Ninety-Hz Spinal Cord Stimulation-Induced Analgesia Is Dependent on Active Charge Balance and Is Nonlinearly Related to Amplitude: A Sham-Controlled Behavioral Study in a Rodent Model of Chronic Neuropathic Pain.

Background: Ninety-Hz active-recharge spinal cord stimulation (SCS) applied at below sensory-threshold intensity, as used with fast-acting subperception therapy spinal cord stimulation, has been shown clinically to produce significant analgesia, but additional characterization is required to better understand the therapy. This preclinical study investigates the behavioral effect of multiple 90-Hz SCS variants in a rodent model of neuropathic pain, focusing on charge balance and the relationship between 90-Hz efficacy and stimulation intensity.

Materials And Methods: Rats (n = 24) received a unilateral partial sciatic nerve ligation to induce neuropathic pain and were implanted with a quadripolar lead at T13.

A systematic review on descending serotonergic projections and modulation of spinal nociception in chronic neuropathic pain and after spinal cord stimulation.

Chronic neuropathic pain is a debilitating ordeal for patients worldwide and pharmacological treatment efficacy is still limited. As many pharmacological interventions for neuropathic pain often fail, insights into the underlying mechanism and role of identified receptors is of utmost importance. An important target for improving treatment of neuropathic pain is the descending serotonergic system as these projections modulate nociceptive signaling in the dorsal horn.

Time-dynamic pulse modulation of spinal cord stimulation reduces mechanical hypersensitivity and spontaneous pain in rats.

Enhancing the efficacy of spinal cord stimulation (SCS) is needed to alleviate the burden of chronic pain and dependence on opioids. Present SCS therapies are characterized by the delivery of constant stimulation in the form of trains of tonic pulses (TPs). We tested the hypothesis that modulated SCS using novel time-dynamic pulses (TDPs) leads to improved analgesia and compared the effects of SCS using conventional TPs and a collection of TDPs in a rat model of neuropathic pain according to a longitudinal, double-blind, and crossover design.

Mechanisms and mode of action of spinal cord stimulation in chronic neuropathic pain.

Tonic spinal cord stimulation (SCS) has been used as a treatment for chronic neuropathic pain ever since its discovery in late 1960s. Despite its clinical successes in a subset of chronic neuropathic pain syndromes, several limitations such as insufficient pain relief and uncomfortable paresthesias have led to the development of new targets, the dorsal root ganglion, and new stimulation waveforms, such as burst and high frequency. The aim of this review is to provide a brief overview of the main mechanisms behind the mode of action of the different SCS paradigms.

Mechanism of dorsal root ganglion stimulation for pain relief in painful diabetic polyneuropathy is not dependent on GABA release in the dorsal horn of the spinal cord.

Aims: It is hypothesized that dorsal root ganglion stimulation (DRGS), sharing some of the mechanisms of traditional spinal cord stimulation (SCS) of the dorsal columns, induces γ-aminobutyric acid (GABA) release from interneurons in the spinal dorsal horn.

Methods: We used quantitative immunohistochemical analysis in order to investigate the effect of DRGS on intensity of intracellular GABA-staining levels in the L4-L6 spinal dorsal horn of painful diabetic polyneuropathy (PDPN) animals. To establish the maximal pain relieving effect, we tested for mechanical hypersensitivity to von Frey filaments and animals received 30 minutes of DRGS at day 3 after implantation of the electrode.

Automated detection of electroencephalography artifacts in human, rodent and canine subjects using machine learning.

Background: Electroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation.

New Method: We have developed a quantitative and automated support vector machine (SVM)-based algorithm to accurately classify artifactual EEG epochs in awake rodent, canine and humans subjects.