thermal effects associated with extrinsic (environmental) and intrinsic (associated with kilohertz-frequency stimulation) temperature changes have been suggested to alter the neural response to stimulation paradigms.

CONCLUSION

The diverse spectrum of neural responses to stimulation in the kilohertz-frequency range is distinct from that associated with conventional stimulation. This offers the potential for new therapeutic avenues across stimulation modalities. However, stimulation in the kilohertz-frequency range is associated with distinct challenges and caveats that need to be considered in experimental paradigms.

Deep brain stimulation: a review of the open neural engineering challenges

OBJECTIVE

Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy.

APPROACH

We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS.

MAIN RESULTS

We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns.

SIGNIFICANCE

This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.

Freezing of gait: understanding the complexity of an enigmatic phenomenon

Diverse but complementary methodologies are required to uncover the complex determinants and pathophysiology of freezing of gait. To develop future therapeutic avenues, we need a deeper understanding of the disseminated functional-anatomic network and its temporally associated dynamic processes. In this targeted review, we will summarize the latest advances across multiple methodological domains including clinical phenomenology, neurogenetics, multimodal neuroimaging, neurophysiology, and neuromodulation. We found that (i) locomotor network vulnerability is established by structural damage, e.g. from neurodegeneration possibly as result from genetic variability, or to variable degree from brain lesions. This leads to an enhanced network susceptibility, where (ii) modulators can both increase or decrease the threshold to express freezing of gait. Consequent to a threshold decrease, (iii) neuronal integration failure of a multilevel brain network will occur and affect one or numerous nodes and projections of the multilevel network. Finally, (iv) an ultimate pathway might encounter failure of effective motor output and give rise to freezing of gait as clinical endpoint. In conclusion, we derive key questions from this review that challenge this pathophysiological view. We suggest that future research on these questions should lead to improved pathophysiological insight and enhanced therapeutic strategies.

Deep brain stimulation: Imaging on a group level

Deep Brain Stimulation (DBS) is an established treatment option for movement disorders and is under investigation for treatment in a growing number of other brain diseases. It has been shown that exact electrode placement crucially affects the efficacy of DBS and this should be considered when investigating novel indications or DBS targets. To measure clinical improvement as a function of electrode placement, neuroscientific methodology and specialized software tools are needed. Such tools should have the goal to make electrode placement comparable across patients and DBS centers, and include statistical analysis options to validate and define optimal targets. Moreover, to allow for comparability across different centers, these need to be performed within an algorithmically and anatomically standardized and openly available group space. With the publication of Lead-DBS software in 2014, an open-source tool was introduced that allowed for precise electrode reconstructions based on pre- and postoperative neuroimaging data. Here, we introduce Lead Group, implemented within the Lead-DBS environment and specifically designed to meet aforementioned demands. In the present article, we showcase the various processing streams of Lead Group in a retrospective cohort of 51 patients suffering from Parkinson's disease, who were implanted with DBS electrodes to the subthalamic nucleus (STN). Specifically, we demonstrate various ways to visualize placement of all electrodes in the group and map clinical improvement values to subcortical space. We do so by using active coordinates and volumes of tissue activated, showing converging evidence of an optimal DBS target in the dorsolateral STN. Second, we relate DBS outcome to the impact of each electrode on local structures by measuring overlap of stimulation volumes with the STN. Finally, we explore the software functions for connectomic mapping, which may be used to relate DBS outcomes to connectivity estimates with remote brain areas. The manuscript is accompanied by a walkthrough tutorial which allows users to reproduce all main results presented here. All data and code needed to reproduce results are openly available.

Subthalamic neuromodulation improves short-term motor learning in Parkinson's disease

The basal ganglia and cerebellum are implicated in both motor learning and Parkinson's disease. Deep brain stimulation (DBS) is an established treatment for advanced Parkinson's disease that leads to motor and non-motor effects by modulating specific neural pathways. Recently, a disynaptic projection from the subthalamic nucleus (STN) to cerebellar hemispheres was discovered. To investigate the functional significance of this pathway in motor learning, short-term improvement in motor execution in 20 patients with Parkinson's disease on and off STN-DBS and 20 age-matched healthy controls was studied in a visuomotor task combined with whole-brain connectomics. Motor learning was impaired in Parkinson's disease off stimulation but was partially restored through DBS. Connectivity between active DBS contacts and a distributed network of brain regions correlated with improvement in motor learning. Region of interest analysis revealed connectivity from active contact to cerebellar hemisphere ipsilateral to hand movement as the strongest predictor for change in motor learning. Peak predictive voxels in the cerebellum localized to Crus II of lobule VII, which also showed higher STN than motor cortex connectivity, suggestive of a connection surpassing motor cortex. Our findings provide new insight into the circuit nature of Parkinson's disease and the distributed network effects of DBS in motor learning.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Closed-Loop Transcranial Ultrasound Stimulation for Real-Time Non-invasive Neuromodulation in vivo

The closed-loop brain stimulation technique plays a key role in neural network information processing and therapies of neurological diseases. Transcranial ultrasound stimulation (TUS) is an established neuromodulation method for the neural oscillation in animals or human. All available TUS systems provide brain stimulation in an open-loop pattern. In this study, we developed a closed-loop transcranial ultrasound stimulation (CLTUS) system for real-time non-invasive neuromodulation in vivo. We used the CLTUS system to modulate the neural activities of the hippocampus of a wild-type mouse based on the phase of the theta rhythm recorded at the ultrasound-targeted location. In addition, we modulated the hippocampus of a temporal lobe epilepsy (TLE) mouse. The ultrasound stimulation increased the absolute power and reduced the relative power of the theta rhythm, which were independent of the specific phase of the theta rhythm. Compared with those of a sham stimulation, the latency of epileptic seizures was significantly increased, while the epileptic seizure duration was significantly decreased under the CLTUS. The above results indicate that the CLTUS can be used to not only modulate the neural oscillation through the theta-phase-specific manipulation of the hippocampus but also effectively inhibit the seizure of a TLE mouse in time. CLTUS has large application potentials for the understanding of the causal relationship of neural circuits as well as for timely, effective, and non-invasive therapies of neurological diseases such as epilepsy and Parkinson's disease.

Region-specific effects of Scrapper on the abundance of glutamate and gamma-aminobutyric acid in the mouse brain

The brain consists of various areas with anatomical features. Neurons communicate with one another via excitatory or inhibitory synaptic transmission. Altered abundance of neurotransmitters, including glutamate and gamma-aminobutyric acid (GABA), in specific brain regions is closely involved in severe neurological diseases, such as schizophrenia and obsessive-compulsive disorder. SCRAPPER, a ubiquitin E3 ligase, regulates synaptic transmission. Scrapper gene deficiency results in defective neurotransmission due to excessive secretion of neurotransmitters. The present study employed matrix-assisted laser desorption/ionization imaging mass spectrometry to analyze the abundance of amino acid neurotransmitters in Scrapper knockout (SCR-KO) mice. SCR-KO mice exhibited significantly increased glutamate levels in the isocortex (CTX), corpus callosum (CC), thalamus (TH), midbrain (MB), cerebellar cortex (CBX), and caudoputamen (CP) and increased GABA levels in the CTX, CC, TH, MB, CBX and hypothalamus (HY) compared with wild-type mice. These findings indicate that Scrapper deficiency leads to upregulated glutamate and GABA levels in multiple regions. Our results show a differential, region-specific effect of Scrapper on the abundance of glutamate and GABA.