Network perspectives on the mechanisms of deep brain stimulation

Effectiveness of Deep Brain Stimulation in Improving Balance in Parkinson's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Balance dysfunction is a debilitating feature of advanced Parkinson's disease (PD), potentially improved by deep brain stimulation (DBS). This systematic review and meta-analysis pooled evidence from randomized controlled trials (RCTs) on DBS effectiveness in improving balance in PD.

METHODS

A systematic search was conducted to identify eligible RCTs investigating the effectiveness of DBS on improving balance in people with PD. Meta-analysis was performed using random effects models and reported as mean difference and 95% confidence intervals. Risk of bias was assessed using Cochrane's ROB-2 tool.

RESULTS

Seventeen RCTs were eligible (n = 333), utilizing a range of stimulation sites, parameters, reporting tools for balance outcomes, and control/comparator groups, making the identification of clear trends and recommendations difficult. Eleven studies were deemed as having some risk of bias, 4 having low risk of bias and 2 having high risk of bias. One small meta-analysis was conducted and found no significant difference in balance outcomes. Most studies reported no significant improvement in Timed Up-and-Go scores, Berg Balance Scale scores, frequency of falls, and balance-related items of the Movement Disorder Society's Unified Parkinson's Disease Rating Scales. Some studies reported improvements in the Tinetti balance test, posturography readings, and reduction in falls though these were not supported by other studies due to a lack of reporting on these items or conflicting findings.

CONCLUSIONS

Current research suggests that DBS results in no significant improvement in balance dysfunction for people with PD, though such assertions require larger RCTs with clear reporting methods using validated reporting tools.

Sustained reduction of essential tremor with low-power non-thermal transcranial focused ultrasound stimulations in humans

BACKGROUND

Transcranial ultrasound stimulation (TUS) is a non-invasive brain stimulation technique; when skull aberrations are compensated for, this technique allows, with millimetric accuracy, circumvention of the invasive surgical procedure associated with deep brain stimulation (DBS) and the limited spatial specificity of transcranial magnetic stimulation.

OBJECTIVE

/hypothesis: We hypothesize that MR-guided low-power TUS can induce a sustained decrease of tremor power in patients suffering from medically refractive essential tremor.

METHODS

The dominant hand only was targeted, and two anatomical sites were sonicated in this exploratory study: the ventral intermediate nucleus of the thalamus (VIM) and the dentato-rubro-thalamic tract (DRT). Patients (N = 9) were equipped with MR-compatible accelerometers attached to their hands to monitor their tremor in real-time during TUS.

RESULTS

VIM neurostimulations followed by a low-duty cycle (5 %) DRT stimulation induced a substantial decrease in the tremor power in four patients, with a minimum of 89.9 % reduction when compared with the baseline power a few minutes after the DRT stimulation. The only patient stimulated in the VIM only and with a low duty cycle (5 %) also experienced a sustained reduction of the tremor (up to 93.4 %). Four patients (N = 4) did not respond. The temperature at target was 37.2 ± 1.4 °C compared to 36.8 ± 1.4 °C for a 3 cm away control point.

CONCLUSIONS

MR-guided low power TUS can induce a substantial and sustained decrease of tremor power. Follow-up studies need to be conducted to reproduce the effect and better to understand the variability of the response amongst patients. MR thermometry during neurostimulations showed no significant thermal rise, supporting a mechanical effect.

Clinical and Brain Morphometry Predictors of Deep Brain Stimulation Outcome in Parkinson's Disease

Subthalamic deep brain stimulation (STN-DBS) is known to improve motor function in advanced Parkinson's disease (PD) and to enable a reduction of anti-parkinsonian medication. While the levodopa challenge test and disease duration are considered good predictors of STN-DBS outcome, other clinical and neuroanatomical predictors are less established. This study aimed to evaluate, in addition to clinical predictors, the effect of patients' individual brain topography on DBS outcome. The medical records of 35 PD patients were used to analyze DBS outcomes measured with the following scales: Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) off medication at baseline, and at 6-months during medication off and stimulation on, use of anti-parkinsonian medication (LED), Abnormal Involuntary Movement Scale (AIMS) and Non-Motor Symptoms Questionnaire (NMS-Quest). Furthermore, preoperative brain MRI images were utilized to analyze the brain morphology in relation to STN-DBS outcome. With STN-DBS, a 44% reduction in the UPDRS-III score and a 43% decrease in the LED were observed (p<0.001). Dyskinesia and non-motor symptoms decreased significantly [median reductions of 78,6% (IQR 45,5%) and 18,4% (IQR 32,2%) respectively, p=0.001 - 0.047]. Along with the levodopa challenge test, patients' age correlated with the observed DBS outcome measured as UPDRS-III improvement (ρ= -0.466 - -0.521, p<0.005). Patients with greater LED decline had lower grey matter volumes in left superior medial frontal gyrus, in supplementary motor area and cingulum bilaterally. Additionally, patients with greater UPDRS-III score improvement had lower grey matter volume in similar grey matter areas. These findings remained significant when adjusted for sex, age, baseline LED and UPDRS scores respectively and for total intracranial volume (p=0.0041- 0.001). However, only the LED decrease finding remained significant when the analyses were further controlled for stimulation amplitude. It appears that along with the clinical predictors of STN-DBS outcome, individual patient topographic differences may influence DBS outcome. Clinical Trial Registration Number: NCT06095245, registration date October 23, 2023, retrospectively registered.

Amelioration of Parkinsonian tremor evoked by DBS: which role play cerebello-(sub)thalamic fiber tracts?

BACKGROUND

Current pathophysiological models of Parkinson's disease (PD) assume a malfunctioning network being adjusted by the DBS signal. As various authors showed a main involvement of the cerebellum within this network, cerebello-cerebral fiber tracts are gaining special interest regarding the mediation of DBS effects.

OBJECTIVES

The crossing and non-decussating fibers of the dentato-rubro-thalamic tract (c-DRTT/nd-DRTT) and the subthalamo-ponto-cerebellar tract (SPCT) are thought to build up an integrated network enabling a bidimensional communication between the cerebellum and the basal ganglia. The aim of this study was to investigate the influence of these tracts on clinical control of Parkinsonian tremor evoked by DBS.

METHODS

We analyzed 120 electrode contacts from a cohort of 14 patients with tremor-dominant or equivalence-type PD having received bilateral STN-DBS. Probabilistic tractography was performed to depict the c-DRTT, nd-DRTT, and SPCT. Distance maps were calculated for the tracts and correlated to clinical tremor control for each electrode pole.

RESULTS

A significant difference between "effective" and "less-effective" contacts was only found for the c-DRTT (p = 0.039), but not for the SPCT, nor the nd-DRTT. In logistic and linear regressions, significant results were also found for the c-DRTT only (pmodel logistic = 0.035, ptract logistic = 0,044; plinear = 0.027).

CONCLUSIONS

We found a significant correlation between the distance of the DBS electrode pole to the c-DRTT and the clinical efficacy regarding tremor reduction. The c-DRTT might therefore play a major role in the mechanisms of alleviation of Parkinsonian tremor and could eventually serve as a possible DBS target for tremor-dominant PD in future.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered the stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

On Multiscaling of Parkinsonian Rest Tremor Signals and Their Classification

Self-similar stochastic processes and broad probability distributions are ubiquitous in nature and in many man-made systems. The brain is a particularly interesting example of (natural) complex system where those features play a pivotal role. In fact, the controversial yet experimentally validated "criticality hypothesis" explaining the functioning of the brain implies the presence of scaling laws for correlations. Recently, we have analyzed a collection of rest tremor velocity signals recorded from patients affected by Parkinson's disease, with the aim of determining and hence exploiting the presence of scaling laws. Our results show that multiple scaling laws are required in order to describe the dynamics of such signals, stressing the complexity of the underlying generating mechanism. We successively extracted numeric features by using the multifractal detrended fluctuation analysis procedure. We found that such features can be effective for discriminating classes of signals recorded in different experimental conditions. Notably, we show that the use of medication (L-DOPA) can be recognized with high accuracy.

Advancements in Diffusion MRI Tractography for Neurosurgery

ABSTRACT

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

Mediation of Tremor Control by the Decussating and Nondecussating Part of the Dentato-Rubro-Thalamic Tract in Deep Brain Stimulation in Essential Tremor: Which Part Should Be Stimulated?

OBJECTIVES

The dentato-rubro-thalamic tract (DRTT) has been found to play a major role in the mechanisms of tremor alleviation by deep brain stimulation (DBS) in essential tremor (ET). Still, the influence of the two different parts of the DRTT, consisting of crossing and nondecussating fibers, is not yet clear with respect to tremor reduction. The aim of this study was to assess the influence of the crossing and the nondecussating part of the DRTT on tremor control in ET.

MATERIALS AND METHODS

We investigated 80 electrode contacts in ten patients with ET who received bilateral DBS of the Nucleus ventralis intermedius of the thalamus (VIM). Preoperatively and with patients under general anesthesia, 3T magnetic resonance imaging scans were performed, including Diffusion Tensor Imaging scans with 64 gradient directions. We calculated the course of the two parts of the DRTT based on a workflow for probabilistic fiber tracking including protocols for correction of susceptibility- and eddy current-induced distortions. Distances of electrode contacts were correlated with clinical data from neurologic single pole testing.

RESULTS

Voltage- and current-steered systems were analyzed separately. Regarding postural tremor, effective contacts showed significantly lower distances to both parts of the DRTT (crossing p < 0.001, nondecussating p < 0.05) in voltage-steered systems. Regarding intentional tremor, significant results were only found for the crossing part (p < 0.01). Regarding both tremor types, effective contacts were closer to the crossing part, unlike less effective contacts. Nonlinear regression analyses using a logistic model showed higher coefficients for the crossing part of the DRTT. Multivariate regression models including distances to both parts of the DRTT showed a significant influence of only the crossing part. Analysis of current-steered systems showed unstable data, probably because of the small number of analyzed patients.

CONCLUSIONS

Our data suggest an involvement of both parts of the DRTT in tremor reduction, indicating mediation of DBS effects by both fiber bundles, although the crossing part showed stronger correlations with good clinical responses. Nevertheless, special attention should be paid to methodologic aspects when using probabilistic tractography for patient-specific targeting to avoid uncertain and inaccurate results.

Pallidal and Cortical Oscillations in Freely Moving Patients With Dystonia

OBJECTIVES

To evaluate the correlation between the pallidal local field potentials (LFPs) activity and the cortical oscillations (at rest and during several motor tasks) in two freely moving patients with generalized dystonia and pallidal deep brain stimulation (DBS).

MATERIALS AND METHODS

Two women with isolated generalized dystonia were selected for bilateral globus pallidus internus (GPi) DBS. After the electrodes' implantation, cortical activity was recorded by a portable electroencephalography (EEG) system simultaneously with GPi LFPs activity, during several motor tasks, gait, and rest condition. Recordings were not performed during stimulation. EEG and LFPs signals relative to each specific movement were coupled together and grouped in neck/upper limbs movements and gait. Power spectral density (PSD), EEG-LFP coherence (through envelope of imaginary coherence operator), and 1/f exponent of LFP-PSD background were calculated.

RESULTS

In both patients, the pallidal LFPs PSD at rest was characterized by prominent 4-12 Hz activity. Voluntary movements increased activity in the theta (θ) band (4-7 Hz) compared to rest, in both LFPs and EEG signals. Gait induced a drastic raise of θ activity in both patients' pallidal activity, less marked for the EEG signal. A coherence peak within the 8-13 Hz range was found between pallidal LFPs and EEG recorded at rest.

CONCLUSIONS

Neck/upper limbs voluntary movements and gait suppressed the GPi-LFPs-cortical-EEG coherence and differently impacted both EEG and LFPs low frequency activity. These findings suggest a selective modulation of the cortico-basal ganglia network activity in dystonia.

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.

Electrophysiological insights into deep brain stimulation of the network disorder dystonia

Deep brain stimulation (DBS), a treatment for modulating the abnormal central neuronal circuitry, has become the standard of care nowadays and is sometimes the only option to reduce symptoms of movement disorders such as dystonia. However, on the one hand, there are still open questions regarding the pathomechanisms of dystonia and, on the other hand, the mechanisms of DBS on neuronal circuitry. That lack of knowledge limits the therapeutic effect and makes it hard to predict the outcome of DBS for individual dystonia patients. Finding electrophysiological biomarkers seems to be a promising option to enable adapted individualised DBS treatment. However, biomarker search studies cannot be conducted on patients on a large scale and experimental approaches with animal models of dystonia are needed. In this review, physiological findings of deep brain stimulation studies in humans and animal models of dystonia are summarised and the current pathophysiological concepts of dystonia are discussed.

Optimal subthalamic stimulation sites and related networks for freezing of gait in Parkinson's disease

Freezing of gait is a common and debilitating symptom in Parkinson's disease. Although high-frequency subthalamic deep brain stimulation is an effective treatment for Parkinson's disease, post-operative freezing of gait severity has been reported to alleviate, deteriorate or remain constant. We conducted this study to explore the optimal stimulation sites and related connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait in Parkinson's disease. A total of 76 Parkinson's disease patients with freezing of gait who underwent bilateral high-frequency subthalamic stimulation were retrospectively included. The volumes of tissue activated were estimated based on individual electrode reconstruction. The optimal and sour stimulation sites were calculated at coordinate/voxel/mapping level and mapped to anatomical space based on patient-specific images and stimulation settings. The structural and functional predictive connectivity networks for the change of the post-operative Freezing of Gait-Questionnaire were also identified based on normative connectomes derived from the Parkinson's Progression Marker Initiative database. Leave-one-out cross-validation model validated the above results, and the model remained significant after including covariates. The dorsolateral two-thirds of the subthalamic nucleus was identified as the optimal stimulation site, while the ventrocentral portion of the right subthalamic nucleus and internal capsule surrounding the left central subthalamic nucleus were considered as the sour stimulation sites. Modulation of the fibre tracts connecting to the supplementary motor area, pre-supplementary motor area and pedunculopontine nucleus accounted for the alleviation of freezing of gait, whereas tracts connecting to medial and ventrolateral prefrontal cortices contributed to the deterioration of freezing of gait. The optimal/sour stimulation sites and structural/functional predictive connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait are identified and validated through sizable Parkinson's disease patients in this study. With the growing understanding of stimulation sites and related networks, individualized deep brain stimulation treatment with directional leads will become an optimal choice for Parkinson's disease patients with freezing of gait in the future.

Mechanisms of Neurostimulation for Epilepsy

This review discusses the use of neurostimulation therapies for epilepsy treatment, including vagal nerve stimulation, responsive neurostimulation, and deep brain stimulation. Different therapeutic strategies and their underlying mechanisms are explored, with a focus on optimizing parameters for seizure reduction. The review also highlights the paradigm shift toward a more diverse and multimodal approach to deep brain neuromodulation.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations

Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy. With this aim, we performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.

Subthalamic nucleus deep brain stimulation induces nigrostriatal dopaminergic plasticity in a stable rat model of Parkinson's disease

OBJECTIVE

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been a highly effective treatment option for middle to late stage Parkinson's disease for decades. Though, the underlying mechanisms of action, particularly effects on the cellular level, remain in part unclear. In the context of identifying disease-modifying effects of STN-DBS by prompting cellular plasticity in midbrain dopaminergic systems, we analyzed neuronal tyrosine hydroxylase and c-Fos expression in the substantia nigra pars compacta (SNpc) and ventral tegmental area (VTA).

METHODS

We applied 1 week of continuous unilateral STN-DBS in a group of stable 6-hydroxydopamine (6-OHDA) hemiparkinsonian rats (STNSTIM) in comparison to a 6-OHDA control group (STNSHAM). Immunohistochemistry identified NeuN+, tyrosine hydroxylase+ and c-Fos+ cells within the SNpc and VTA.

RESULTS

After 1 week, rats in the STNSTIM group had 3.5-fold more tyrosine hydroxylase+ neurons within the SNpc (P = 0.010) but not in the VTA compared to sham controls. There was no difference in basal cell activity as indicated by c-Fos expression in both midbrain dopaminergic systems.

CONCLUSION

Our data support a neurorestorative effect of STN-DBS in the nigrostriatal dopaminergic system already after 7 days of continuous STN-DBS in the stable Parkinson's disease rat model without affecting basal cell activity.

Deep Brain Stimulation beyond the Clinic: Navigating the Future of Parkinson's and Alzheimer's Disease Therapy

Deep brain stimulation (DBS) is a surgical procedure that uses electrical neuromodulation to target specific regions of the brain, showing potential in the treatment of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Despite similarities in disease pathology, DBS is currently only approved for use in PD patients, with limited literature on its effectiveness in AD. While DBS has shown promise in ameliorating brain circuits in PD, further research is needed to determine the optimal parameters for DBS and address any potential side effects. This review emphasizes the need for foundational and clinical research on DBS in different brain regions to treat AD and recommends the development of a classification system for adverse effects. Furthermore, this review suggests the use of either a low-frequency system (LFS) or high-frequency system (HFS) depending on the specific symptoms of the patient for both PD and AD.

Efficacy of different strategies of responsive neurostimulation on seizure control and their association with acute neurophysiological effects in rats

Responsive neurostimulation (RNS) has shown promising but limited efficacy in the treatment of drug-resistant epilepsy. The clinical utility of RNS is hindered by the incomplete understanding of the mechanism behind its therapeutic effects. Thus, assessing the acute effects of responsive stimulation (AERS) based on intracranial EEG recordings in the temporal lobe epilepsy rat model may provide a better understanding of the potential therapeutic mechanisms underlying the antiepileptic effect of RNS. Furthermore, clarifying the correlation between AERS and seizure severity may help guide the optimization of RNS parameter settings. In this study, RNS with high (130 Hz) and low frequencies (5 Hz) was applied to the subiculum (SUB) and CA1. To quantify the changes induced by RNS, we calculated the AERS during synchronization by Granger causality and analyzed the band power ratio in the classic power band after different stimulations were delivered in the interictal and seizure onset periods, respectively. This demonstrates that only targets combined with an appropriate stimulation frequency could be efficient for seizure control. High-frequency stimulation of CA1 significantly shortened the ongoing seizure duration, which may be causally related to increased synchronization after stimulation. Both high-frequency stimulation of the CA1 and low-frequency stimulation delivered to the SUB reduced seizure frequency, and the reduced seizure risk may correlate with the change in power ratio near the theta band. It indicated that different stimulations may control seizures in diverse manners, perhaps with disparate mechanisms. More focus should be placed on understanding the correlation between seizure severity and synchronization and rhythm around theta bands to simplify the process of parameter optimization.

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.

Adaptive Stimulations in a Biophysical Network Model of Parkinson’s Disease

Deep brain stimulation (DBS)—through a surgically implanted electrode to the subthalamic nucleus (STN)—has become a widely used therapeutic option for the treatment of Parkinson’s disease and other neurological disorders. The standard conventional high-frequency stimulation (HF) that is currently used has several drawbacks. To overcome the limitations of HF, researchers have been developing closed-loop and demand-controlled, adaptive stimulation protocols wherein the amount of current that is delivered is turned on and off in real-time in accordance with a biophysical signal. Computational modeling of DBS in neural network models is an increasingly important tool in the development of new protocols that aid researchers in animal and clinical studies. In this computational study, we seek to implement a novel technique of DBS where we stimulate the STN in an adaptive fashion using the interspike time of the neurons to control stimulation. Our results show that our protocol eliminates bursts in the synchronized bursting neuronal activity of the STN, which is hypothesized to cause the failure of thalamocortical neurons (TC) to respond properly to excitatory cortical inputs. Further, we are able to significantly decrease the TC relay errors, representing potential therapeutics for Parkinson’s disease.

Epileptic-network-based prediction and control of seizures in humans

Epilepsy is now conceptualized as a network disease. The epileptic brain network comprises structurally and functionally connected cortical and subcortical brain regions - spanning lobes and hemispheres -, whose connections and dynamics evolve in time. With this concept, focal and generalized seizures as well as other related pathophysiological phenomena are thought to emerge from, spread via, and be terminated by network vertices and edges that also generate and sustain normal, physiological brain dynamics. Research over the last years has advanced concepts and techniques to identify and characterize the evolving epileptic brain network and its constituents on various spatial and temporal scales. Network-based approaches further our understanding of how seizures emerge from the evolving epileptic brain network, and they provide both novel insights into pre-seizure dynamics and important clues for success or failure of measures for network-based seizure control and prevention. In this review, we summarize the current state of knowledge and address several important challenges that would need to be addressed to move network-based prediction and control of seizures closer to clinical translation.

Novel ways to modulate the vestibular system: Magnetic vestibular stimulation, deep brain stimulation and transcranial magnetic stimulation / transcranial direct current stimulation

BACKGROUND

Advances in neurotechnologies are revolutionizing our understanding of complex neural circuits and enabling new treatments for disorders of the human brain. In the vestibular system, electromagnetic stimuli can now modulate vestibular reflexes and sensations of self-motion by artificially stimulating the labyrinth, cerebellum, cerebral cortex, and their connections.

OBJECTIVE

In this narrative review, we describe evolving neuromodulatory techniques including magnetic vestibular stimulation (MVS), deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), and transcranial direct-current stimulation (tDCS) and discuss current and potential future application in the field of neuro-otology.

RESULTS

MVS triggers both vestibular nystagmic (persistent) and perceptual (lasting ∼1 min) responses that may serve as a model to study central adaptational mechanisms and pathomechanisms of hemispatial neglect. By systematically mapping DBS electrodes, targeted stimulation of central vestibular pathways allowed modulating eye movements, vestibular heading perception, spatial attention and graviception, resulting in reduced anti-saccade error rates and hypometria, improved heading discrimination, shifts in verticality perception and transiently decreased spatial attention. For TMS/tDCS treatment trials have demonstrated amelioration of vestibular symptoms in various neuro-otological conditions, including chronic vestibular insufficiency, Mal-de-Debarquement and cerebellar ataxia.

CONCLUSION

Neuromodulation has a bright future as a potential treatment of vestibular dysfunction. MVS, DBS and TMS may provide new and sophisticated, customizable, and specific treatment options of vestibular symptoms in humans. While promising treatment responses have been reported for TMS/tDCS, treatment trials for vestibular disorders using MVS or DBS have yet to be defined and performed.

Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST

Spiking neural networks (SNNs) represent the state-of-the-art approach to the biologically realistic modeling of nervous system function. The systematic calibration for multiple free model parameters is necessary to achieve robust network function and demands high computing power and large memory resources. Special requirements arise from closed-loop model simulation in virtual environments and from real-time simulation in robotic application. Here, we compare two complementary approaches to efficient large-scale and real-time SNN simulation. The widely used NEural Simulation Tool (NEST) parallelizes simulation across multiple CPU cores. The GPU-enhanced Neural Network (GeNN) simulator uses the highly parallel GPU-based architecture to gain simulation speed. We quantify fixed and variable simulation costs on single machines with different hardware configurations. As a benchmark model, we use a spiking cortical attractor network with a topology of densely connected excitatory and inhibitory neuron clusters with homogeneous or distributed synaptic time constants and in comparison to the random balanced network. We show that simulation time scales linearly with the simulated biological model time and, for large networks, approximately linearly with the model size as dominated by the number of synaptic connections. Additional fixed costs with GeNN are almost independent of model size, while fixed costs with NEST increase linearly with model size. We demonstrate how GeNN can be used for simulating networks with up to 3.5 · 10⁶ neurons (> 3 · 10¹²synapses) on a high-end GPU, and up to 250, 000 neurons (25 · 10⁹ synapses) on a low-cost GPU. Real-time simulation was achieved for networks with 100, 000 neurons. Network calibration and parameter grid search can be efficiently achieved using batch processing. We discuss the advantages and disadvantages of both approaches for different use cases.

Contemporary Approaches Toward Neuromodulation of Fear Extinction and Its Underlying Neural Circuits

Neuroscience and neuroimaging research have now identified brain nodes that are involved in the acquisition, storage, and expression of conditioned fear and its extinction. These brain regions include the ventromedial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), amygdala, insular cortex, and hippocampus. Psychiatric neuroimaging research shows that functional dysregulation of these brain regions might contribute to the etiology and symptomatology of various psychopathologies, including anxiety disorders and post traumatic stress disorder (PTSD) (Barad et al. Biol Psychiatry 60:322-328, 2006; Greco and Liberzon Neuropsychopharmacology 41:320-334, 2015; Milad et al. Biol Psychiatry 62:1191-1194, 2007a, Biol Psychiatry 62:446-454, b; Maren and Quirk Nat Rev Neurosci 5:844-852, 2004; Milad and Quirk Annu Rev Psychol 63:129, 2012; Phelps et al. Neuron 43:897-905, 2004; Shin and Liberzon Neuropsychopharmacology 35:169-191, 2009). Combined, these findings indicate that targeting the activation of these nodes and modulating their functional interactions might offer an opportunity to further our understanding of how fear and threat responses are formed and regulated in the human brain, which could lead to enhancing the efficacy of current treatments or creating novel treatments for PTSD and other psychiatric disorders (Marin et al. Depress Anxiety 31:269-278, 2014; Milad et al. Behav Res Ther 62:17-23, 2014). Device-based neuromodulation techniques provide a promising means for directly changing or regulating activity in the fear extinction network by targeting functionally connected brain regions via stimulation patterns (Raij et al. Biol Psychiatry 84:129-137, 2018; Marković et al. Front Hum Neurosci 15:138, 2021). In the past ten years, notable advancements in the precision, safety, comfort, accessibility, and control of administration have been made to the established device-based neuromodulation techniques to improve their efficacy. In this chapter we discuss ten years of progress surrounding device-based neuromodulation techniques-Electroconvulsive Therapy (ECT), Transcranial Magnetic Stimulation (TMS), Magnetic Seizure Therapy (MST), Transcranial Focused Ultrasound (TUS), Deep Brain Stimulation (DBS), Vagus Nerve Stimulation (VNS), and Transcranial Electrical Stimulation (tES)-as research and clinical tools for enhancing fear extinction and treating PTSD symptoms. Additionally, we consider the emerging research, current limitations, and possible future directions for these techniques.

Developments in the mechanistic understanding and clinical application of deep brain stimulation for Parkinson's disease

INTRODUCTION. Deep brain stimulation (DBS) is a life-changing treatment for patients with Parkinson's disease (PD) and gives the unique opportunity to directly explore how basal ganglia work. Despite the rapid technological innovation of the last years, the untapped potential of DBS is still high.

AREAS COVERED. This review summarizes the developments in the mechanistic understanding of DBS and the potential clinical applications of cutting-edge technological advances. Rather than a univocal local mechanism, DBS exerts its therapeutic effects through several multimodal mechanisms and involving both local and network-wide structures, although crucial questions remain unexplained. Nonetheless, new insights in mechanistic understanding of DBS in PD have provided solid bases for advances in preoperative selection phase, prediction of motor and non-motor outcomes, leads placement and postoperative stimulation programming.

EXPERT OPINION. DBS has not only strong evidence of clinical effectiveness in PD treatment, but technological advancements are revamping its role of neuromodulation of brain circuits and key to better understanding PD pathophysiology. In the next few years, the worldwide use of new technologies in clinical practice will provide large data to elucidate their role and to expand their applications for PD patients, providing useful insights to personalize DBS treatment and follow-up.

Update on the application of mesenchymal stem cell-derived exosomes in the treatment of Parkinson's disease: A systematic review

Parkinson's disease (PD) has become the second largest neurodegenerative disease after Alzheimer's disease, and its incidence is increasing year by year. Traditional dopamine replacement therapy and deep brain stimulation can only alleviate the clinical symptoms of patients with PD but cannot cure the disease. In recent years, stem cell therapy has been used to treat neurodegenerative diseases. Many studies have shown that stem cell transplantation has a therapeutic effect on PD. Here, we review recent studies indicating that exosomes derived from mesenchymal stem cells also have the potential to treat PD in animal models, but the exact mechanism remains unclear. This article reviews the mechanisms through which exosomes are involved in intercellular information exchange, promote neuroprotection and freely cross the blood-brain barrier in the treatment of PD. The increase in the incidence of PD and the decline in the quality of life of patients with advanced PD have placed a heavy burden on patients, families and society. Therefore, innovative therapies for PD are urgently needed. Herein, we discuss the mechanisms underlying the effects of exosomes in PD, to provide new insights into the treatment of PD. The main purpose of this article is to explore the therapeutic potential of exosomes derived from mesenchymal stem cells and future research directions for this degenerative disease.

Dynamics of phase oscillator networks with synaptic weight and structural plasticity

We study the dynamics of Kuramoto oscillator networks with two distinct adaptation processes, one varying the coupling strengths and the other altering the network structure. Such systems model certain networks of oscillatory neurons where the neuronal dynamics, synaptic weights, and network structure interact with and shape each other. We model synaptic weight adaptation with spike-timing-dependent plasticity (STDP) that runs on a longer time scale than neuronal spiking. Structural changes that include addition and elimination of contacts occur at yet a longer time scale than the weight adaptations. First, we study the steady-state dynamics of Kuramoto networks that are bistable and can settle in synchronized or desynchronized states. To compare the impact of adding structural plasticity, we contrast the network with only STDP to one with a combination of STDP and structural plasticity. We show that the inclusion of structural plasticity optimizes the synchronized state of a network by allowing for synchronization with fewer links than a network with STDP alone. With non-identical units in the network, the addition of structural plasticity leads to the emergence of correlations between the oscillators' natural frequencies and node degrees. In the desynchronized regime, the structural plasticity decreases the number of contacts, leading to a sparse network. In this way, adding structural plasticity strengthens both synchronized and desynchronized states of a network. Second, we use desynchronizing coordinated reset stimulation and synchronizing periodic stimulation to induce desynchronized and synchronized states, respectively. Our findings indicate that a network with a combination of STDP and structural plasticity may require stronger and longer stimulation to switch between the states than a network with STDP only.

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.

Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson’s disease

The prodromal phase of Parkinson’s disease is characterized by aggregation of the misfolded pathogenic protein α-synuclein in select neural centres, co-occurring with non-motor symptoms including sensory and cognitive loss, and emotional disturbances. It is unclear whether neuronal loss is significant during the prodrome. Underlying these symptoms are synaptic impairments and aberrant neural network activity. However, the relationships between synaptic defects and network-level perturbations are not established. In experimental models, pathological α-synuclein not only impacts neurotransmission at the synaptic level, but also leads to changes in brain network-level oscillatory dynamics—both of which likely contribute to non-motor deficits observed in Parkinson’s disease. Here we draw upon research from both human subjects and experimental models to propose a ‘synapse to network prodrome cascade’ wherein before overt cell death, pathological α-synuclein induces synaptic loss and contributes to aberrant network activity, which then gives rise to prodromal symptomology. As the disease progresses, abnormal patterns of neural activity ultimately lead to neuronal loss and clinical progression of disease. Finally, we outline goals and research needed to unravel the basis of functional impairments in Parkinson’s disease and other α-synucleinopathies.

Dysregulation of adult hippocampal neuroplasticity in major depression: pathogenesis and therapeutic implications

Major depressive disorder (MDD) was previously hypothesized to be a disease of monoamine deficiency in which low levels of monoamines in the synaptic cleft were believed to underlie depressive symptoms. More recently, however, there has been a paradigm shift toward a neuroplasticity hypothesis of depression in which downstream effects of antidepressants, such as increased neurogenesis, contribute to improvements in cognition and mood. This review takes a top-down approach to assess how changes in behavior and hippocampal-dependent circuits may be attributed to abnormalities at the molecular, structural, and synaptic level. We conclude with a discussion of how antidepressant treatments share a common effect in modulating neuroplasticity and consider outstanding questions and future perspectives.

Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Abnormal Functional Brain Network in Parkinson's Disease and the Effect of Acute Deep Brain Stimulation

Objective: The objective of this study was to use functional connectivity and graphic indicators to investigate the abnormal brain network topological characteristics caused by Parkinson's disease (PD) and the effect of acute deep brain stimulation (DBS) on those characteristics in patients with PD. Methods: We recorded high-density EEG (256 channels) data from 21 healthy controls (HC) and 20 patients with PD who were in the DBS-OFF state and DBS-ON state during the resting state with eyes closed. A high-density EEG source connectivity method was used to identify functional brain networks. Power spectral density (PSD) analysis was compared between the groups. Functional connectivity was calculated for 68 brain regions in the theta (4-8 Hz), alpha (8-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz) frequency bands. Network estimates were measured at both the global (network topology) and local (inter-regional connection) levels. Results: Compared with HC, PSD was significantly increased in the theta (p = 0.003) frequency band and was decreased in the beta1 (p = 0.009) and beta2 (p = 0.04) frequency bands in patients with PD. However, there were no differences in any frequency bands between patients with PD with DBS-OFF and DBS-ON. The clustering coefficient and local efficiency of patients with PD showed a significant decrease in the alpha, beta1, and beta2 frequency bands (p < 0.001). In addition, edgewise statistics showed a significant difference between the HC and patients with PD in all analyzed frequency bands (p < 0.005). However, there were no significant differences between the DBS-OFF state and DBS-ON state in the brain network, except for the functional connectivity in the beta2 frequency band (p < 0.05). Conclusion: Compared with HC, patients with PD showed the following characteristics: slowed EEG background activity, decreased clustering coefficient and local efficiency of the brain network, as well as both increased and decreased functional connectivity between different brain areas. Acute DBS induces a local response of the brain network in patients with PD, mainly showing decreased functional connectivity in a few brain regions in the beta2 frequency band.

Target-Specific Effects of Deep Brain Stimulation for Tourette Syndrome: A Systematic Review and Meta-Analysis

Background: Extended research has pointed to the efficacy of deep brain stimulation (DBS) in treatment of patients with treatment-refractory Tourette syndrome (TS). The four most commonly used DBS targets for TS include the centromedian nucleus-nucleus ventrooralis internus (CM-Voi) and the centromedian nucleus-parafascicular (CM-Pf) complexes of the thalamus, and the posteroventrolateral (pvIGPi) and the anteromedial portion of the globus pallidus internus (amGPi). Differences and commonalities between those targets need to be compared systematically. Objective: Therefore, we evaluated whether DBS is effective in reducing TS symptoms and target-specific differences. Methods: A PubMed literature search was conducted according to the PRISMA guidelines. Eligible literature was used to conduct a systematic review and meta-analysis. Results: In total, 65 studies with 376 patients were included. Overall, Yale Global Tic Severity Scale (YGTSS) scores were reduced by more than 50 in 69% of the patients. DBS also resulted in significant reductions of secondary outcome measures, including the total YGTSS, modified Rush Video-Based Tic Rating Scale (mRVRS), Yale-Brown Obsessive Compulsive Scale (YBOCS), and Becks Depression Inventory (BDI). All targets resulted in significant reductions of YGTSS scores and, with the exception of the CM-Pf, also in reduced YBOCS scores. Interestingly, DBS of pallidal targets showed increased YGTSS and YBOCS reductions compared to thalamic targets. Also, the meta-analysis including six randomized controlled and double-blinded trials demonstrated clinical efficacy of DBS for TS, that remained significant for GPi but not thalamic stimulation in two separate meta-analyses. Conclusion: We conclude that DBS is a clinically effective treatment option for patients with treatment-refractory TS, with all targets showing comparable improvement rates. Future research might focus on personalized and symptom-specific target selection.

A connectomic analysis of deep brain stimulation for treatment-resistant depression

OBJECTIVE

Deep brain stimulation (DBS) has been used as a treatment of last resort for treatment-resistant depression (TRD) for more than a decade. Many DBS targets have been proposed and tested clinically, but the underlying circuit mechanisms remain unclear. Uncovering white matter tracts (WMT) activated by DBS targets may provide crucial information about the circuit substrates mediating DBS efficacy in ameliorating TRD.

METHODS

We performed probabilistic tractography using diffusion magnetic resonance imaging datas from 100 healthy volunteers in Human Connectome Project datasets to analyze the structural connectivity patterns of stimulation targeting currently-used DBS target for TRD. We generated mean and binary fiber distribution maps and calculated the numbers of WMT streamlines in the dataset.

RESULTS

Probabilistic tracking results revealed that activation of distinct DBS targets demonstrated modulation of overlapping but considerably distinct pathways. DBS targets were categorized into 4 groups: Cortical, Striatal, Thalamic, and Medial Forebrain Bundle according to their main modulated WMT and brain areas. Our data also revealed that Brodmann area 10 and amygdala are hub structures that are associated with all DBS targets.

CONCLUSIONS

Our results together suggest that the distinct mechanism of DBS targets implies individualized target selection and formulation in the future of DBS treatment for TRD. The modulation of Brodmann area 10 and amygdala may be critical for the efficacy of DBS-mediated treatment of TRD.

Subthalamic and pallidal deep brain stimulation: are we modulating the same network?

The subthalamic nucleus and internal pallidum are main target sites for deep brain stimulation in Parkinson's disease. Multiple trials that investigated subthalamic versus pallidal stimulation were unable to settle on a definitive optimal target between the two. One reason could be that the effect is mediated via a common functional network. To test this hypothesis, we calculated connectivity profiles seeding from deep brain stimulation electrodes in 94 patients that underwent subthalamic and 28 patients with pallidal treatment based on a normative connectome atlas calculated from 1,000 healthy subjects. In each cohort, we calculated connectivity profiles that were associated with optimal clinical improvements. The two maps showed striking similarity and were able to cross-predict outcomes in the respective other cohort (R = 0.37 at p < 0.001; R = 0.34 at p = 0.032). Next, we calculated an agreement map which retained regions common to both target sites. Crucially, this map was able to explain an additional amount of variance in clinical improvements of either cohort when compared to the maps calculated on the two cohorts alone. Finally, we tested profiles and predictive utility of connectivity maps calculated from different motor symptom subscores with a specific focus on bradykinesia and rigidity. While our study is based on retrospective data and indirect connectivity metrics, it may deliver empirical data to support the hypothesis of a largely overlapping network associated with effective deep brain stimulation in Parkinson's disease irrespective of the specific target.

STN-DBS affects language processing differentially in Parkinson's disease: Multiple-case MEG study

OBJECTIVES

In this study, we investigated the effects of bilateral and unilateral deep brain stimulation of the subthalamic nucleus (STN-DBS) in PD patients on neural responses associated with two aspects of spoken language processing: semantics of action-related verbs and morphosyntactic processing.

MATERIALS AND METHODS

Using a passive unattended paradigm to present spoken linguistic stimuli, we recorded magnetoencephalographic (MEG) responses in three PD patients in four DBS conditions: left unilateral STN-DBS, right unilateral STN-DBS, bilateral STN-DBS, and no STN-DBS. To ensure that any observed effects of DBS on the neuromagnetic responses could be attributed to the linguistic context per se and were not merely induced by the electrical stimulation, we assessed the effects of STN-DBS on linguistic contrasts within each stimulation condition. Hence, we contrasted the processing of action vs. abstract verbs as well as the processing of correct vs. incorrect morphosyntactic inflections within each DBS condition.

RESULTS

The results revealed that, compared to the DBS-off state, both bilateral and right unilateral stimulation of the STN yielded significant dissociations in the processing of action and abstract verbs, with greater neuromagnetic responses for action verbs compared to abstract verbs. For morphosyntax processing, only left unilateral stimulation yielded significant dissociations (relative to the DBS-off state), with greater neuromagnetic responses to the incorrect inflections compared to the correct inflections.

CONCLUSION

The results reflect differential effects of unilateral and bilateral STN-DBS on neuromagnetic responses associated with the processing of spoken language. They suggest that different specific aspects of linguistic information processing in PD are affected differently by STN-DBS.

Dysfunctional Brain Dynamics of Parkinson's Disease and the Effect of Acute Deep Brain Stimulation

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Although previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics.

Objective: We tested two hypotheses. (1) Reduced brain dynamics, as evidenced by slowed microstate dynamic change, is a characteristic of PD and is related to the movement disorders of patients with PD. (2) Therapeutic acute DBS can partially reverse slow brain dynamics in PD to healthy levels.

Methods: We used electroencephalography (EEG) microstate analysis based on high density (256-channel) EEG to detect the effects of PD and DBS on brain dynamic changes on a sub-second timescale. We compared 21 healthy controls (HCs) with 20 patients with PD who were in either DBS-OFF or DBS-ON states. Assessment of movement disorder using the Unified Parkinson's Disease Rating Scale III was correlated with microstate parameters.

Results: Compared with HCs, patients with PD displayed a longer mean microstate duration with reduced occurrence per second, which were significantly associated with movement disorders. In patients with PD, some parameters of microstate analysis were restored toward healthy levels after DBS.

Conclusions: Resting-state EEG microstate analysis is an important tool for investigating brain dynamic changes in PD and DBS. PD can slow down brain dynamic change, and therapeutic acute DBS can partially reverse this change toward a healthy level.

Anterior thalamic stimulation improves working memory precision judgments

BACKGROUND

The anterior nucleus of thalamus (ANT) has been suggested as an extended hippocampal system. The circuit of ANT and hippocampus has been widely demonstrated to be associated with memory function. Both lesions to each region and disrupting inter-regional information flow can induce working memory impairment. However, the role of this circuit in working memory precision remains unknown.

OBJECTIVE

To test the role of the hippocampal-anterior thalamic pathway in working memory precision, we delivered intracranially electrical stimulation to the ANT. We hypothesize that ANT stimulation can improve working memory precision.

METHODS

Presurgical epilepsy patients with depth electrodes in ANT and hippocampus were recruited to perform a color-recall working memory task. Participants were instructed to point out the color they were supposed to recall by clicking a point on the color wheel, while the intracranial EEG data were synchronously recorded. For randomly selected half trials, a bipolar electrical stimulation was delivered to the ANT electrodes.

RESULTS

We found that compared to non-stimulation trials, working memory precision judgements were significantly improved for stimulation trials. ANT electrical stimulation significantly increased spectral power of gamma (30-100 Hz) oscillations and decreased interictal epileptiform discharges (IED) in the hippocampus. Moreover, the increased gamma power during the pre-stimulus and retrieval period predicted the improvement of working memory precision judgements.

CONCLUSION

ANT electrical stimulation can improve working memory precision judgements and modulate hippocampal gamma activity, providing direct evidence on the role of the human hippocampal-anterior thalamic axis in working memory precision.

The Biology and Pathobiology of Glutamatergic, Cholinergic, and Dopaminergic Signaling in the Aging Brain

The elderly population is growing worldwide, with important health and socioeconomic implications. Clinical and experimental studies on aging have uncovered numerous changes in the brain, such as decreased neurogenesis, increased synaptic defects, greater metabolic stress, and enhanced inflammation. These changes are associated with cognitive decline and neurobehavioral deficits. Although aging is not a disease, it is a significant risk factor for functional worsening, affective impairment, disease exaggeration, dementia, and general disease susceptibility. Conversely, life events related to mental stress and trauma can also lead to accelerated age-associated disorders and dementia. Here, we review human studies and studies on mice and rats, such as those modeling human neurodegenerative diseases, that have helped elucidate (1) the dynamics and mechanisms underlying the biological and pathological aging of the main projecting systems in the brain (glutamatergic, cholinergic, and dopaminergic) and (2) the effect of defective glutamatergic, cholinergic, and dopaminergic projection on disabilities associated with aging and neurodegenerative disorders, such as Alzheimer's and Parkinson's diseases. Detailed knowledge of the mechanisms of age-related diseases can be an important element in the development of effective ways of treatment. In this context, we briefly analyze which adverse changes associated with neurodegenerative diseases in the cholinergic, glutaminergic and dopaminergic systems could be targeted by therapeutic strategies developed as a result of our better understanding of these damaging mechanisms.

A 1-year follow-up study on immunological changes following deep brain stimulation in patients with epilepsy

The aim of this study was to evaluate the effects of deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) on systemic inflammatory responses in patients with drug-resistant epilepsy (DRE). Twenty-two Finnish patients with ANT-DBS implantation were enrolled in this pilot study. Changes in plasma interleukin-6 (IL-6) and interleukin-10 (IL-10) levels were examined using generalized estimating equation models at seven time points (before DBS surgery and 1, 2, 3, 6, 9 and 12 months after implantation). In the whole group, the IL-6/IL-10 ratio decreased significantly over time following ANT-DBS, while the decrease in IL-6 levels and increase in IL-10 levels were not significant. In the responder and nonresponder groups, IL-6 levels remained unchanged during the follow-up. Responders had significantly lower pre-DBS IL-10 levels before the ANT-DBS treatment than nonresponders, but the levels significantly increased over time after the treatment. In addition, responders had a higher pre-DBS IL-6/IL-10 ratio than nonresponders, and the ratio decreased for both groups after treatment, but the decrease did not reach the level of statistical significance. The rate of decrease in the ratio per month tended to be higher in responders than in nonresponders. These results may highlight the anti-inflammatory properties of ANT-DBS treatment associated with its therapeutic effectiveness in patients with DRE. Additional studies are essential to evaluate the potential of the proinflammatory cytokine IL-6, the anti-inflammatory cytokine IL-10, and their ratio as biomarkers to evaluate the therapeutic response to DBS treatment, which could facilitate treatment optimization.

Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation

The development of closed-loop deep brain stimulation (DBS) systems represents a significant opportunity for innovation in the clinical application of neurostimulation therapies. Despite the highly dynamic nature of neurological diseases, open-loop DBS applications are incapable of modifying parameters in real time to react to fluctuations in disease states. Thus, current practice for the designation of stimulation parameters, such as duration, amplitude, and pulse frequency, is an algorithmic process. Ideal stimulation parameters are highly individualized and must reflect both the specific disease presentation and the unique pathophysiology presented by the individual. Stimulation parameters currently require a lengthy trial-and-error process to achieve the maximal therapeutic effect and can only be modified during clinical visits. The major impediment to the development of automated, adaptive closed-loop systems involves the selection of highly specific disease-related biomarkers to provide feedback for the stimulation platform. This review explores the disease relevance of neurochemical and electrophysiological biomarkers for the development of closed-loop neurostimulation technologies. Electrophysiological biomarkers, such as local field potentials, have been used to monitor disease states. Real-time measurement of neurochemical substances may be similarly useful for disease characterization. Thus, the introduction of measurable neurochemical analytes has significantly expanded biomarker options for feedback-sensitive neuromodulation systems. The potential use of biomarker monitoring to advance neurostimulation approaches for treatment of Parkinson's disease, essential tremor, epilepsy, Tourette syndrome, obsessive-compulsive disorder, chronic pain, and depression is examined. Further, challenges and advances in the development of closed-loop neurostimulation technology are reviewed, as well as opportunities for next-generation closed-loop platforms.

Deep Brain Stimulation for Tremor and Dystonia

Deep brain stimulation (DBS) is the most commonly used surgical treatment for drug-refractory movement disorders such as tremor and dystonia. Appropriate patient selection along with target selection is important to ensure optimal outcome without complications. This review summarizes the recent literature regarding the mechanism of action, indications, outcome, and complications of DBS in tremor and dystonia. A comparison with other modalities of surgical interventions is discussed along with a note of the recent advances in technology. Future research needs to be directed to understand the underlying etiopathogenesis of the disease and the way in which DBS modulates the intracranial abnormal networks.

A Scientometric Analysis of the 100 Most Cited Articles on Pallidotomy

BACKGROUND

Pallidotomy is the oldest stereotactically performed neurosurgical procedure for movement disorders. Consequently, there is a wealth of literature available on the topic.

OBJECTIVES

The aim of this analysis was to identify the top-cited articles on pallidotomy in order to discern the origins, spread, the current trends, and the future directions of this surgical procedure.

METHODS

We performed a search of the Web of Science database on 19 October 2020 using the keyword "pallidotomy." The top-100 cited articles found were arranged in descending order on the basis of citation count (CC) and citation per year (CY). Relevant conclusions were derived.

RESULTS

The 100 top-cited articles were published between 1961 and 2017, in 24 journals. The average CC and CY were 118.1 (range - 856-46) and 5.326 (range - 29.52-2.09), respectively. The 3 most prolific authors were Lang AE (Neurologist - Toronto), Lozano AM (Neurosurgeon - Toronto), and Vitek JL (Neurologist - Atlanta). The Journal of Neurosurgery published the highest number of top-cited articles [Neurology. 1960;10:61-9]. The maximum articles were from the USA. University of Toronto and Emory University were the most productive institutions.

CONCLUSIONS

Pallidotomy has gone through several ebbs and flows. Unilateral pallidotomy is currently recommended for the treatment of motor symptoms of Parkinson's disease and dystonia. The need for further research and improved technology to make the technique safer and prove its efficacy is highlighted, especially keeping in mind a large number of populations to which the prohibitively expensive deep brain stimulation is unavailable.