Quantifying Pain Location and Intensity with Multimodal Pain Body Diagrams.

To quantify an individual's subjective pain severity, standardized pain rating scales such as the numeric rating scale (NRS), visual analog scale (VAS), or McGill pain questionnaire (MPQ) are commonly used to assess pain on a numerical scale. However, these scales are often biased and fail to capture the complexity of pain experiences. In contrast, clinical practice often requires patients to report areas of pain by drawing on a body diagram, which is an effective but qualitative tool. The method presented here extracts quantifiable metrics from pain body diagrams (PBDs) which are validated against the NRS, VAS, and MPQ pain scales. By using a novel pressure-hue transformation on a digital tablet, different drawing pressures applied with a digital stylus can be represented as different hues on a PBD. This produces a visually intuitive diagram of hues ranging from green to blue to red, representing mild to moderate to most painful regions, respectively. To quantify each PBD, novel pain metrics were defined: (1) PBD mean intensity, which equals the sum of each pixel's hue value divided by the number of colored pixels, (2) PBD coverage, which equals the number of colored pixels divided by the total number of pixels on the body, and (3) PBD sum intensity, which equals the sum of all pixels' hue values. Using correlation and information theory analyses, these PBD metrics were shown to have high concordance with standardized pain metrics, including NRS, VAS and MPQ. In conclusion, PBDs can provide novel spatial and quantitative information that can be repeatedly measured and tracked over time to comprehensively characterize a participant's pain experience.

Network targets for therapeutic brain stimulation: towards personalized therapy for pain.

Precision neuromodulation of central brain circuits is a promising emerging therapeutic modality for a variety of neuropsychiatric disorders. Reliably identifying in whom, where, and in what context to provide brain stimulation for optimal pain relief are fundamental challenges limiting the widespread implementation of central neuromodulation treatments for chronic pain. Current approaches to brain stimulation target empirically derived regions of interest to the disorder or targets with strong connections to these regions. However, complex, multidimensional experiences like chronic pain are more closely linked to patterns of coordinated activity across distributed large-scale functional networks. Recent advances in precision network neuroscience indicate that these networks are highly variable in their neuroanatomical organization across individuals. Here we review accumulating evidence that variable central representations of pain will likely pose a major barrier to implementation of population-derived analgesic brain stimulation targets. We propose network-level estimates as a more valid, robust, and reliable way to stratify personalized candidate regions. Finally, we review key background, methods, and implications for developing network topology-informed brain stimulation targets for chronic pain.

First-in-human prediction of chronic pain state using intracranial neural biomarkers.

Chronic pain syndromes are often refractory to treatment and cause substantial suffering and disability. Pain severity is often measured through subjective report, while objective biomarkers that may guide diagnosis and treatment are lacking. Also, which brain activity underlies chronic pain on clinically relevant timescales, or how this relates to acute pain, remains unclear. Here four individuals with refractory neuropathic pain were implanted with chronic intracranial electrodes in the anterior cingulate cortex and orbitofrontal cortex (OFC). Participants reported pain metrics coincident with ambulatory, direct neural recordings obtained multiple times daily over months. We successfully predicted intraindividual chronic pain severity scores from neural activity with high sensitivity using machine learning methods. Chronic pain decoding relied on sustained power changes from the OFC, which tended to differ from transient patterns of activity associated with acute, evoked pain states during a task. Thus, intracranial OFC signals can be used to predict spontaneous, chronic pain state in patients.

Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury.

DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.

Epidural Spinal Electrogram Provides Direct Spinal Recordings in Awake Human Participants.

Little is known about the electrophysiological activity of the spinal cord during voluntary movement control in humans. We present a novel method for recording electrophysiological activity from the human spinal cord using implanted epidural electrodes during naturalistic movements including overground walking. Spinal electrograms (SEGs) were recorded from epidural electrodes implanted as part of a test trial for patients with chronic pain undergoing evaluation for spinal cord stimulation. Externalized ends of the epidural leads were connected to an external amplifier to capture SEGs. Electromyographic and accelerometry data from the upper and lower extremities were collected using wireless sensors and synchronized to the SEG data. Patients were instructed to perform various arm and leg movements while SEG and kinematic data were collected. This study proves the safety and feasibility of performing epidural spinal recordings from human subjects performing movement tasks.

Corrigendum: Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.

[This corrects the article DOI: 10.3389/fnhum.2021.644593.].

High-Frequency Impulse Therapy for Treatment of Chronic Back Pain: A Multicenter Randomized Controlled Pilot Study.

PURPOSE: This study aims to examine high-frequency impulse therapy (HFIT) impact on pain and function among patients undergoing care for chronic low back pain (CLBP). METHODS: A pilot randomized-controlled trial of HFIT system versus sham was conducted across 5 orthopedic and pain center sites in California, USA. Thirty-six patients seeking clinical care for CLBP were randomized. Primary outcome was function measured by the Six Minute Walk Test (6MWT). Secondary outcomes were function (Timed Up and Go [TUG] and Oswestry Disability Index [ODI]), pain (Numerical Rating Scale [NRS]), quality of life (Patient Global Impression of Change [PGIC]), and device use. Patients were assessed at baseline and every week for 4 weeks of follow-up. Mann-Whitney U-test was used to analyze changes in each outcome. Repeated measures ANOVA was used to assess the effect of treatment over time. RESULTS: The average age of subjects was 53.9 ± 15.7 (mean ± SD) years, with 12.1 ± 8.8 years of chronic low back pain. Patients who received an HFIT device had a significantly higher 6MWT score at weeks 2 [Cohen's d (95% CI): 0.33 (0.02, 0.61)], 3 [0.32 (0.01, 0.59)] and 4 [0.31 (0.01, 0.60)], respectively, as compared to their baseline scores (p < 0.05). Patients in the treatment group had significantly lower TUG scores at week 3 [0.30 (0.04, 0.57)] and significantly lower NRS scores at weeks 2 [0.34 (0.02, 0.58)] and 4 [0.41 (0.10, 0.67)] (p < 0.05). CONCLUSION: A larger-scale RCT can build on the findings of this study to test whether HFIT is effective in reducing pain and improving function in CLBP patients. This study shows encouraging evidence of functional improvement and reduction in pain in subjects who used HFIT. The efficacy and minimally invasive nature of HFIT is anticipated to substantially improve the management of CLBP patients.

Analysis-rcs-data: Open-Source Toolbox for the Ingestion, Time-Alignment, and Visualization of Sense and Stimulation Data From the Medtronic Summit RC+S System.

Closed-loop neurostimulation is a promising therapy being tested and clinically implemented in a growing number of neurological and psychiatric indications. This therapy is enabled by chronically implanted, bidirectional devices including the Medtronic Summit RC+S system. In order to successfully optimize therapy for patients implanted with these devices, analyses must be conducted offline on the recorded neural data, in order to inform optimal sense and stimulation parameters. The file format, volume, and complexity of raw data from these devices necessitate conversion, parsing, and time reconstruction ahead of time-frequency analyses and modeling common to standard neuroscientific analyses. Here, we provide an open-source toolbox written in Matlab which takes raw files from the Summit RC+S and transforms these data into a standardized format amenable to conventional analyses. Furthermore, we provide a plotting tool which can aid in the visualization of multiple data streams and sense, stimulation, and therapy settings. Finally, we describe an analysis module which replicates RC+S on-board power computations, a functionality which can accelerate biomarker discovery. This toolbox aims to accelerate the research and clinical advances made possible by longitudinal neural recordings and adaptive neurostimulation in people with neurological and psychiatric illnesses.

Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer's disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.

Musical Hallucinations in Chronic Pain: The Anterior Cingulate Cortex Regulates Internally Generated Percepts.

The anterior cingulate cortex (ACC) has been extensively implicated in the functional brain network underlying chronic pain. Electrical stimulation of the ACC has been proposed as a therapy for refractory chronic pain, although, mechanisms of therapeutic action are still unclear. As stimulation of the ACC has been reported to produce many different behavioral and perceptual responses, this region likely plays a varied role in sensory and emotional integration as well as modulating internally generated perceptual states. In this case series, we report the emergence of subjective musical hallucinations (MH) after electrical stimulation of the ACC in two patients with refractory chronic pain. In an N-of-1 analysis from one patient, we identified neural activity (local field potentials) that distinguish MH from both the non-MH condition and during a task involving music listening. Music hallucinations were associated with reduced alpha band activity and increased gamma band activity in the ACC. Listening to similar music was associated with different changes in ACC alpha and gamma power, extending prior results that internally generated perceptual phenomena are supported by circuits in the ACC. We discuss these findings in the context of phantom perceptual phenomena and posit a framework whereby chronic pain may be interpreted as a persistent internally generated percept.

The American Society of Pain and Neuroscience (ASPN) Practical Guidelines to Study Design and Scientific Manuscript Preparation in Neuromodulation.

BACKGROUND: Healthcare clinical and even policy decisions are progressively made based on research-based evidence. The process by which the appropriate trials are developed and well-written manuscripts by means of evidence-based medicine recommendations has resulted in unprecedented necessity in evidence-based medicine in neuromodulation. METHODS: The essential considerations in the planning of neuromodulation research are discussed in the light of available scientific literature as well as the authors' scientific expertise regarding research study design and scientific manuscript preparation. CONCLUSION: This article should enable the reader to understand how to appropriately design a clinical research study and prepare scientific manuscripts. The high-quality and well-designed studies, when performed and reported effectively, support evidence-based medicine and foster improved patient outcomes.

Practical Closed-Loop Strategies for Deep Brain Stimulation: Lessons From Chronic Pain.

Deep brain stimulation (DBS) is a plausible therapy for various neuropsychiatric disorders, though continuous tonic stimulation without regard to underlying physiology (open-loop) has had variable success. Recently available DBS devices can sense neural signals which, in turn, can be used to control stimulation in a closed-loop mode. Closed-loop DBS strategies may mitigate many drawbacks of open-loop stimulation and provide more personalized therapy. These devices contain many adjustable parameters that control how the closed-loop system operates, which need to be optimized using a combination of empirically and clinically informed decision making. We offer a practical guide for the implementation of a closed-loop DBS system, using examples from patients with chronic pain. Focusing on two research devices from Medtronic, the Activa PC+S and Summit RC+S, we provide pragmatic details on implementing closed- loop programming from a clinician's perspective. Specifically, by combining our understanding of chronic pain with data-driven heuristics, we describe how to tune key parameters to handle feature selection, state thresholding, and stimulation artifacts. Finally, we discuss logistical and practical considerations that clinicians must be aware of when programming closed-loop devices.

A Deep Brain Stimulation Trial Period for Treating Chronic Pain.

Early studies of deep brain stimulation (DBS) for various neurological disorders involved a temporary trial period where implanted electrodes were externalized, in which the electrical contacts exiting the patient's brain are connected to external stimulation equipment, so that stimulation efficacy could be determined before permanent implant. As the optimal brain target sites for various diseases (i.e., Parkinson's disease, essential tremor) became better established, such trial periods have fallen out of favor. However, deep brain stimulation trial periods are experiencing a modern resurgence for at least two reasons: (1) studies of newer indications such as depression or chronic pain aim to identify new targets and (2) a growing interest in adaptive DBS tools necessitates neurophysiological recordings, which are often done in the peri-surgical period. In this review, we consider the possible approaches, benefits, and risks of such inpatient trial periods with a specific focus on developing new DBS therapies for chronic pain.

A Comprehensive Practice Guideline for Magnetic Resonance Imaging Compatibility in Implanted Neuromodulation Devices.

OBJECTIVES: The evolution of neuromodulation devices in order to enter magnetic resonance imaging (MRI) scanners has been one of understanding limitations, engineering modifications, and the development of a consensus within the community in which the FDA could safely administer labeling for the devices. In the initial decades of neuromodulation, it has been contraindicated for MRI use with implanted devices. In this review, we take a comprehensive approach to address all the major products currently on the market in order to provide physicians with the ability to determine when an MRI can be performed for each type of device implant. MATERIALS AND METHODS: We have prepared a narrative review of MRI guidelines for currently marketed implanted neuromodulation devices including spinal cord stimulators, intrathecal drug delivery systems, peripheral nerve stimulators, deep brain stimulators, vagal nerve stimulators, and sacral nerve stimulators. Data sources included relevant literature identified through searches of PubMed, MEDLINE/OVID, SCOPUS, and manual searches of the bibliographies of known primary and review articles, as well as manufacturer-provided information. RESULTS: Guidelines and recommendations for each device and their respective guidelines for use in and around MR environments are presented. CONCLUSIONS: This is the first comprehensive guideline with regards to various devices in the market and MRI compatibility from the American Society of Pain and Neuroscience.

Transcranial Magnetic Stimulation for Pain, Headache, and Comorbid Depression: INS-NANS Expert Consensus Panel Review and Recommendation.

BACKGROUND: While transcranial magnetic stimulation (TMS) has been studied for the treatment of psychiatric disorders, emerging evidence supports its use for pain and headache by stimulating either motor cortex (M1) or dorsolateral prefrontal cortex (DLPFC). However, its clinical implementation is hindered due to a lack of consensus in the quality of clinical evidence and treatment recommendation/guideline(s). Thus, working collaboratively, this multinational multidisciplinary expert panel aims to: 1) assess and rate the existing outcome evidence of TMS in various pain/headache conditions; 2) provide TMS treatment recommendation/guidelines for the evaluated conditions and comorbid depression; and 3) assess the cost-effectiveness and technical issues relevant to the long-term clinical implementation of TMS for pain and headache. METHODS: Seven task groups were formed under the guidance of a 5-member steering committee with four task groups assessing the utilization of TMS in the treatment of Neuropathic Pain (NP), Acute Pain, Primary Headache Disorders, and Posttraumatic Brain Injury related Headaches (PTBI-HA), and remaining three assessing the treatment for both pain and comorbid depression, and the cost-effectiveness and technological issues relevant to the treatment. RESULTS: The panel rated the overall level of evidence and recommendability for clinical implementation of TMS as: 1) high and extremely/strongly for both NP and PTBI-HA respectively; 2) moderate for postoperative pain and migraine prevention, and recommendable for migraine prevention. While the use of TMS for treating both pain and depression in one setting is clinically and financially sound, more studies are required to fully assess the long-term benefit of the treatment for the two highly comorbid conditions, especially with neuronavigation. CONCLUSIONS: After extensive literature review, the panel provided recommendations and treatment guidelines for TMS in managing neuropathic pain and headaches. In addition, the panel also recommended more outcome and cost-effectiveness studies to assess the feasibility of the long-term clinical implementation of the treatment.

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain.

Pain is a subjective experience that alerts an individual to actual or potential tissue damage. Through mechanisms that are still unclear, normal physiological pain can lose its adaptive value and evolve into pathological chronic neuropathic pain. Chronic pain is a multifaceted experience that can be understood in terms of somatosensory, affective, and cognitive dimensions, each with associated symptoms and neural signals. While there have been many attempts to treat chronic pain, in this article we will argue that feedback-controlled 'closed-loop' deep brain stimulation (DBS) offers an urgent and promising route for treatment. Contemporary DBS trials for chronic pain use "open-loop" approaches in which tonic stimulation is delivered with fixed parameters to a single brain region. The impact of key variables such as the target brain region and the stimulation waveform is unclear, and long-term efficacy has mixed results. We hypothesize that chronic pain is due to abnormal synchronization between brain networks encoding the somatosensory, affective and cognitive dimensions of pain, and that multisite, closed-loop DBS provides an intuitive mechanism for disrupting that synchrony. By (1) identifying biomarkers of the subjective pain experience and (2) integrating these signals into a state-space representation of pain, we can create a predictive model of each patient's pain experience. Then, by establishing how stimulation in different brain regions influences individual neural signals, we can design real-time, closed-loop therapies tailored to each patient. While chronic pain is a complex disorder that has eluded modern therapies, rich historical data and state-of-the-art technology can now be used to develop a promising treatment.

Memory-guided learning: CA1 and CA3 neuronal ensembles differentially encode the commonalities and differences between situations.

Memory influences learning, but how neural signals support such transfer are unknown. To investigate these mechanisms, we trained rats to perform a standard spatial memory task in a plus maze and tested how training affected learning and neural coding in two new task variants. A switch task exchanged the start and goal locations in the same environment, whereas, an altered environment task contained unfamiliar local and distal cues. Learning was facilitated in both variants compared with the acquisition of the standard task. In the switch task, performance was largely maintained, and was accompanied by immediate and stable place-field remapping. Place-field maps in CA1 were anticorrelated in the standard and switch sessions, and the anticorrelation covaried with switch performance. Simultaneously, CA3 maps were uncorrelated overall in the standard and switch, though many CA3 cells had fields in shifted locations in the same maze arms. In the altered environment, performance was initially impaired, and place fields changed dynamically. CA1 fields were initially unstable, and their stabilization correlated with improving performance. Most CA3 cells, however, stopped firing on the maze in the altered environment, even as the same cells maintained prominent fields in standard sessions recorded before and after. CA1 and CA3 place fields thus revealed different coding dynamics that correlated with both learning and memory performance. Together, CA1 and CA3 ensembles represented the similarities and differences between new and familiar situations through concurrent rate and place remapping.