Quantifying the neural elements activated and inhibited by globus pallidus deep brain stimulation

Biophysics of Frequency-Dependent Variation in Paresthesia and Pain Relief during Spinal Cord Stimulation

The neurophysiological effects of spinal cord stimulation (SCS) for chronic pain are poorly understood, resulting in inefficient failure-prone programming protocols and inadequate pain relief. Nonetheless, novel stimulation patterns are regularly introduced and adopted clinically. Traditionally, paresthetic sensation is considered necessary for pain relief, although novel paradigms provide analgesia without paresthesia. However, like pain relief, the neurophysiological underpinnings of SCS-induced paresthesia are unknown. Here, we paired biophysical modeling with clinical paresthesia thresholds (of both sexes) to investigate how stimulation frequency affects the neural response to SCS relevant to paresthesia and analgesia. Specifically, we modeled the dorsal column (DC) axonal response, dorsal column nucleus (DCN) synaptic transmission, conduction failure within DC fiber collaterals, and dorsal horn network output. Importantly, we found that high-frequency stimulation reduces DC fiber activation thresholds, which in turn accurately predicts clinical paresthesia perception thresholds. Furthermore, we show that high-frequency SCS produces asynchronous DC fiber spiking and ultimately asynchronous DCN output, offering a plausible biophysical basis for why high-frequency SCS is less comfortable and produces qualitatively different sensation than low-frequency stimulation. Finally, we demonstrate that the model dorsal horn network output is sensitive to SCS-inherent variations in spike timing, which could contribute to heterogeneous pain relief across patients. Importantly, we show that model DC fiber collaterals cannot reliably follow high-frequency stimulation, strongly affecting the network output and typically producing antinociceptive effects at high frequencies. Altogether, these findings clarify how SCS affects the nervous system and provide insight into the biophysics of paresthesia generation and pain relief.

Dissecting deep brain stimulation evoked neural activity in the basal ganglia

Deep brain stimulation (DBS) is an established therapeutic tool for the treatment of Parkinson's disease (PD). The mechanisms of DBS for PD are likely rooted in modulation of the subthalamo-pallidal network. However, it can be difficult to electrophysiologically interrogate that network in human patients. The recent identification of large amplitude evoked potential (EP) oscillations from DBS in the subthalamic nucleus (STN) or globus pallidus internus (GPi) are providing new scientific opportunities to expand understanding of human basal ganglia network activity. In turn, the goal of this review is to provide a summary of DBS-induced EPs in the basal ganglia and attempt to explain various components of the EP waveforms from their likely network origins. Our analyses suggest that DBS-induced antidromic activation of globus pallidus externus (GPe) is a key driver of these oscillatory EPs, independent of stimulation location (i.e. STN or GPi). This suggests a potentially more important role for GPe in the mechanisms of DBS for PD than typically assumed. And from a practical perspective, DBS EPs are poised to become clinically useful electrophysiological biomarker signals for verification of DBS target engagement.

Low-frequency deep brain stimulation reveals resonant beta-band evoked oscillations in the pallidum of Parkinson's Disease patients

Introduction

Evidence suggests that spontaneous beta band (11-35 Hz) oscillations in the basal ganglia thalamocortical (BGTC) circuit are linked to Parkinson's disease (PD) pathophysiology. Previous studies on neural responses in the motor cortex evoked by electrical stimulation in the subthalamic nucleus have suggested that circuit resonance may underlie the generation of spontaneous and stimulation-evoked beta oscillations in PD. Whether these stimulation-evoked, resonant oscillations are present across PD patients in the internal segment of the globus pallidus (GPi), a primary output nucleus in the BGTC circuit, is yet to be determined.

Methods

We characterized spontaneous and stimulation-evoked local field potentials (LFPs) in the GPi of four PD patients (five hemispheres) using deep brain stimulation (DBS) leads externalized after DBS implantation surgery.

Results

Our analyses show that low-frequency (2-4 Hz) stimulation in the GPi evoked long-latency (>50 ms) beta-band neural responses in the GPi in 4/5 hemispheres. We demonstrated that neural sources generating both stimulation-evoked and spontaneous beta oscillations were correlated in their frequency content and spatial localization.

Discussion

Our results support the hypothesis that the same neuronal population and resonance phenomenon in the BGTC circuit generates both spontaneous and evoked pallidal beta oscillations. These data also support the development of closed-loop control systems that modulate the GPi spontaneous oscillations across PD patients using beta band stimulation-evoked responses.

Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation

The neuromodulation effect of low-intensity focused ultrasound (LIFU) is highly target-specific. Unintended off-target neuronal excitation can be elicited when the beam focusing accuracy and resolution are limited, whereas the resulted side effect has not been evaluated quantitatively. There is also a lack of methods addressing the minimization of such side effects. Therefore, this work introduces a computational model of unintended neuronal excitation during LIFU neuromodulation, which evaluates the off-target activation area (OTAA) by integrating an ultrasound field model with the neuronal spiking model. In addition, a phased array beam focusing scheme called constrained optimal resolution beamforming (CORB) is proposed to minimize the off-target neuronal excitation area while ensuring effective stimulation in the target brain region. A lower bound of the OTAA is analytically approximated in a simplified homogeneous medium, which could guide the selection of transducer parameters such as aperture size and operating frequency. Simulations in a human head model using three transducer setups show that CORB markedly reduces the OTAA compared with two benchmark beam focusing methods. The high neuromodulation resolution demonstrates the capability of LIFU to effectively limit the side effects during neuromodulation, allowing future clinical applications such as treatment of neuropsychiatric disorders.

A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation

Neurostimulation has diverse clinical applications and potential as a treatment for medically refractory movement disorders, epilepsy, and other neurological disorders. However, the parameters used to program electrodes-polarity, pulse width, amplitude, and frequency-and how they are adjusted have remained largely untouched since the 1970 s. This review summarizes the state-of-the-art in Deep Brain Stimulation (DBS) and highlights the need for further research to uncover the physiological mechanisms of neurostimulation. We focus on studies that reveal the potential for clinicians to use waveform parameters to selectively stimulate neural tissue for therapeutic benefit, while avoiding activating tissue associated with adverse effects. DBS uses cathodic monophasic rectangular pulses with passive recharging in clinical practice to treat neurological conditions such as Parkinson's Disease. However, research has shown that stimulation efficiency can be improved, and side effects reduced, through modulating parameters and adding novel waveform properties. These developments can prolong implantable pulse generator lifespan, reducing costs and surgery-associated risks. Waveform parameters can stimulate neurons based on axon orientation and intrinsic structural properties, providing clinicians with more precise targeting of neural pathways. These findings could expand the spectrum of diseases treatable with neuromodulation and improve patient outcomes.

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.

Short-pulsed micro-magnetic stimulation of the vagus nerve

Vagus nerve stimulation (VNS) is commonly used to treat drug-resistant epilepsy and depression. The therapeutic effect of VNS depends on stimulating the afferent vagal fibers. However, the vagus is a mixed nerve containing afferent and efferent fibers, and the stimulation of cardiac efferent fibers during VNS may produce a rare but severe risk of bradyarrhythmia. This side effect is challenging to mitigate since VNS, via electrical stimulation technology used in clinical practice, requires unique electrode design and pulse optimization for selective stimulation of only the afferent fibers. Here we describe a method of VNS using micro-magnetic stimulation (µMS), which may be an alternative technique to induce a focal stimulation, enabling a selective fiber stimulation. Micro-coils were implanted into the cervical vagus nerve in adult male Wistar rats. For comparison, the physiological responses were recorded continuously before, during, and after stimulation with arterial blood pressure (ABP), respiration rate (RR), and heart rate (HR). The electrical VNS caused a decrease in ABP, RR, and HR, whereas µM-VNS only caused a transient reduction in RR. The absence of an HR modulation indicated that µM-VNS might provide an alternative technology to VNS with fewer heart-related side effects, such as bradyarrhythmia. Numerical electromagnetic simulations helped estimate the optimal coil orientation with respect to the nerve to provide information on the electric field’s spatial distribution and strength. Furthermore, a transmission emission microscope provided very high-resolution images of the cervical vagus nerve in rats, which identified two different populations of nerve fibers categorized as large and small myelinated fibers.

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.

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

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

Excitatory deep brain stimulation quenches beta oscillations arising in a computational model of the subthalamo-pallidal loop

Parkinson’s disease (PD) is associated with abnormal \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β band oscillations (13–30 Hz) in the cortico-basal ganglia circuits. Abnormally increased striato-pallidal inhibition and strengthening the synaptic coupling between subthalamic nucleus (STN) and globus pallidus externa (GPe), due to the loss of dopamine, are considered as the potential sources of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations in the basal ganglia. Deep brain stimulation (DBS) of the basal ganglia subregions is known as a way to reduce the pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations and motor deficits related to PD. Despite the success of the DBS, its underlying mechanism is poorly understood and, there is controversy about the inhibitory or excitatory role of the DBS in the literature. Here, we utilized a computational network model of basal ganglia which consists of STN, GPe, globus pallidus interna, and thalamic neuronal population. This model can reproduce healthy and pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations similar to what has been observed in experimental studies. Using this model, we investigated the effect of DBS to understand whether its effect is excitatory or inhibitory. Our results show that the excitatory DBS is able to quench the pathological synchrony and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations, while, applying inhibitory DBS failed to quench the PD signs. In light of simulation results, we conclude that the effect of the DBS on its target is excitatory.

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): Proof of concept in the human

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 13-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinson's disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulses with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequency-specific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.

Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology

Introduction: Advances in neuromodulation and deep brain stimulation (DBS) technologies have facilitated opportunities for improved clinical benefit and side effect management. However, new technologies have added complexity to clinic-based DBS programming.Areas covered: In this article, we review basic basal ganglia physiology, proposed mechanisms of action and technical aspects of DBS. We discuss novel DBS technologies for movement disorders including the role of advanced imaging software, lead design, IPG design, novel programming techniques including directional stimulation and coordinated reset neuromodulation. Additional topics include the use of potential biomarkers, such as local field potentials, electrocorticography, and adaptive stimulation. We will also discuss future directions including optogenetically inspired DBS.Expert opinion: The introduction of DBS for the management of movement disorders has expanded treatment options. In parallel with our improved understanding of brain physiology and neuroanatomy, new technologies have emerged to address challenges associated with neuromodulation, including variable effectiveness, side-effects, and programming complexity. Advanced functional neuroanatomy, improved imaging, real-time neurophysiology, improved electrode designs, and novel programming techniques have collectively been driving improvements in DBS outcomes.

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.

Mapping efficacious deep brain stimulation for pediatric dystonia

OBJECTIVE

The objective of this study was to report the authors' experience with deep brain stimulation (DBS) of the internal globus pallidus (GPi) as a treatment for pediatric dystonia, and to elucidate substrates underlying clinical outcome using state-of-the-art neuroimaging techniques.

METHODS

A retrospective analysis was conducted in 11 pediatric patients (6 girls and 5 boys, mean age 12 ± 4 years) with medically refractory dystonia who underwent GPi-DBS implantation between June 2009 and September 2017. Using pre- and postoperative MRI, volumes of tissue activated were modeled and weighted by clinical outcome to identify brain regions associated with clinical outcome. Functional and structural networks associated with clinical benefits were also determined using large-scale normative data sets.

RESULTS

A total of 21 implanted leads were analyzed in 11 patients. The average follow-up duration was 19 ± 20 months (median 5 months). Using a 7-point clinical rating scale, 10 patients showed response to treatment, as defined by scores < 3. The mean improvement in the Burke-Fahn-Marsden Dystonia Rating Scale motor score was 40% ± 23%. The probabilistic map of efficacy showed that the voxel cluster most associated with clinical improvement was located at the posterior aspect of the GPi, comparatively posterior and superior to the coordinates of the classic GPi target. Strong functional and structural connectivity was evident between the probabilistic map and areas such as the precentral and postcentral gyri, parietooccipital cortex, and brainstem.

CONCLUSIONS

This study reported on a series of pediatric patients with dystonia in whom GPi-DBS resulted in variable clinical benefit and described a clinically favorable stimulation site for this cohort, as well as its structural and functional connectivity. This information could be valuable for improving surgical planning, simplifying programming, and further informing disease pathophysiology.

Real-time suppression and amplification of frequency-specific neural activity using stimulation evoked oscillations

BACKGROUND

Approaches to predictably control neural oscillations are needed to understand their causal role in brain function in healthy or diseased states and to advance the development of neuromodulation therapies.

OBJECTIVE

We present a closed-loop neural control and optimization framework to actively suppress or amplify low-frequency neural oscillations observed in local field potentials in real-time by using electrical stimulation. The rationale behind this control approach and our working hypothesis is that neural oscillatory activity evoked by electrical pulses can suppress or amplify spontaneous oscillations via destructive or constructive interference when the pulses are continuously delivered with appropriate amplitudes and at precise phases of the modulated oscillations in a closed-loop scheme.

METHODS

We tested our hypothesis in two nonhuman primates that exhibited a robust increase in low-frequency (8-30 Hz) oscillatory power in the subthalamic nucleus (STN) following administration of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). To test our neural control approach, we targeted 8-17 Hz oscillations and used electrode arrays and electrical stimulation waveforms similar to those used in humans chronically implanted with brain stimulation systems. Stimulation parameters that maximize the suppression or amplification of neural oscillations were predicted using mathematical models of the stimulation evoked oscillations.

RESULTS

Our neural control and optimization approach was capable of actively and robustly suppressing or amplifying oscillations in the targeted frequency band (8-17 Hz) in real-time in the studied subjects.

CONCLUSIONS

The results from this study support our hypothesis and suggest that the proposed neural control framework allows one to characterize in controlled experiments the functional role of frequency-specific neural oscillations by using electrodes and stimulation waveforms currently being employed in humans.

Evoked potentials reveal neural circuits engaged by human deep brain stimulation

BACKGROUND

Deep brain stimulation (DBS) is an effective therapy for reducing the motor symptoms of Parkinson's disease, but the mechanisms of action of DBS and neural correlates of symptoms remain unknown.

OBJECTIVE

To use the neural response to DBS to reveal connectivity of neural circuits and interactions between groups of neurons as potential mechanisms for DBS.

METHODS

We recorded activity evoked by DBS of the subthalamic nucleus (STN) in humans with Parkinson's disease. In follow up experiments we also simultaneously recorded activity in the contralateral STN or the ipsilateral globus pallidus from both internal (GPi) and external (GPe) segments.

RESULTS

DBS local evoked potentials (DLEPs) were stereotyped across subjects, and a biophysical model of reciprocal connections between the STN and the GPe recreated DLEPs. Simultaneous STN and GP recordings during STN DBS demonstrate that DBS evoked potentials were present throughout the basal ganglia and confirmed that DLEPs arose from the reciprocal connections between the STN and GPe. The shape and amplitude of the DLEPs were dependent on the frequency and duration of DBS and were correlated with resting beta band oscillations. In the frequency domain, DLEPs appeared as a 350 Hz high frequency oscillation (HFO) independent of the frequency of DBS.

CONCLUSIONS

DBS evoked potentials suggest that the intrinsic dynamics of the STN and GP are highly interlinked and may provide a promising new biomarker for adaptive DBS.

Steering the Volume of Tissue Activated With a Directional Deep Brain Stimulation Lead in the Globus Pallidus Pars Interna: A Modeling Study With Heterogeneous Tissue Properties

Objective: To study the effect of directional deep brain stimulation (DBS) electrode configuration and vertical electrode spacing on the volume of tissue activated (VTA) in the globus pallidus, pars interna (GPi). Background: Directional DBS leads may allow clinicians to precisely direct current fields to different functional networks within traditionally targeted brain areas. Modeling the shape and size of the VTA for various monopolar or bipolar configurations can inform clinical programming strategies for GPi DBS. However, many computational models of VTA are limited by assuming tissue homogeneity. Methods: We generated a multimodal image-based detailed anatomical (MIDA) computational model with a directional DBS lead (1.5 mm or 0.5 mm vertical electrode spacing) placed with segmented contact 2 at the ventral posterolateral "sensorimotor" region of the GPi. The effect of tissue heterogeneity was examined by replacing the MIDA tissues with a homogeneous tissue of conductance 0.3 S/m. DBS pulses (amplitude: 1 mA, pulse width: 60 μs, frequency: 130 Hz) were used to produce VTAs. The following DBS contact configurations were tested: single-segment monopole (2B-/Case+), two-segment monopole (2A-/2B-/Case+ and 2B-/3B-/Case+), ring monopole (2A-/2B-/2C-/Case+), one-cathode three-anode bipole (2B-/3A+/3B+/3C+), three-cathode three-anode bipole (2A-/2B-/2C-/3A+/3B+/3C+). Additionally, certain vertical configurations were repeated with 2 mA current amplitude. Results: Using a heterogeneous tissue model affected both the size and shape of the VTA in GPi. Electrodes with both 0.5 mm and 1.5 mm vertical spacing (1 mA) modeling showed that the single segment monopolar VTA was entirely contained within the GPi when the active electrode is placed at the posterolateral "sensorimotor" GPi. Two segments in a same ring and ring settings, however, produced VTAs outside of the GPi border that spread into adjacent white matter pathways, e.g., optic tract and internal capsule. Both stacked monopolar settings and vertical bipolar settings allowed activation of structures dorsal to the GPi in addition to the GPi. Modeling of the stacked monopolar settings with the DBS lead with 0.5 mm vertical electrode spacing further restricted VTAs within the GPi, but the VTA volumes were smaller compared to the equivalent settings of 1.5 mm spacing.

Feedback-dependent neuronal properties make focal dystonias so focal

Focal dystonia, by definition, affects a specific body part; however, it may have a widespread neural substrate. We tested this hypothesis by examining the intrinsic behaviour and the neuronal properties that are modulated by changes in the physiological behaviour of their connections, that is feedback dependence, of the isolated pallidal neurons. During deep brain stimulation surgery in 12 patients with isolated cervical dystonia (without hand involvement), we measured spontaneous as well as evoked single-unit properties in response to fist making (hand movement) or shoulder shrug (neck movements). We measured the activity of isolated neurons that were only sensitive to the neck movements, hand movement, or not responsive to hand or neck movements. The spontaneous firing behaviour, such as the instantaneous firing rate and its regularity, was comparable in all three types of neurons. The neck movement-sensitive neurons had prominent bursting behaviour in comparison with the hand neurons. The feedback dependence of the neck movement-sensitive neurons was also significantly impaired when compared to hand movement-sensitive neurons. Motor-evoked change in firing rate of neck movement-sensitive neurons rapidly declined; the decay time constant was much shorter compared to hand movement-sensitive neurons. These results suggest that in isolated cervical dystonia, at the resolution of single neurons, the deficits are much widespread, affecting the neurons that drive the neck movement as well as the hand movements. We speculate that clinically discernable dystonia occurs when additional abnormality is added to baseline dysfunctional network, and one source of such abnormality may involve feedback.

Admittance Method for Estimating Local Field Potentials Generated in a Multi-Scale Neuron Model of the Hippocampus

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the challenge of misalignment between current sources and mesh nodes in a finite-element or resistor-network method volume conduction model needs to be further investigated. Therefore, using a previously published and validated multi-scale model of the hippocampus, the authors have formulated an algorithm for LFP estimation, and by extension, bidirectional communication between discretized and numerically solved volume conduction models and biologically detailed neural circuit models constructed in NEURON. Development of this algorithm required that we assess meshes of (i) unstructured tetrahedral and grid-based hexahedral geometries as well as (ii) differing approaches for managing the spatial misalignment of current sources and mesh nodes. The resulting algorithm is validated through the comparison of Admittance Method predicted evoked potentials with analytically estimated LFPs. Establishing this method is a critical step toward closed-loop integration of volume conductor and NEURON models that could lead to substantial improvement of the predictive power of multi-scale stimulation models of cortical tissue. These models may be used to deepen our understanding of hippocampal pathologies and the identification of efficacious electroceutical treatments.

A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection

Action selection has been hypothesized to be a key function of the basal ganglia, yet the nuclei involved, their interactions and the importance of the direct/indirect pathway segregation in such process remain debated. Here, we design a spiking computational model of the monkey basal ganglia derived from a previously published population model, initially parameterized to reproduce electrophysiological activity at rest and to embody as much quantitative anatomical data as possible. As a particular feature, both models exhibit the strong overlap between the direct and indirect pathways that has been documented in non-human primates. Here, we first show how the translation from a population to an individual neuron model was achieved, with the addition of a minimal number of parameters. We then show that our model performs action selection, even though it was built without any assumption on the activity carried out during behaviour. We investigate the mechanisms of this selection through circuit disruptions and found an instrumental role of the off-centre/on-surround structure of the MSN-STN-GPi circuit, as well as of the MSN-MSN and FSI-MSN projections. This validates their potency in enabling selection. We finally study the pervasive centromedian and parafascicular thalamic inputs that reach all basal ganglia nuclei and whose influence is therefore difficult to anticipate. Our model predicts that these inputs modulate the responsiveness of action selection, making them a candidate for the regulation of the speed-accuracy trade-off during decision-making.

Deep brain stimulation in essential tremor: targets, technology, and a comprehensive review of clinical outcomes

Introduction: Essential tremor (ET) is a common movement disorder with an estimated prevalence of 0.9% worldwide. Deep brain stimulation (DBS) is an established therapy for medication refractory and debilitating tremor. With the arrival of next generation technology, the implementation and delivery of DBS has been rapidly evolving. This review will highlight the current applications and constraints for DBS in ET.Areas covered: The mechanism of action, targets for neuromodulation, next generation guidance techniques, symptom-specific applications, and long-term efficacy will be reviewed.Expert opinion: The posterior subthalamic area and zona incerta are alternative targets to thalamic DBS in ET. However, they may be associated with additional stimulation-induced side effects. Novel stimulation paradigms and segmented electrodes provide innovative approaches to DBS programming and stimulation-induced side effects.

ROOTS: An Algorithm to Generate Biologically Realistic Cortical Axons and an Application to Electroceutical Modeling

Advances in computation and neuronal modeling have enabled the study of entire neural tissue systems with an impressive degree of biological realism. These efforts have focused largely on modeling dendrites and somas while largely neglecting axons. The need for biologically realistic explicit axonal models is particularly clear for applications involving clinical and therapeutic electrical stimulation because axons are generally more excitable than other neuroanatomical subunits. While many modeling efforts can rely on existing repositories of reconstructed dendritic/somatic morphologies to study real cells or to estimate parameters for a generative model, such datasets for axons are scarce and incomplete. Those that do exist may still be insufficient to build accurate models because the increased geometric variability of axons demands a proportional increase in data. To address this need, a Ruled-Optimum Ordered Tree System (ROOTS) was developed that extends the capability of neuronal morphology generative methods to include highly branched cortical axon terminal arbors. Further, this study presents and explores a clear use-case for such models in the prediction of cortical tissue response to externally applied electric fields. The results presented herein comprise (i) a quantitative and qualitative analysis of the generative algorithm proposed, (ii) a comparison of generated fibers with those observed in histological studies, (iii) a study of the requisite spatial and morphological complexity of axonal arbors for accurate prediction of neuronal response to extracellular electrical stimulation, and (iv) an extracellular electrical stimulation strength-duration analysis to explore probable thresholds of excitation of the dentate perforant path under controlled conditions. ROOTS demonstrates a superior ability to capture biological realism in model fibers, allowing improved accuracy in predicting the impact that microscale structures and branching patterns have on spatiotemporal patterns of activity in the presence of extracellular electric fields.

Pallidal lead placement in dystonia: leads of non-responders are contained within an anatomical range defined by responders

Background

Deep brain stimulation (DBS) within the pallidum represents an effective and well-established treatment for isolated dystonia. However, clinical outcome after surgery may be variable with limited response in 10–25% of patients. The effect of lead location on clinical improvement is still under debate.

Objective

To identify stimulated brain regions associated with the most beneficial clinical outcome in dystonia patients.

Methods

18 patients with cervical and generalized dystonia with chronic DBS of the internal pallidum were investigated. Patients were grouped according to their clinical improvement into responders, intermediate responders and non-responders. Magnetic resonance and computed tomography images were co-registered, and the volume of tissue activated (VTA) with respect to the pallidum of individual patients was analysed.

Results

VTAs in responders (n = 11), intermediate responders (n = 3) and non-responders (n = 4) intersected with the posterior internal (GPi) and external (GPe) pallidum and the subpallidal area. VTA heat maps showed an almost complete overlap of VTAs of responders, intermediate and non-responders. VTA coverage of the GPi was not higher in responders. In contrast, VTAs of intermediate and non-responders covered the GPi to a significantly larger extent in the left hemisphere (p < 0.01).

Conclusions

DBS of ventral parts of the posterior GPi, GPe and the adjacent subpallidal area containing pallidothalamic output projections resulted in favourable clinical effects. Of note, non-responders were also stimulated within the same area. This suggests that factors other than mere lead location (e.g., clinical phenotype, genetic background) have determined clinical outcome in the present cohort.

Electronic supplementary material

The online version of this article (10.1007/s00415-020-09753-z) contains supplementary material, which is available to authorized users.

Brain connectivity markers for the identification of effective contacts in subthalamic nucleus deep brain stimulation

The clinical benefit of deep brain stimulation (DBS) for Parkinson's disease (PD) is relevant to the tracts adjacent to the stimulation site, but it remains unclear what connectivity pattern is associated with effective DBS. The aim of this study was to identify clinically effective electrode contacts on the basis of brain connectivity markers derived from diffusion tensor tractography. We reviewed 77 PD patients who underwent bilateral subthalamic nucleus DBS surgery. The patients were assigned into the training (n = 58) and validation (n = 19) groups. According to the therapeutic window size, all contacts were classified into effective and ineffective groups. The whole‐brain connectivity of each contact's volume of tissue activated was estimated using tractography with preoperative diffusion tensor data. Extracted connectivity features were put into an all‐relevant feature selection procedure within cross‐validation loops, to identify features with significant discriminative power for contact classification. A total of 616 contacts on 154 DBS leads were discriminated, with 388 and 228 contacts being classified as effective and ineffective ones, respectively. After the feature selection, the connectivity of contacts with the thalamus, pallidum, hippocampus, primary motor area, supplementary motor area and superior frontal gyrus was identified to significantly contribute to contact classification. Based on these relevant features, the random forest model constructed from the training group achieved an accuracy of 84.9% in the validation group, to discriminate effective contacts from the ineffective. Our findings advanced the understanding of the specific brain connectivity patterns associated with clinical effective electrode contacts, which potentially guided postoperative DBS programming.

Memory Prosthesis: Is It Time for a Deep Neuromimetic Computing Approach?

Memory loss, one of the most dreaded afflictions of the human condition, presents considerable burden on the world's health care system and it is recognized as a major challenge in the elderly. There are only a few neuromodulation treatments for memory dysfunctions. Open loop deep brain stimulation is such a treatment for memory improvement, but with limited success and conflicting results. In recent years closed-loop neuroprosthesis systems able to simultaneously record signals during behavioral tasks and generate with the use of internal neural factors the precise timing of stimulation patterns are presented as attractive alternatives and show promise in memory enhancement and restoration. A few such strides have already been made in both animals and humans, but with limited insights into their mechanisms of action. Here, I discuss why a deep neuromimetic computing approach linking multiple levels of description, mimicking the dynamics of brain circuits, interfaced with recording and stimulating electrodes could enhance the performance of current memory prosthesis systems, shed light into the neurobiology of learning and memory and accelerate the progress of memory prosthesis research. I propose what the necessary components (nodes, structure, connectivity, learning rules, and physiological responses) of such a deep neuromimetic model should be and what type of data are required to train/test its performance, so it can be used as a true substitute of damaged brain areas capable of restoring/enhancing their missing memory formation capabilities. Considerations to neural circuit targeting, tissue interfacing, electrode placement/implantation, and multi-network interactions in complex cognition are also provided.

Electrophysiological and imaging evidence of sustained inhibition in limbic and frontal networks following deep brain stimulation for treatment refractory obsessive compulsive disorder

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder that arises from a complex interaction of environmental and genetic factors. Despite numerous pharmacological and behavioral interventions, approximately 10% of patients remain refractory. High-frequency deep brain stimulation (HF-DBS) has shown promising results for treatment-refractory OCD. We report the follow-up result of up to 6 years of 4 treatment-refractory OCD patients treated by HF-DBS. Targets of stimulation were the anterior limb of the internal capsule (ALIC) in two cases, and the nucleus accumbens (NAc) in the remaining cohort. The clinical profiles were quantified by the Yale-Brown obsessive-compulsive scale (Y-BOCS). Highly significant reductions in Y-BOCS scores were obtained from all patients during the follow-up period. A greater that 90% reduction in Y-BOCS, observed in the most successful case, was achieved with NAc HF-DBS. Y-BOCS scores in the other patients consistently achieved over 50% reductions in OCD symptoms. FDG-PET imaging indicated post-surgical reductions in metabolism, in not only targeted limbic networks, but also other frontal cortical and subcortical regions, suggesting that large-scale network modulation and inhibitions are associated with functional recovery in OCD. This study demonstrates that HF-DBS targeted to the ALIC and NAc is a safe and effective method for ameliorating intractable, treatment-refractory OCD symptoms. The NAc appeared to be the superior target for symptom reduction, and local inhibition of NAc activity and reduced frontal metabolism are key therapeutic indications.

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

Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease symptoms. The therapeutic benefits of deep brain stimulation are frequency-dependent, but the underlying physiological mechanisms remain unclear. To advance deep brain stimulation therapy an understanding of fundamental mechanisms is critical. The objectives of this study were to (i) compare the frequency-dependent effects on cell firing in subthalamic nucleus and substantia nigra pars reticulata; (ii) quantify frequency-dependent effects on short-term plasticity in substantia nigra pars reticulata; and (iii) investigate effects of continuous long-train high frequency stimulation (comparable to conventional deep brain stimulation) on synaptic plasticity. Two closely spaced (600 µm) microelectrodes were advanced into the subthalamic nucleus (n = 27) and substantia nigra pars reticulata (n = 14) of 22 patients undergoing deep brain stimulation surgery for Parkinson’s disease. Cell firing and evoked field potentials were recorded with one microelectrode during stimulation trains from the adjacent microelectrode across a range of frequencies (1–100 Hz, 100 µA, 0.3 ms, 50–60 pulses). Subthalamic firing attenuated with ≥20 Hz (P < 0.01) stimulation (silenced at 100 Hz), while substantia nigra pars reticulata decreased with ≥3 Hz (P < 0.05) (silenced at 50 Hz). Substantia nigra pars reticulata also exhibited a more prominent increase in transient silent period following stimulation. Patients with longer silent periods after 100 Hz stimulation in the subthalamic nucleus tended to have better clinical outcome after deep brain stimulation. At ≥30 Hz the first evoked field potential of the stimulation train in substantia nigra pars reticulata was potentiated (P < 0.05); however, the average amplitude of the subsequent potentials was rapidly attenuated (P < 0.01). This is suggestive of synaptic facilitation followed by rapid depression. Paired pulse ratios calculated at the beginning of the train revealed that 20 Hz (P < 0.05) was the minimum frequency required to induce synaptic depression. Lastly, the average amplitude of evoked field potentials during 1 Hz pulses showed significant inhibitory synaptic potentiation after long-train high frequency stimulation (P < 0.001) and these increases were coupled with increased durations of neuronal inhibition (P < 0.01). The subthalamic nucleus exhibited a higher frequency threshold for stimulation-induced inhibition than the substantia nigra pars reticulata likely due to differing ratios of GABA:glutamate terminals on the soma and/or the nature of their GABAergic inputs (pallidal versus striatal). We suggest that enhancement of inhibitory synaptic plasticity, and frequency-dependent potentiation and depression are putative mechanisms of deep brain stimulation. Furthermore, we foresee that future closed-loop deep brain stimulation systems (with more frequent off stimulation periods) may benefit from inhibitory synaptic potentiation that occurs after high frequency stimulation.

Multi-objective particle swarm optimization for postoperative deep brain stimulation targeting of subthalamic nucleus pathways

OBJECTIVE

The effectiveness of deep brain stimulation (DBS) therapy strongly depends on precise surgical targeting of intracranial leads and on clinical optimization of stimulation settings. Recent advances in surgical targeting, multi-electrode designs, and multi-channel independent current-controlled stimulation are poised to enable finer control in modulating pathways within the brain. However, the large stimulation parameter space enabled by these technologies also poses significant challenges for efficiently identifying the most therapeutic DBS setting for a given patient. Here, we present a computational approach for programming directional DBS leads that is based on a non-convex optimization framework for neural pathway targeting.

APPROACH

The algorithm integrates patient-specific pre-operative 7 T MR imaging, post-operative CT scans, and multi-objective particle swarm optimization (MOPSO) methods using dominance based-criteria and incorporating multiple neural pathways simultaneously. The algorithm was evaluated on eight patient-specific models of subthalamic nucleus (STN) DBS to identify electrode configurations and stimulation amplitudes to optimally activate or avoid six clinically relevant pathways: motor territory of STN, non-motor territory of STN, internal capsule, superior cerebellar peduncle, thalamic fasciculus, and hyperdirect pathway.

MAIN RESULTS

Across the patient-specific models, single-electrode stimulation showed significant correlations across modeled pathways, particularly for motor and non-motor STN efferents. The MOPSO approach was able to identify multi-electrode configurations that achieved improved targeting of motor STN efferents and hyperdirect pathway afferents than that achieved by any single-electrode monopolar setting at equivalent power levels.

SIGNIFICANCE

These results suggest that pathway targeting with patient-specific model-based optimization algorithms can efficiently identify non-trivial electrode configurations for enhancing activation of clinically relevant pathways. However, the results also indicate that inter-pathway correlations can limit selectivity for certain pathways even with directional DBS leads.

Simulation Study of Intermittent Axonal Block and Desynchronization Effect Induced by High-Frequency Stimulation of Electrical Pulses

Deep brain stimulation (DBS) has been successfully used in treating neural disorders in brain, such as Parkinson’s disease and epilepsy. However, the precise mechanisms of DBS remain unclear. Regular DBS therapy utilizes high-frequency stimulation (HFS) of electrical pulses. Among all of neuronal elements, axons are mostly inclined to be activated by electrical pulses. Therefore, the response of axons may play an important role in DBS treatment. To study the axonal responses during HFS, we developed a computational model of myelinated axon to simulate sequences of action potentials generated in single and multiple axons (an axon bundle) by stimulations. The stimulations are applied extracellularly by a point source of current pulses with a frequency of 50–200 Hz. Additionally, our model takes into account the accumulation of potassium ions in the peri-axonal spaces. Results show that the increase of extracellular potassium generates intermittent depolarization block in the axons during HFS. Under the state of alternate block and recovery, axons fire action potentials at a rate far lower than the frequency of stimulation pulses. In addition, the degree of axonal block is highly related to the distance between the axons and the stimulation point. The differences in the degree of block for individual axons in a bundle result in desynchronized firing among the axons. Stimulations with higher frequency and/or greater intensity can induce axonal block faster and increase the desynchronization effect on axonal firing. Presumably, the desynchronized axonal activity induced by HFS could generate asynchronous activity in the population of target neurons downstream thereby suppressing over-synchronized firing of neurons in pathological conditions. The desynchronization effect generated by intermittent activation of axons may be crucial for DBS therapy. The present study provides new insights into the mechanisms of DBS, which is significant for advancing the application of DBS.

Axonal Stimulations With a Higher Frequency Generate More Randomness in Neuronal Firing Rather Than Increase Firing Rates in Rat Hippocampus

Deep brain stimulation (DBS) has been used for treating many brain disorders. Clinical applications of DBS commonly require high-frequency stimulations (HFS, ∼100 Hz) of electrical pulses to obtain therapeutic efficacy. It is not clear whether the electrical energy of HFS functions other than generating firing of action potentials in neuronal elements. To address the question, we investigated the reactions of downstream neurons to pulse sequences with a frequency in the range 50-200 Hz at afferent axon fibers in the hippocampal CA1 region of anesthetized rats. The results show that the mean rates of neuronal firing induced by axonal HFS were similar even for an up to fourfold difference (200:50) in the number and thereby in the energy of electrical pulses delivered. However, HFS with a higher pulse frequency (100 or 200 Hz) generated more randomness in the firing pattern of neurons than a lower pulse frequency (50 Hz), which were quantitatively evaluated by the significant changes of two indexes, namely, the peak coefficients and the duty ratios of excitatory phase of neuronal firing, induced by different frequencies (50-200 Hz). The findings indicate that a large portion of the HFS energy might function to generate a desynchronization effect through a possible mechanism of intermittent depolarization block of neuronal membranes. The present study addresses the demand of high frequency for generating HFS-induced desynchronization in neuronal activity, which may play important roles in DBS therapy.

Clinical deep brain stimulation strategies for orientation-selective pathway activation

OBJECTIVE

This study investigated stimulation strategies to increase the selectivity of activating axonal pathways within the brain based on their orientations relative to clinical deep brain stimulation (DBS) lead implants.

APPROACH

Previous work has shown how varying electrode shape and controlling the primary electric field direction through preclinical electrode arrays can produce orientation-selective axonal stimulation. Here, we significantly extend those results using computational models to evaluate the degree to which clinical DBS leads can direct stimulus-induced electric fields and generate orientation-selective activation of fiber pathways in the brain. Orientation-selective pulse paradigms were evaluated in conceptual models and in patient-specific models of subthalamic nucleus (STN)-DBS for treating Parkinson's disease.

MAIN RESULTS

Single-contact monopolar or two-contact bipolar stimulation through clinical DBS leads with cylindrical electrodes primarily activated axons orientated parallel to the lead. Conversely, multi-contact monopolar stimulation with a cathode-leading pulse waveform selectively activated axons perpendicular to the DBS lead. Clinical DBS leads with segmented rows of electrodes and a single current source provided additional angular resolution for activating axons oriented 0°, ±22.5°, ±45°, ±67.5°, or 90° relative to the lead shaft. Employing multiple independent current sources to deliver unequal amounts of current through these leads further increased the angular resolution of activation relative to the lead shaft. The patient-specific models indicated that multi-contact cathode configurations, which are rarely used in clinical practice, could increase activation of the hyperdirect pathway collaterals projecting into STN (a putative therapeutic target), while minimizing direct activation of the corticospinal tract of internal capsule, which can elicit sensorimotor side-effects when stimulated.

SIGNIFICANCE

When combined with patient-specific tissue anisotropy and patient-specific anatomical morphologies of neural pathways responsible for therapy and side effects, orientation-selective DBS approaches show potential to significantly improve clinical outcomes of DBS therapy for a range of existing and investigational clinical indications.

Solenoidal Micromagnetic Stimulation Enables Activation of Axons With Specific Orientation

Electrical stimulation of the central and peripheral nervous systems - such as deep brain stimulation, spinal cord stimulation, and epidural cortical stimulation are common therapeutic options increasingly used to treat a large variety of neurological and psychiatric conditions. Despite their remarkable success, there are limitations which if overcome, could enhance outcomes and potentially reduce common side-effects. Micromagnetic stimulation (μMS) was introduced to address some of these limitations. One of the most remarkable properties is that μMS is theoretically capable of activating neurons with specific axonal orientations. Here, we used computational electromagnetic models of the μMS coils adjacent to neuronal tissue combined with axon cable models to investigate μMS orientation-specific properties. We found a 20-fold reduction in the stimulation threshold of the preferred axonal orientation compared to the orthogonal direction. We also studied the directional specificity of μMS coils by recording the responses evoked in the inferior colliculus of rodents when a pulsed magnetic stimulus was applied to the surface of the dorsal cochlear nucleus. The results confirmed that the neuronal responses were highly sensitive to changes in the μMS coil orientation. Accordingly, our results suggest that μMS has the potential of stimulating target nuclei in the brain without affecting the surrounding white matter tracts.

Frequency-dependent antidromic activation in thalamocortical relay neurons: effects of synaptic inputs

OBJECTIVE

Deep brain stimulation (DBS) generates action potentials (APs) in presynaptic axons and fibers of passage. The APs may be antidromically propagated to invade the cell body and/or orthodromically transmitted to downstream structures, thereby affecting widespread targets distant from the electrode. Activation of presynaptic terminals also causes trans-synaptic effects, which in turn alter the excitability of the post-synaptic neurons. Our aim was to determine how synaptic inputs affect the antidromic invasion of the cell body.

APPROACH

We used a biophysically-based multi-compartment model to simulate antidromic APs in thalamocortical relay (TC) neurons. We applied distributed synaptic inputs to the model and quantified how excitatory and inhibitory inputs contributed to the fidelity of antidromic activation over a range of antidromic frequencies.

MAIN RESULTS

Antidromic activation exhibited strong frequency dependence, which arose from the hyperpolarizing afterpotentials in the cell body and its respective recovery cycle. Low-frequency axonal spikes faithfully invaded the soma, whereas frequent failures of antidromic activation occurred at high frequencies. The frequency-dependent pattern of the antidromic activation masked burst-driver inputs to TC neurons from the cerebellum in a frequency-dependent manner. Antidromic activation also depended on the excitability of the cell body. Excitatory synaptic inputs improved the fidelity of antidromic activation by increasing the excitability, and inhibitory inputs suppressed antidromic activation by reducing soma excitability. Stimulus-induced depolarization of neuronal segments also facilitated antidromic propagation and activation.

SIGNIFICANCE

The results reveal that synaptic inputs, stimulus frequency, and electrode position regulate antidromic activation of the cell body during extracellular stimulation. These findings provide a biophysical basis for interpreting the widespread inhibition/activation of target nuclei during DBS.

Quantitative theory of deep brain stimulation of the subthalamic nucleus for the suppression of pathological rhythms in Parkinson's disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is modeled to explore the mechanisms of this effective, but poorly understood, treatment for motor symptoms of drug-refractory Parkinson's disease and dystonia. First, a neural field model of the corticothalamic-basal ganglia (CTBG) system is developed that reproduces key clinical features of Parkinson's disease, including its characteristic 4-8 Hz and 13-30 Hz electrophysiological signatures. Deep brain stimulation of the STN is then modeled and shown to suppress the pathological 13-30 Hz (beta) activity for physiologically realistic and optimized stimulus parameters. This supports the idea that suppression of abnormally coherent activity in the CTBG system is a major factor in DBS therapy for Parkinson's disease, by permitting normal dynamics to resume. At high stimulus intensities, nonlinear effects in the target population mediate wave-wave interactions between resonant beta activity and the stimulus pulse train, leading to complex spectral structure that shows remarkable similarity to that seen in steady-state evoked potential experiments.

The effects of paranodal myelin damage on action potential depend on axonal structure

Biophysical computational models of axons provide an important tool for quantifying the effects of injury and disease on signal conduction characteristics. Several studies have used generic models to study the average behavior of healthy and injured axons; however, few studies have included the effects of normal structural variation on the simulated axon's response to injury. The effects of variations in physiological characteristics on axonal function were mapped by altering the structure of the nodal, paranodal, and juxtaparanodal regions across reported values in three different caliber axons (1, 2, and 5.7 μm). Myelin detachment and retraction were simulated to quantify the effects of each injury mechanism on signal conduction. Conduction velocity was most affected by axonal fiber diameter (89%), while membrane potential amplitude was most affected by nodal length (86%) in healthy axons. Postinjury axonal functionality was most affected by myelin detachment in the paranodal and juxtaparanodal regions when retraction and detachment were modeled simultaneously. The efficacy of simulated potassium channel blockers on restoring membrane potential and velocity varied with axonal caliber and injury type. The structural characteristics of axons affect their functional response to myelin retraction and detachment and their subsequent response to potassium channel blocker treatment.

High frequency stimulation of afferent fibers generates asynchronous firing in the downstream neurons in hippocampus through partial block of axonal conduction

Deep brain stimulation (DBS) is effective for treating neurological disorders in clinic. However, the therapeutic mechanisms of high-frequency stimulation (HFS) of DBS have not yet been elucidated. Previous studies have suggested that HFS-induced changes in axon conduction could have important contributions to the DBS effects and desiderate further studies. To investigate the effects of prolonged HFS of afferent axons on the firing of downstream neurons, HFS trains of 100 and 200Hz were applied on the Schaffer collaterals of the hippocampal CA1 region in anaesthetized rats. Single unit activity of putative pyramidal cells and interneurons in the downstream region was analyzed during the late periods of prolonged HFS when the axonal conduction was blocked. The results show that the firing rates of both pyramidal cells and interneurons increased rather than decreased during the period of axon block. However, the firing rates were far smaller than the stimulation frequency of HFS. In addition, the firing pattern of pyramidal cells changed from typical bursts during baseline recordings into regular single spikes during HFS periods. Furthermore, the HFS produced asynchronous firing in the downstream neurons in contrast to the synchronous firing induced by single pulses. Presumably, the HFS-induced block of axonal conduction was not complete. During the period of partial block, individual axons could recover intermittently and independently, and drive the downstream neurons to fire in an asynchronous pattern. This axonal mechanism of HFS provides a novel explanation for how DBS could replace an original pattern of neuronal activity by a HFS-modulated asynchronous firing in the target region thereby generating the therapeutic effects of DBS.

Particle swarm optimization for programming deep brain stimulation arrays

OBJECTIVE

Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently.

APPROACH

Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption.

MAIN RESULTS

The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches.

SIGNIFICANCE

The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Differences in globus pallidus neuronal firing rates and patterns relate to different disease biology in children with dystonia

BACKGROUND

The pathophysiology underlying different types of dystonia is not yet understood. We report microelectrode data from the globus pallidus interna (GPi) and globus pallidus externa (GPe) in children undergoing deep brain stimulation (DBS) for dystonia and investigate whether GPi and GPe firing rates differ between dystonia types.

METHODS

Single pass microelectrode data were obtained to guide electrode position in 44 children (3.3-18.1 years, median 10.7) with the following dystonia types: 14 primary, 22 secondary Static and 8 progressive secondary to neuronal brain iron accumulation (NBIA). Preoperative stereotactic MRI determined coordinates for the GPi target. Digitised spike trains were analysed offline, blind to clinical data. Electrode placement was confirmed by a postoperative stereotactic CT scan.

FINDINGS

We identified 263 GPi and 87 GPe cells. Both GPi and GPe firing frequencies differed significantly with dystonia aetiology. The median GPi firing frequency was higher in the primary group than in the secondary static group (13.5 Hz vs 9.6 Hz; p=0.002) and higher in the NBIA group than in either the primary (25 Hz vs 13.5 Hz; p=0.006) or the secondary static group (25 Hz vs 9.6 Hz; p=0.00004). The median GPe firing frequency was higher in the NBIA group than in the secondary static group (15.9 Hz vs 7 Hz; p=0.013). The NBIA group also showed a higher proportion of regularly firing GPi cells compared with the other groups (p<0.001). A higher proportion of regular GPi cells was also seen in patients with fixed/tonic dystonia compared with a phasic/dynamic dystonia phenotype (p<0.001). The GPi firing frequency showed a positive correlation with 1-year outcome from DBS measured by improvement in the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS-m) score (p=0.030). This association was stronger for the non-progressive patients (p=0.006).

INTERPRETATION

Pallidal firing rates and patterns differ significantly with dystonia aetiology and phenotype. Identification of specific firing patterns may help determine targets and patient-specific protocols for neuromodulation therapy.

FUNDING

National Institute of Health Research, Guy's and St. Thomas' Charity, Dystonia Society UK, Action Medical Research, German National Academic Foundation.

Deep brain stimulation in the central nucleus of the amygdala decreases 'wanting' and 'liking' of food rewards

We investigated the potential of deep brain stimulation (DBS) in the central nucleus of the amygdala (CeA) in rats to modulate functional reward mechanisms. The CeA is the major output of the amygdala with direct connections to the hypothalamus and gustatory brainstem, and indirect connections with the nucleus accumbens. Further, the CeA has been shown to be involved in learning, emotional integration, reward processing, and regulation of feeding. We hypothesized that DBS, which is used to treat movement disorders and other brain dysfunctions, might block reward motivation. In rats performing a lever-pressing task to obtain sugar pellet rewards, we stimulated the CeA and control structures, and compared stimulation parameters. During CeA stimulation, animals stopped working for rewards and rejected freely available rewards. Taste reactivity testing during DBS exposed aversive reactions to normally liked sucrose tastes and even more aversive taste reactions to normally disliked quinine tastes. Interestingly, given the opportunity, animals implanted in the CeA would self-stimulate with 500 ms trains of stimulation at the same frequency and current parameters as continuous stimulation that would stop reward acquisition. Neural recordings during DBS showed that CeA neurons were still active and uncovered inhibitory-excitatory patterns after each stimulus pulse indicating possible entrainment of the neural firing with DBS. In summary, DBS modulation of CeA may effectively usurp normal neural activity patterns to create an 'information lesion' that not only decreased motivational 'wanting' of food rewards, but also blocked 'liking' of rewards.

Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets

Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with radially distributed electrodes raises practical design and stimulation programming challenges. We used computational modeling to investigate: (1) how the number of radial electrodes impact the ability to steer, shift, and sculpt a region of neural activation (RoA), and (2) which RoA features are best used in combination with machine learning classifiers to predict programming settings to target a particular area near the lead. Stimulation configurations were modeled using 27 lead designs with one to nine radially distributed electrodes. The computational modeling framework consisted of a three-dimensional finite element tissue conductance model in combination with a multi-compartment biophysical axon model. For each lead design, two-dimensional threshold-dependent RoAs were calculated from the computational modeling results. The models showed more radial electrodes enabled finer resolution RoA steering; however, stimulation amplitude, and therefore spatial extent of the RoA, was limited by charge injection and charge storage capacity constraints due to the small electrode surface area for leads with more than four radially distributed electrodes. RoA shifting resolution was improved by the addition of radial electrodes when using uniform multi-cathode stimulation, but non-uniform multi-cathode stimulation produced equivalent or better resolution shifting without increasing the number of radial electrodes. Robust machine learning classification of 15 monopolar stimulation configurations was achieved using as few as three geometric features describing a RoA. The results of this study indicate that, for a clinical-scale DBS lead, more than four radial electrodes minimally improved in the ability to steer, shift, and sculpt axonal activation around a DBS lead and a simple feature set consisting of the RoA center of mass and orientation enabled robust machine learning classification. These results provide important design constraints for future development of high-density DBS arrays.

Deep brain stimulation in the globus pallidus externa promotes sleep

The basal ganglia, a network of subcortical structures, play a critical role in movements, sleep and mental behavior. Basal ganglia disorders such as Parkinson's disease and Huntington's disease affect sleep. Deep brain stimulation (DBS) to treat motor symptoms in Parkinson's disease can ameliorate sleep disturbances. Our series of previous studies lead the hypothesis that dopamine, acting on D2 receptors on the striatopallidal terminals, enhances activity in the globus pallidus externa (GPe) and promotes sleep. Here, we tested if DBS in the GPe promotes sleep in rats. We found that unilateral DBS (180 Hz at 100 μA) in the GPe in rats significantly increased both non-rapid eye movement and rapid eye movement sleep compared to sham DBS stimulation. The EEG power spectrum of sleep induced by DBS was similar to that of the baseline sleep, and sleep latency was not affected by DBS. The GPe is potentially a better site for DBS to treat both insomnia and motor disorders caused by basal ganglia dysfunction.

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

The proceedings of the 3rd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, imaging, and computational work on DBS for the treatment of neurological and neuropsychiatric disease. Significant innovations of the past year are emphasized. The Think Tank's contributors represent a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers, and members of industry. Presentations and discussions covered a broad range of topics, including policy and advocacy considerations for the future of DBS, connectomic approaches to DBS targeting, developments in electrophysiology and related strides toward responsive DBS systems, and recent developments in sensor and device technologies.

Failure to suppress low-frequency neuronal oscillatory activity underlies the reduced effectiveness of random patterns of deep brain stimulation

Subthalamic nucleus (STN) deep brain stimulation (DBS) is an established treatment for the motor symptoms of Parkinson's disease (PD). However, the mechanisms of action of DBS are unknown. Random temporal patterns of DBS are less effective than regular DBS, but the neuronal basis for this dependence on temporal pattern of stimulation is unclear. Using a rat model of PD, we quantified the changes in behavior and single-unit activity in globus pallidus externa and substantia nigra pars reticulata during high-frequency STN DBS with different degrees of irregularity. Although all stimulus trains had the same average rate, 130-Hz regular DBS more effectively reversed motor symptoms, including circling and akinesia, than 130-Hz irregular DBS. A mixture of excitatory and inhibitory neuronal responses was present during all stimulation patterns, and mean firing rate did not change during DBS. Low-frequency (7-10 Hz) oscillations of single-unit firing times present in hemiparkinsonian rats were suppressed by regular DBS, and neuronal firing patterns were entrained to 130 Hz. Irregular patterns of DBS less effectively suppressed 7- to 10-Hz oscillations and did not regularize firing patterns. Random DBS resulted in a larger proportion of neuron pairs with increased coherence at 7-10 Hz compared with regular 130-Hz DBS, which suggested that long pauses (interpulse interval >50 ms) during random DBS facilitated abnormal low-frequency oscillations in the basal ganglia. These results suggest that the efficacy of high-frequency DBS stems from its ability to regularize patterns of neuronal firing and thereby suppress abnormal oscillatory neural activity within the basal ganglia.

Tractography patterns of subthalamic nucleus deep brain stimulation

Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process.

Common therapeutic mechanisms of pallidal deep brain stimulation for hypo- and hyperkinetic movement disorders

Abnormalities in cortico-basal ganglia (CBG) networks can cause a variety of movement disorders ranging from hypokinetic disorders, such as Parkinson's disease (PD), to hyperkinetic conditions, such as Tourette syndrome (TS). Each condition is characterized by distinct patterns of abnormal neural discharge (dysrhythmia) at both the local single-neuron level and the global network level. Despite divergent etiologies, behavioral phenotypes, and neurophysiological profiles, high-frequency deep brain stimulation (HF-DBS) in the basal ganglia has been shown to be effective for both hypo- and hyperkinetic disorders. The aim of this review is to compare and contrast the electrophysiological hallmarks of PD and TS phenotypes in nonhuman primates and discuss why the same treatment (HF-DBS targeted to the globus pallidus internus, GPi-DBS) is capable of ameliorating both symptom profiles. Recent studies have shown that therapeutic GPi-DBS entrains the spiking of neurons located in the vicinity of the stimulating electrode, resulting in strong stimulus-locked modulations in firing probability with minimal changes in the population-scale firing rate. This stimulus effect normalizes/suppresses the pathological firing patterns and dysrhythmia that underlie specific phenotypes in both the PD and TS models. We propose that the elimination of pathological states via stimulus-driven entrainment and suppression, while maintaining thalamocortical network excitability within a normal physiological range, provides a common therapeutic mechanism through which HF-DBS permits information transfer for purposive motor behavior through the CBG while ameliorating conditions with widely different symptom profiles.

Spherical statistics for characterizing the spatial distribution of deep brain stimulation effects on neuronal activity

BACKGROUND

Computational models of deep brain stimulation (DBS) have played a key role in understanding its physiological mechanisms. By estimating a volume of tissue directly modulated by DBS, one can relate the neuronal pathways within those volumes to the therapeutic efficacy of a particular DBS setting.

NEW METHOD

A spherical statistical framework is described to quantify and determine salient features of such morphologies using visualization techniques, empirical shape analysis, and formal hypothesis testing. This framework is shown using a 3D model of thalamocortical neurons surrounding a radially-segmented DBS array.

RESULTS

We show that neuronal population volumes modulated by various DBS electrode configurations can be characterized by parametric distribution models, such as Kent and Watson girdle models. Distribution parameters were found to change with stimulus settings, including amplitude and radial distance from the DBS array. Increasing stimulation amplitude through a single electrode resulted in more diffuse neuronal activation and increased rotational symmetry about the mean direction of the activated population. When stimulation amplitude was held constant, the activated neuronal population distribution was more concentrated with distance from the DBS array and was also more rotationally asymmetric. We also show how data representation (e.g. stimulus-entrained cell body vs. axon node) can significantly alter model distribution shape.

COMPARISON TO EXISTING METHODS

This statistical framework provides a quantitative method to analyze the spatial morphologies of DBS-induced effects on neuronal activity.

CONCLUSIONS

The application of spherical statistics to assess spatial distributions of neuronal activity has potential usefulness for numerous other recording, labeling, and stimulation modalities.