Journal of neurophysiology
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Spinal cord stimulation (SCS) is used clinically to limit chronic pain, but fundamental questions remain on the identity of axonal populations recruited. We developed an ex vivo adult mouse spinal cord preparation to assess recruitment following delivery of clinically analogous stimuli determined by downscaling a finite element model of clinical SCS. Analogous electric field distributions were generated with 300-µm × 300-µm electrodes positioned 200 µm above the dorsal column (DC) with stimulation between 50 and 200 µA. ⋯ To identify axonal populations recruited, finite element modeling identified scaling parameters to deliver clinically analogous SCS in an ex vivo adult mouse spinal cord preparation. Results showed that SCS first recruited an axonal population in the dorsal column at a threshold severalfold lower than primary afferents. These putative postsynaptic dorsal column tract cells may represent a previously unconsidered population responsible for SCS-induced paresthesias necessary for analgesia.
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Heightened pain sensitivity, the amount of pain experienced in response to a noxious event, is a known risk factor for development of chronic pain. We have previously reported that pain-free, sensorimotor peak alpha frequency (PAF) is a reliable biomarker of pain sensitivity for thermal, prolonged pains lasting tens of minutes. To test whether PAF can provide information about pain sensitivity occurring over clinically relevant timescales (i.e., weeks), EEG was recorded before and while participants experienced a long-lasting pain model, repeated intramuscular injection of nerve growth factor (NGF), that produces progressively developing muscle pain for up to 21 days. ⋯ NEW & NOTEWORTHY Pain sensitivity, the intensity of pain experienced after injury, has been identified as an important risk factor in the development of chronic pain. Biomarkers of pain sensitivity have the potential to ease chronic pain burdens by preventing disease emergence. In the current study, we demonstrate that the speed of pain-free, sensorimotor peak alpha frequency recorded during resting-state EEG predicts pain sensitivity to a clinically-relevant, human model of prolonged pain that persists for weeks.