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.

Multiformity of extracellular microelectrode recordings from Aδ neurons in the dorsal root ganglia: a computational modeling study.

Microelectrodes serve as a fundamental tool in electrophysiology research throughout the nervous system, providing a means of exploring neural function with a high resolution of neural firing information. We constructed a hybrid computational model using the finite element method and multicompartment cable models to explore factors that contribute to extracellular voltage waveforms that are produced by sensory pseudounipolar neurons, specifically smaller A-type neurons, and that are recorded by microelectrodes in dorsal root ganglia. The finite element method model included a dorsal root ganglion, surrounding tissues, and a planar microelectrode array. We built a multicompartment neuron model with multiple trajectories of the glomerular initial segment found in many A-type sensory neurons. Our model replicated both the somatic intracellular voltage profile of Aδ low-threshold mechanoreceptor neurons and the unique extracellular voltage waveform shapes that are observed in experimental settings. Results from this model indicated that tortuous glomerular initial segment geometries can introduce distinct multiphasic properties into a neuron's recorded waveform. Our model also demonstrated how recording location relative to specific microanatomical components of these neurons, and recording distance from these components, can contribute to additional changes in the multiphasic characteristics and peak-to-peak voltage amplitude of the waveform. This knowledge may provide context for research employing microelectrode recordings of pseudounipolar neurons in sensory ganglia, including functional mapping and closed-loop neuromodulation. Furthermore, our simulations gave insight into the neurophysiology of pseudounipolar neurons by demonstrating how the glomerular initial segment aids in increasing the resistance of the stem axon and mitigating rebounding somatic action potentials.NEW & NOTEWORTHY We built a computational model of sensory neurons in the dorsal root ganglia to investigate factors that influence the extracellular waveforms recorded by microelectrodes. Our model demonstrates how the unique structure of these neurons can lead to diverse and often multiphasic waveform profiles depending on the location of the recording contact relative to microanatomical neural components. Our model also provides insight into the neurophysiological function of axon glomeruli that are often present in these neurons.

Neurotechnology for Pain.

Neurotechnologies for treating pain rely on electrical stimulation of the central or peripheral nervous system to disrupt or block pain signaling and have been commercialized to treat a variety of pain conditions. While their adoption is accelerating, neurotechnologies are still frequently viewed as a last resort, after many other treatment options have been explored. We review the pain conditions commonly treated with electrical stimulation, as well as the specific neurotechnologies used for treating those conditions. We identify barriers to adoption, including a limited understanding of mechanisms of action, inconsistent efficacy across patients, and challenges related to selectivity of stimulation and off-target side effects. We describe design improvements that have recently been implemented, as well as some cutting-edge technologies that may address the limitations of existing neurotechnologies. Addressing these challenges will accelerate adoption and change neurotechnologies from last-line to first-line treatments for people living with chronic pain.

Postural Changes in Spinal Cord Stimulation Thresholds: Current and Voltage Sources.

OBJECTIVE: Spinal cord stimulation (SCS) thresholds are known to change with body position; however, these changes have not been fully characterized for both "constant-voltage" and "constant-current" pulse generators. This study aimed to evaluate and quantify changes in psychophysical thresholds resulting from postural changes that may affect both conventional paresthesia-based SCS and novel paresthesia-free SCS technologies. MATERIALS AND METHODS: We measured perceptual, usage, and discomfort thresholds in four body positions (prone, supine, sitting, standing) in 149 consecutive patients, with temporary lower thoracic percutaneous epidural electrodes placed for treating persistent low back and leg pain. We trialed 119 patients with constant-voltage stimulators and 30 patients with constant-current stimulators. RESULTS: Moving from supine to the sitting, standing, or prone positions caused all three thresholds (perceptual, usage, and discomfort) to increase by 22% to 34% for constant-voltage stimulators and by 44% to 82% for constant-current stimulators. Changing from a seated to a supine position caused stimulation to exceed discomfort threshold significantly more often for constant-current (87%) than for constant-voltage (63%) stimulators (p = 0.01). CONCLUSIONS: Posture-induced changes in SCS thresholds occurred consistently as patients moved from lying (supine or prone) to upright (standing or sitting) positions. These changes were more pronounced for constant-current than for constant-voltage pulse generators and more often led to stimulation-evoked discomfort. These observations are consistent with postural changes in spinal cord position measured in imaging studies, and with computer model predictions of neural recruitment for these different spinal cord positions. These observations have implications for the design, implantation, and clinical application of spinal cord stimulators, not only for conventional paresthesia-based SCS but also for paresthesia-free SCS.

A Definition of Neuromodulation and Classification of Implantable Electrical Modulation for Chronic Pain.

OBJECTIVES: Neuromodulation therapies use a variety of treatment modalities (eg, electrical stimulation) to treat chronic pain. These therapies have experienced rapid growth that has coincided with escalating confusion regarding the nomenclature surrounding these neuromodulation technologies. Furthermore, studies are often published without a complete description of the effective stimulation dose, making it impossible to replicate the findings. To improve clinical care and facilitate dissemination among the public, payors, research groups, and regulatory bodies, there is a clear need for a standardization of terms. APPROACH: We formed an international group of authors comprising basic scientists, anesthesiologists, neurosurgeons, and engineers with expertise in neuromodulation. Because the field of neuromodulation is extensive, we chose to focus on creating a taxonomy and standardized definitions for implantable electrical modulation of chronic pain. RESULTS: We first present a consensus definition of neuromodulation. We then describe a classification scheme based on the 1) intended use (the site of modulation and its indications) and 2) physical properties (waveforms and dose) of a neuromodulation therapy. CONCLUSIONS: This framework will help guide future high-quality studies of implantable neuromodulatory treatments and improve reporting of their findings. Standardization with this classification scheme and clear definitions will help physicians, researchers, payors, and patients better understand the applications of implantable electrical modulation for pain and guide informed treatment decisions.

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.

Model-Based Optimization of Spinal Cord Stimulation for Inspiratory Muscle Activation.

OBJECTIVE: High-frequency spinal cord stimulation (HF-SCS) is a potential method to provide natural and effective inspiratory muscle pacing in patients with ventilator-dependent spinal cord injuries. Experimental data have demonstrated that HF-SCS elicits physiological activation of the diaphragm and inspiratory intercostal muscles via spinal cord pathways. However, the activation thresholds, extent of activation, and optimal electrode configurations (i.e., lead separation, contact spacing, and contact length) to activate these neural elements remain unknown. Therefore, the goal of this study was to use a computational modeling approach to investigate the direct effects of HF-SCS on the spinal cord and to optimize electrode design and stimulation parameters. MATERIALS AND METHODS: We developed a computer model of HF-SCS that consisted of two main components: 1) finite element models of the electric field generated during HF-SCS, and 2) multicompartment cable models of axons and motoneurons within the spinal cord. We systematically evaluated the neural recruitment during HF-SCS for several unique electrode designs and stimulation configurations to optimize activation of these neural elements. We then evaluated our predictions by testing two of these lead designs with in vivo canine experiments. RESULTS: Our model results suggested that within physiological stimulation amplitudes, HF-SCS activates both axons in the ventrolateral funiculi (VLF) and inspiratory intercostal motoneurons. We used our model to predict a lead design to maximize HF-SCS activation of these neural targets. We evaluated this lead design via in vivo experiments, and our computational model predictions demonstrated excellent agreement with our experimental testing. CONCLUSIONS: Our computational modeling and experimental results support the potential advantages of a lead design with longer contacts and larger edge-to-edge contact spacing to maximize inspiratory muscle activation during HF-SCS at the T2 spinal level. While these results need to be further validated in future studies, we believe that the results of this study will help improve the efficacy of HF-SCS technologies for inspiratory muscle pacing.

Glossary of Neurostimulation Terminology: A Collaborative Neuromodulation Foundation, Institute of Neuromodulation, and International Neuromodulation Society Project.

OBJECTIVE: Consistent terminology is necessary to facilitate communication, but limited efforts have addressed this need in the neurostimulation community. We set out to provide a useful and updated glossary for our colleagues and prospective patients. MATERIALS AND METHODS: This collaborative effort of the Neuromodulation Foundation (NF), the Institute of Neuromodulation (IoN), and the International Neuromodulation Society (INS) expands a glossary first published in 2007 for spinal cord stimulation. Peripheral nerve, dorsal root ganglion, deep brain, and motor cortex stimulation have been added to our scope. Volunteers from the collaborating entities used a nominal group process, consensus development panels, and the Delphi technique to reach consensus on inclusion and definition of terms. We created a glossary suitable for print and for expansion on the websites of the collaborating entities, which will offer the possibility of explaining definitions for a general audience. We excluded proprietary and brand names but included terms that have attracted proprietary interest without becoming brands or trademarks. We made an effort to be inclusive while also being concise and economical with space. RESULTS: We identified and defined 91 terms for this print edition and created an accompanying list of acronyms. As appropriate, we provided figures to illustrate the definitions. CONCLUSIONS: Although we refer to the glossary presented herein as the print edition, it can of course be viewed and searched electronically. NF, IoN, and INS will continue to collaborate on expanded web editions that can include hyperlinks for internal and external navigation. We believe this glossary will benefit our growing field by facilitating communication and mitigating inappropriate use of neurostimulation terms.

The Effect of Clinically Controllable Factors on Neural Activation During Dorsal Root Ganglion Stimulation.

OBJECTIVE: Dorsal root ganglion stimulation (DRGS) is an effective therapy for chronic pain, though its mechanisms of action are unknown. Currently, we do not understand how clinically controllable parameters (e.g., electrode position, stimulus pulse width) affect the direct neural response to DRGS. Therefore, the goal of this study was to utilize a computational modeling approach to characterize how varying clinically controllable parameters changed neural activation profiles during DRGS. MATERIALS AND METHODS: We coupled a finite element model of a human L5 DRG to multicompartment models of primary sensory neurons (i.e., Aα-, Aß-, Aδ-, and C-neurons). We calculated the stimulation amplitudes necessary to elicit one or more action potentials in each neuron, and examined how neural activation profiles were affected by varying clinically controllable parameters. RESULTS: In general, DRGS predominantly activated large myelinated Aα- and Aß-neurons. Shifting the electrode more than 2 mm away from the ganglion abolished most DRGS-induced neural activation. Increasing the stimulus pulse width to 500 µs or greater increased the number of activated Aδ-neurons, while shorter pulse widths typically only activated Aα- and Aß-neurons. Placing a cathode near a nerve root, or an anode near the ganglion body, maximized Aß-mechanoreceptor activation. Guarded active contact configurations did not activate more Aß-mechanoreceptors than conventional bipolar configurations. CONCLUSIONS: Our results suggest that DRGS applied with stimulation parameters within typical clinical ranges predominantly activates Aß-mechanoreceptors. In general, varying clinically controllable parameters affects the number of Aß-mechanoreceptors activated, although longer pulse widths can increase Aδ-neuron activation. Our data support several Neuromodulation Appropriateness Consensus Committee guidelines on the clinical implementation of DRGS.

Quantitative Sensory Testing of Spinal Cord and Dorsal Root Ganglion Stimulation in Chronic Pain Patients.

BACKGROUND/OBJECTIVES: The physiological mechanisms underlying the pain-modulatory effects of clinical neurostimulation therapies, such as spinal cord stimulation (SCS) and dorsal root ganglion stimulation (DRGS), are only partially understood. In this pilot prospective study, we used patient-reported outcomes (PROs) and quantitative sensory testing (QST) to investigate the physiological effects and possible mechanisms of action of SCS and DRGS therapies. MATERIALS AND METHODS: We tested 16 chronic pain patients selected for SCS and DRGS therapy, before and after treatment. PROs included pain intensity, pain-related symptoms (e.g., pain interference, pain coping, sleep interference) and disability, and general health status. QST included assessments of vibration detection theshold (VDT), pressure pain threshold (PPT) and tolerance (PPToL), temporal summation (TS), and conditioned pain modulation (CPM), at the most painful site. RESULTS: Following treatment, all participants reported significant improvements in PROs (e.g., reduced pain intensity [p < 0.001], pain-related functional impairment [or pain interference] and disability [p = 0.001 for both]; better pain coping [p = 0.03], sleep [p = 0.002]), and overall health [p = 0.005]). QST showed a significant treatment-induced increase in PPT (p = 0.002) and PPToL (p = 0.011), and a significant reduction in TS (p = 0.033) at the most painful site, but showed no effects on VDT and CPM. We detected possible associations between a few QST measures and a few PROs. Notably, higher TS was associated with increased pain interference scores at pre-treatment (r = 0.772, p = 0.009), and a reduction in TS was associated with the reduction in pain interference (r = 0.669, p = 0.034) and pain disability (r = 0.690, p = 0.027) scores with treatment. CONCLUSIONS: Our preliminary findings suggest significant clinical and therapeutic benefits associated with SCS and DRGS therapies, and the possible ability of these therapies to modulate pain processing within the central nervous system. Replication of our pilot findings in future, larger studies is necessary to characterize the physiological mechanisms of SCS and DRGS therapies.

Functional Magnetic Resonance Imaging Correlates of Ventral Striatal Deep Brain Stimulation for Poststroke Pain.

OBJECTIVE: Deep brain stimulation (DBS) for pain has largely been implemented in an uncontrolled manner to target the somatosensory component of pain, with research leading to mixed results. We have previously shown that patients with poststroke pain syndrome who were treated with DBS targeting the ventral striatum/anterior limb of the internal capsule (VS/ALIC) demonstrated a significant improvement in measures related to the affective sphere of pain. In this study, we sought to determine how DBS targeting the VS/ALIC modifies brain activation in response to pain. MATERIALS AND METHODS: Five patients with poststroke pain syndrome who were blinded to DBS status (ON/OFF) and six age- and sex-matched healthy controls underwent functional magnetic resonance imaging (fMRI) measuring blood oxygen level-dependent activation in a block design. In this design, each participant received heat stimuli to the affected or unaffected wrist area. Statistical comparisons were performed using fMRI z-maps. RESULTS: In response to pain, patients in the DBS OFF state showed significant activation (p < 0.001) in the same regions as healthy controls (thalamus, insula, and operculum) and in additional regions (orbitofrontal and superior convexity cortical areas). DBS significantly reduced activation of these additional regions and introduced foci of significant inhibitory activation (p < 0.001) in the hippocampi when painful stimulation was applied to the affected side. CONCLUSIONS: These findings suggest that DBS of the VS/ALIC modulates affective neural networks.

Evoked Potentials Recorded From the Spinal Cord During Neurostimulation for Pain: A Computational Modeling Study.

OBJECTIVES: Spinal cord stimulation (SCS) for pain is typically implemented in an open-loop manner using parameters that remain largely unchanged. To improve the overall efficacy and consistency of SCS, one closed-loop approach proposes to use evoked compound action potentials (ECAPs) recorded from the SCS lead(s) as a feedback control signal to guide parameter selection. The goal of this study was to use a computational modeling approach to investigate the source of these ECAP recordings and technical and physiological factors that affect their composition. METHODS: We developed a computational model that coupled a finite element model of lower thoracic SCS with multicompartment models of sensory axons within the spinal cord. We used a reciprocity-based approach to calculate SCS-induced ECAPs recorded from the SCS lead. RESULTS: Our model ECAPs contained a triphasic, P1, N1, P2 morphology. The model P2-N1 amplitudes and conduction velocities agreed with previous experimental data from human subjects. Model results suggested that the ECAPs are dominated by the activation of axons with diameters 8.7-10.0 µm located in the dorsal aspect of the spinal cord. We also observed changes in the ECAP amplitude and shape due to the electrode location relative to the vertebrae and spinal cord. CONCLUSION: Our modeling results suggest that clinically effective SCS relies on the activation of numerous axons within a narrow fiber diameter range and that several factors affect the composition of the ECAP recordings. These results can improve how we interpret and implement these recordings in a potential closed-loop approach to SCS.

Patient-Specific Analysis of Neural Activation During Spinal Cord Stimulation for Pain.

OBJECTIVE: Despite the widespread use of spinal cord stimulation (SCS) for chronic pain management, its neuromodulatory effects remain poorly understood. Computational models provide a valuable tool to study SCS and its effects on axonal pathways within the spinal cord. However, these models must include sufficient detail to correlate model predictions with clinical effects, including patient-specific data. Therefore, the goal of this study was to investigate axonal activation at clinically relevant SCS parameters using a computer model that incorporated patient-specific anatomy and electrode locations. METHODS: We developed a patient-specific computer model for a patient undergoing SCS to treat chronic pain. This computer model consisted of two main components: 1) finite element model of the extracellular voltages generated by SCS and 2) multicompartment cable models of axons in the spinal cord. To determine the potential significance of a patient-specific approach, we also performed simulations with standard canonical models of SCS. We used the computer models to estimate axonal activation at clinically measured sensory, comfort, and discomfort thresholds. RESULTS: The patient-specific and canonical models predicted significantly different axonal activation. Relative to the canonical models, the patient-specific model predicted sensory threshold estimates that were more consistent with the corresponding clinical measurements. These results suggest that it is important to account for sources of interpatient variability (e.g., anatomy, electrode locations) in model-based analysis of SCS. CONCLUSIONS: This study demonstrates the potential for patient-specific computer models to quantitatively describe the axonal response to SCS and to address scientific questions related to clinical SCS.

Objective Measures to Characterize the Physiological Effects of Spinal Cord Stimulation in Neuropathic Pain: A Literature Review.

OBJECTIVE: The physiological mechanisms behind the therapeutic effects of spinal cord stimulation (SCS) are only partially understood. Our aim was to perform a literature review of studies that used objective measures to characterize mechanisms of action of SCS in neuropathic pain patients. MATERIALS AND METHODS: We searched the PubMed data base to identify clinical studies that used objective measures to assess the effects of SCS in neuropathic pain. We extracted the study factors (e.g., type of measure, diagnoses, painful area[s], and SCS parameters) and outcomes from the included studies. RESULTS: We included 67 studies. Of these, 24 studies used neurophysiological measures, 14 studies used functional neuroimaging techniques, three studies used a combination of neurophysiological and functional neuroimaging techniques, 14 studies used quantitative sensory testing, and 12 studies used proteomic, vascular, and/or pedometric measures. Our findings suggest that SCS largely inhibits somatosensory processing and/or spinal nociceptive activity. Our findings also suggest that SCS modulates activity across specific regions of the central nervous system that play a prominent role in the sensory and emotional functions of pain. CONCLUSIONS: SCS appears to modulate pain via spinal and/or supraspinal mechanisms of action (e.g., pain gating, descending pain inhibition). However, to better understand the mechanisms of action of SCS, we believe that it is necessary to carry out systematic, controlled, and well-powered studies using objective patient measures. To optimize the clinical effectiveness of SCS for neuropathic pain, we also believe that it is necessary to develop and implement patient-specific approaches.

Biophysical basis of subthalamic local field potentials recorded from deep brain stimulation electrodes.

Clinical deep brain stimulation (DBS) technology is evolving to enable chronic recording of local field potentials (LFPs) that represent electrophysiological biomarkers of the underlying disease state. However, little is known about the biophysical basis of LFPs, or how the patient's unique brain anatomy and electrode placement impact the recordings. Therefore, we developed a patient-specific computational framework to analyze LFP recordings within a clinical DBS context. We selected a subject with Parkinson's disease implanted with a Medtronic Activa PC+S DBS system and reconstructed their subthalamic nucleus (STN) and DBS electrode location using medical imaging data. The patient-specific STN volume was populated with 235,280 multicompartment STN neuron models, providing a neuron density consistent with histological measurements. Each neuron received time-varying synaptic inputs and generated transmembrane currents that gave rise to the LFP signal recorded at DBS electrode contacts residing in a finite element volume conductor model. We then used the model to study the role of synchronous beta-band inputs to the STN neurons on the recorded power spectrum. Three bipolar pairs of simultaneous clinical LFP recordings were used in combination with an optimization algorithm to customize the neural activity parameters in the model to the patient. The optimized model predicted a 2.4-mm radius of beta-synchronous neurons located in the dorsolateral STN. These theoretical results enable biophysical dissection of the LFP signal at the cellular level with direct comparison to the clinical recordings, and the model system provides a scientific platform to help guide the design of DBS technology focused on the use of subthalamic beta activity in closed-loop algorithms. NEW & NOTEWORTHY The analysis of deep brain stimulation of local field potential (LFP) data is rapidly expanding from scientific curiosity to the basis for clinical biomarkers capable of improving the therapeutic efficacy of stimulation. With this growing clinical importance comes a growing need to understand the underlying electrophysiological fundamentals of the signals and the factors contributing to their modulation. Our model reconstructs the clinical LFP from first principles and highlights the importance of patient-specific factors in dictating the signals recorded.

Deep brain stimulation of the ventral striatal area for poststroke pain syndrome: a magnetoencephalography study.

Poststroke pain syndrome (PSPS) is an often intractable disorder characterized by hemiparesis associated with unrelenting chronic pain. Although traditional analgesics have largely failed, integrative approaches targeting affective-cognitive spheres have started to show promise. Recently, we demonstrated that deep brain stimulation (DBS) of the ventral striatal area significantly improved the affective sphere of pain in patients with PSPS. In the present study, we examined whether electrophysiological correlates of pain anticipation were modulated by DBS that could serve as signatures of treatment effects. We recorded event-related fields (ERFs) of pain anticipation using magnetoencephalography (MEG) in 10 patients with PSPS preoperatively and postoperatively in DBS OFF and ON states. Simple visual cues evoked anticipation as patients awaited a painful (PS) or nonpainful stimulus (NPS) to the nonaffected or affected extremity. Preoperatively, ERFs showed no difference between PS and NPS anticipation to the affected extremity, possibly due to loss of salience in a network saturated by pain experience. DBS significantly modulated the early N1, consistent with improvements in affective networks involving restoration of salience and discrimination capacity. Additionally, DBS suppressed the posterior P2 (aberrant anticipatory anxiety) while enhancing the anterior N1 (cognitive and emotional regulation) in responders. DBS-induced changes in ERFs could potentially serve as signatures for clinical outcomes. NEW & NOTEWORTHY We examined the electrophysiological correlates of pain affect in poststroke pain patients who underwent deep brain stimulation (DBS) targeting the ventral striatal area under a randomized, controlled trial. DBS significantly modulated early event-related components, particularly N1 and P2, measured with magnetoencephalography during a pain anticipatory task, compared with baseline and the DBS-OFF condition, pointing to possible mechanisms of action. DBS-induced changes in event-related fields could potentially serve as biomarkers for clinical outcomes.

Randomized clinical trial of deep brain stimulation for poststroke pain.

OBJECTIVE: The experience with deep brain stimulation (DBS) for pain is largely based on uncontrolled studies targeting the somatosensory pathways, with mixed results. We hypothesized that targeting limbic neural pathways would modulate the affective sphere of pain and alleviate suffering. METHODS: We conducted a prospective, double-blinded, randomized, placebo-controlled, crossover study of DBS targeting the ventral striatum/anterior limb of the internal capsule (VS/ALIC) in 10 patients with poststroke pain syndrome. One month after bilateral DBS, patients were randomized to active DBS or sham for 3 months, followed by crossover for another 3-month period. The primary endpoint was a ≥50% improvement on the Pain Disability Index in 50% of patients with active DBS compared to sham. This 6-month blinded phase was followed by an 18-month open stimulation phase. RESULTS: Nine participants completed randomization. Although this trial was negative for its primary and secondary endpoints, we did observe significant differences in multiple outcome measures related to the affective sphere of pain (eg, Montgomery-Åsberg Depression Rating Scale, Beck Depression Inventory, Affective Pain Rating Index of the Short-Form McGill Pain Questionnaire). Fourteen serious adverse events were recorded and resolved. INTERPRETATION: VS/ALIC DBS to modulate the affective sphere of pain represents a paradigm shift in chronic pain management. Although this exploratory study was negative for its primary endpoint, VS/ALIC DBS demonstrated an acceptable safety profile and statistically significant improvements on multiple outcome measures related to the affective sphere of pain. Therefore, we believe these results justify further work on neuromodulation therapies targeting the affective sphere of pain. Ann Neurol 2017;81:653-663.

Pain anticipatory phenomena in patients with central poststroke pain: a magnetoencephalography study.

Central poststroke pain (CPSP) is characterized by hemianesthesia associated with unrelenting chronic pain. The final pain experience stems from interactions between sensory, affective, and cognitive components of chronic pain. Hence, managing CPSP will require integrated approaches aimed not only at the sensory but also the affective-cognitive spheres. A better understanding of the brain's processing of pain anticipation is critical for the development of novel therapeutic approaches that target affective-cognitive networks and alleviate pain-related disability. We used magnetoencephalography (MEG) to characterize the neural substrates of pain anticipation in patients suffering from intractable CPSP. Simple visual cues evoked anticipation while patients awaited impending painful (PS), nonpainful (NPS), or no stimulus (NOS) to their nonaffected and affected extremities. MEG responses were studied at gradiometer level using event-related fields analysis and time-frequency oscillatory analysis upon source localization. On the nonaffected side, significantly greater responses were recorded during PS. PS (vs. NPS and NOS) exhibited significant parietal and frontal cortical activations in the beta and gamma bands, respectively, whereas NPS (vs. NOS) displayed greater activation in the orbitofrontal cortex. On the affected extremity, PS (vs. NPS) did not show significantly greater responses. These data suggest that anticipatory phenomena can modulate neural activity when painful stimuli are applied to the nonaffected extremity but not the affected extremity in CPSP patients. This dichotomy may stem from the chronic effects of pain on neural networks leading to habituation or saturation. Future clinically effective therapies will likely be associated with partial normalization of the neurophysiological correlates of pain anticipation.

Computational analysis of kilohertz frequency spinal cord stimulation for chronic pain management.

BACKGROUND: Kilohertz frequency spinal cord stimulation (KHFSCS) is an emerging therapy for treating refractory neuropathic pain. Although KHFSCS has the potential to improve the lives of patients experiencing debilitating pain, its mechanisms of action are unknown and thus it is difficult to optimize its development. Therefore, the goal of this study was to use a computer model to investigate the direct effects of KHFSCS on specific neural elements of the spinal cord. METHODS: This computer model consisted of two main components: (1) finite element models of the electric field generated by KHFSCS and (2) multicompartment cable models of axons in the spinal cord. Model analysis permitted systematic investigation into a number of variables (e.g., dorsal cerebrospinal fluid thickness, lead location, fiber collateralization, and fiber size) and their corresponding effects on excitation and conduction block thresholds during KHFSCS. RESULTS: The results of this study suggest that direct excitation of large-diameter dorsal column or dorsal root fibers require high stimulation amplitudes that are at the upper end or outside of the range used in clinical KHFSCS (i.e., 0.5 to 5 mA). Conduction block was only possible within the clinical range for a thin dorsal cerebrospinal fluid layer. CONCLUSIONS: These results suggest that clinical KHFSCS may not function through direct activation or conduction block of dorsal column or dorsal root fibers. Although these results should be validated with further studies, the authors propose that additional concepts and/or alternative hypotheses should be considered when examining the pain relief mechanisms of KHFSCS.

Does high-frequency stimulation of sensory axons break the causal link between pain relief and paresthesia?

Neurostimulation produces unnatural cutaneous sensations with potent analgesic effects in pain syndromes. In this issue of Neuron, Sagalajev et al.1 demonstrate that these sensations are an epiphenomenon and explain how high-frequency stimulation can provide analgesia without these unnecessary sensations.