Red LED photobiomodulation reduces pain hypersensitivity and improves sensorimotor function following mild T10 hemicontusion spinal cord injury

BACKGROUND The development of hypersensitivity following spinal cord injury can result in incurable persistent neuropathic pain. Our objective was to examine the effect of red light therapy on the development of hypersensitivity and sensorimotor function, as well as on microglia/macrophage subpopulations following spinal cord injury. METHODS Wistar rats were treated (or sham treated) daily for 30 min with an LED red (670 nm) light source (35 mW/cm2), transcutaneously applied to the dorsal surface, following a mild T10 hemicontusion injury (or sham injury). The development of hypersensitivity was assessed and sensorimotor function established using locomotor recovery and electrophysiology of dorsal column pathways. Immunohistochemistry and TUNEL were performed to examine cellular changes in the spinal cord. RESULTS We demonstrate that red light penetrates through the entire rat spinal cord and significantly reduces signs of hypersensitivity following a mild T10 hemicontusion spinal cord injury. This is accompanied with improved dorsal column pathway functional integrity and locomotor recovery. The functional improvements were preceded by a significant reduction of dying (TUNEL+) cells and activated microglia/macrophages (ED1+) in the spinal cord. The remaining activated microglia/macrophages were predominantly of the anti-inflammatory/wound-healing subpopulation (Arginase1+ED1+) which were expressed early, and up to sevenfold greater than that found in sham-treated animals. CONCLUSIONS These findings demonstrate that a simple yet inexpensive treatment regime of red light reduces the development of hypersensitivity along with sensorimotor improvements following spinal cord injury and may therefore offer new hope for a currently treatment-resistant pain condition.This study was funded by the Gretel and Gordon Bootes Medical Research Foundation

Dorsal Column Nuclei Neural Signal Features Permit Robust Machine-Learning of Natural Tactile- and Proprioception-Dominated Stimuli

Neural prostheses enable users to effect movement through a variety of actuators by translating brain signals into movement control signals. However, to achieve more natural limb movements from these devices, the restoration of somatosensory feedback is required. We used feature-learnability, a machine-learning approach, to assess signal features for their capacity to enhance decoding performance of neural signals evoked by natural tactile and proprioceptive somatosensory stimuli, recorded from the surface of the dorsal column nuclei (DCN) in urethane-anesthetized rats. The highest performing individual feature, spike amplitude, classified somatosensory DCN signals with 70% accuracy. The highest accuracy achieved was 87% using 13 features that were extracted from both high and low-frequency (LF) bands of DCN signals. In general, high-frequency (HF) features contained the most information about peripheral somatosensory events, but when features were acquired from short time-windows, classification accuracy was significantly improved by adding LF features to the feature set. We found that proprioception-dominated stimuli generalize across animals better than tactile-dominated stimuli, and we demonstrate how information that signal features contribute to neural decoding changes over the time-course of dynamic somatosensory events. These findings may inform the biomimetic design of artificial stimuli that can activate the DCN to substitute somatosensory feedback. Although, we investigated somatosensory structures, the feature set we investigated may also prove useful for decoding other (e.g., motor) neural signals.AL was supported by the Australian Government Research Training Program. We are extremely gratefully to the Bootes Medical Research Foundation for funding this project

Sex, but not skin tone affects penetration of red-light (660 nm) through sites susceptible to sports injury in lean live and cadaveric tissues

Red‐light treatment is emerging as a novel therapy for promoting tissue recovery but data on red‐light penetration through human tissues are lacking. We aimed to: (1) determine the effect of light irradiance, tissue thickness, skin tone, sex and bone/muscle content on 660 nm light penetration through common sites of sports injuries, and (2) establish if cadaver tissues serve as a useful model for predicting red‐light penetration in live tissues. Live and cadaver human tissues were exposed to 660 nm light at locations across the skull, spinal cord and upper and lower limbs. Red‐light was produced by a light emitting diode array of various irradiances (15‐500 mW/cm2) and measured by a light‐probe positioned on the tissue surface opposite to the light emitting diodes. 100 mW/cm2 successfully penetrated tissue 50 mm. These results assist clinicians and researchers in determining red‐light treatment intensities for penetrating human tissues.Bootes Medical Research Foundatio

Peripheral Nerve Activation Evokes Machine-Learnable Signals in the Dorsal Column Nuclei

The brainstem dorsal column nuclei (DCN) are essential to inform the brain of tactile and proprioceptive events experienced by the body. However, little is known about how ascending somatosensory information is represented in the DCN. Our objective was to investigate the usefulness of high-frequency (HF) and low-frequency (LF) DCN signal features (SFs) in predicting the nerve from which signals were evoked. We also aimed to explore the robustness of DCN SFs and map their relative information content across the brainstem surface. DCN surface potentials were recorded from urethane-anesthetized Wistar rats during sural and peroneal nerve electrical stimulation. Five salient SFs were extracted from each recording electrode of a seven-electrode array. We used a machine learning approach to quantify and rank information content contained within DCN surface-potential signals following peripheral nerve activation. Machine-learning of SF and electrode position combinations was quantified to determine a hierarchy of information importance for resolving the peripheral origin of nerve activation. A supervised back-propagation artificial neural network (ANN) could predict the nerve from which a response was evoked with up to 96.8 ± 0.8% accuracy. Guided by feature-learnability, we maintained high prediction accuracy after reducing ANN algorithm inputs from 35 (5 SFs from 7 electrodes) to 6 (4 SFs from one electrode and 2 SFs from a second electrode). When the number of input features were reduced, the best performing input combinations included HF and LF features. Feature-learnability also revealed that signals recorded from the same midline electrode can be accurately classified when evoked from bilateral nerve pairs, suggesting DCN surface activity asymmetry. Here we demonstrate a novel method for mapping the information content of signal patterns across the DCN surface and show that DCN SFs are robust across a population. Finally, we also show that the DCN is functionally asymmetrically organized, which challenges our current understanding of somatotopic symmetry across the midline at sub-cortical levels

Peripheral nerve activation evokes machine-learnable signals in the dorsal column nuclei

The brainstem dorsal column nuclei (DCN) are essential to inform the brain of tactile and proprioceptive events experienced by the body. However, little is known about how ascending somatosensory information is represented in the DCN. Our objective was to investigate the usefulness of high-frequency (HF) and low-frequency (LF) DCN signal features (SFs) in predicting the nerve from which signals were evoked. We also aimed to explore the robustness of DCN SFs and map their relative information content across the brainstem surface. DCN surface potentials were recorded from urethane-anesthetized Wistar rats during sural and peroneal nerve electrical stimulation. Five salient SFs were extracted from each recording electrode of a seven-electrode array. We used a machine learning approach to quantify and rank information content contained within DCN surface-potential signals following peripheral nerve activation. Machine-learning of SF and electrode position combinations was quantified to determine a hierarchy of information importance for resolving the peripheral origin of nerve activation. A supervised back-propagation artificial neural network (ANN) could predict the nerve from which a response was evoked with up to 96.8 ± 0.8% accuracy. Guided by feature-learnability, we maintained high prediction accuracy after reducing ANN algorithm inputs from 35 (5 SFs from 7 electrodes) to 6 (4 SFs from one electrode and 2 SFs from a second electrode). When the number of input features were reduced, the best performing input combinations included HF and LF features. Feature-learnability also revealed that signals recorded from the same midline electrode can be accurately classified when evoked from bilateral nerve pairs, suggesting DCN surface activity asymmetry. Here we demonstrate a novel method for mapping the information content of signal patterns across the DCN surface and show that DCN SFs are robust across a population. Finally, we also show that the DCN is functionally asymmetrically organized, which challenges our current understanding of somatotopic symmetry across the midline at sub-cortical levels.The authors are extremely grateful to the Bootes Medical Research Foundation which funded this project. AL was supported by the Australian Government Research Training Program

Waveform Similarity Analysis: in vivo data and simulation - PLoS

<p>This zip file contains MATLAB code, compound nerve and muscle data from rat sciatic/sural nerves and a simulation experiment to accompany our manuscript: "Waveform Similarity Analysis: A simple template comparing approach for detecting and quantifying noisy evoked compound action potentials"</p

Evidence that venoconstriction reverses the phase II sympathoinhibitory and brdaycardic response to haemorrhage

Severe hypotensive haemorrhage results in a biphasic response, characterized by an initial increase in heart rate and sympathetic vasomotor activity (phase I) followed by a life-threatening hypotension, accompanied by profound sympathoinhibition and bradycardia (phase II). The phase II response is believed to be dependent on inputs from cardiopulmonary receptors, and may be triggered by the reduction in venous return and cardiac filling associated with severe haemorrhage. In this study, we tested the hypothesis that the phase II response could be reversed by venoconstriction, which is known to enhance venous return and cardiac filling, by comparing the effects of phenylephrine (which constricts veins as well as arterioles) with that of vasopressin (which constricts arterioles but not veins). In sodium pentobarbitone-anaesthetised rats, haemorrhage evoked an initial increase in heart rate (HR) and renal sympathetic activity (RSNA) followed by a large decrease in both variables to levels below the pre-haemorrhage baseline levels (phase II response). During the phase II response, an intravenous injection of phenylephrine, sufficient to restore mean arterial pressure to the pre-haemorrhage level, resulted in a gradually developing increase (over 3-4 min) in HR and RSNA back to the baseline levels. In contrast, intravenous injection of an equipressor dose of vasopressin did not result in any increase in RSNA and only a transient increase in HR. Injection of phenylephrine, but not vasopressin, also increased the pulsatile component of central venous pressure, indicative of reduced venous capacitance. The findings indicate that venoconstriction reverses the phase II sympathoinhibition and bradycardia

Red-Light (670 nm) Therapy Reduces Mechanical Sensitivity and Neuronal Cell Death, and Alters Glial Responses after Spinal Cord Injury in Rats

Individuals with spinal cord injury (SCI) often develop debilitating neuropathic pain, which may be driven by neuronal damage and neuroinflammation. We have previously demonstrated that treatment using 670 nm (red) light irradiation alters microglia/macrophage responses and alleviates mechanical hypersensitivity at 7 days post-injury (dpi). Here, we investigated the effect of red light on the development of mechanical hypersensitivity, neuronal markers, and glial response in the subacute stage (days 1-7) following SCI. Wistar rats were subjected to a mild hemi-contusion SCI at vertebra T10 or to sham surgery followed by daily red-light treatment (30 min/day; 670 nm LED; 35 mW/cm2) or sham treatment. Mechanical sensitivity of the rat dorsum was assessed from 1 dpi and repeated every second day. Spinal cords were collected at 1, 3, 5, and 7 dpi for analysis of myelination, neurofilament protein NF200 expression, neuronal cell death, reactive astrocytes (glial fibrillary acidic protein [GFAP]+ cells), interleukin 1 β (IL-1β) expression, and inducible nitric oxide synthase (iNOS) production in IBA1+ microglia/macrophages. Red-light treatment significantly reduced the cumulative mechanical sensitivity and the hypersensitivity incidence following SCI. This effect was accompanied by significantly reduced neuronal cell death, reduced astrocyte activation, and reduced iNOS expression in IBA1+ cells at the level of the injury. However, myelin and NF200 immunoreactivity and IL-1β expression in GFAP+ and IBA1+ cells were not altered by red-light treatment. Thus, red-light therapy may represent a useful non-pharmacological approach for treating pain during the subacute period after SCI by decreasing neuronal loss and modulating the inflammatory glial response.The authors gratefully acknowledge the Bootes Medical Research Foundation for funding this project

Sympathoinhibitory pathway from caudal midline medulla to RVLM is independent of baroreceptor reflex pathway

Glutamate stimulation of the caudal midline medulla (CMM) causes profound sympathoinhibition due to GABAergic inhibition of presympathetic neurons in the rostral ventrolateral medulla (RVLM). We investigated whether the sympatho-inhibitory pathway from CMM to RVLM, like the central baroreceptor reflex pathway, includes a glutamatergic synapse in the caudal ventrolateral medulla (CVLM). In pentobarbital sodium-anesthetized rats, the RVLM on one side was inhibited by a muscimol microinjection. Then the response evoked by glutamate microinjections into the CMM or by baroreceptor stimulation was determined before and after 1) microinjection of the GABA receptor antagonist bicuculline into the RVLM on the other side or 2) microinjections of the glutamate receptor antagonist kynurenate bilaterally into the CVLM. Bicuculline in the RVLM greatly reduced both CMM- and baroreceptor-evoked sympathoinhibition. Compared with the effect of vehicle solution, kynurenate in the CVLM greatly reduced baroreceptor-evoked sympathoinhibition, whereas its effect on CMM-evoked sympathoinhibition was not different from that of the vehicle solution. These findings indicate that the output pathway from CMM sympathoinhibitory neurons, unlike the baroreceptor and other reflex sympathoinhibitory pathways, does not include a glutamatergic synapse in the CVLM