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Spinal cord stimulation (SCS) is an effective treatment for chronic pain, but SCS efficacy has not significantly improved over time, in part because the mechanisms of action remain unclear. Most preclinical studies investigating pain and SCS mechanisms have focused on the responses of deep dorsal horn (DDH) neurons, but neural networks in the superficial dorsal horn (SDH) are also important for processing nociceptive information. This work synthesizes heterogeneous experimental recordings from the SDH into a computational model that replicates experimental responses and that can be used to quantify neuronal responses to SCS under neuropathic pain conditions. <\/jats:p>","DOI":"10.1152\/jn.00186.2023","type":"journal-article","created":{"date-parts":[[2023,9,20]],"date-time":"2023-09-20T08:00:33Z","timestamp":1695196833000},"page":"1103-1117","update-policy":"https:\/\/doi.org\/10.1152\/aps-crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Network model of nociceptive processing in the superficial spinal dorsal horn reveals mechanisms of hyperalgesia, allodynia, and spinal cord stimulation"],"prefix":"10.1152","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8995-2785","authenticated-orcid":false,"given":"John E.","family":"Gilbert","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Duke University, Durham, North Carolina, United 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