Neural signaling in neuropathic pain: A computational modeling perspective

Abstract

Neuropathic pain is a complex condition with a huge unmet medical need. Owing to our incomplete understanding of its perplexing pathology, current therapeutic strategies for treating neuropathic pain remain limited in their efficacy. Computational modeling has emerged as a promising methodology in unraveling the intricate neural mechanisms contributing to neuropathic pain. This review serves as a bridge that links traditional experimental research in neuropathic pain to computational neuroscience. We aim to fill in the gap of knowledge between these two fields by introducing the methodology of computational modeling as well as the neurophysiological background for neuropathic pain. We provide examples of recent advances in using computational modeling at the molecular, cellular, and neural network levels to harness the understanding of pain-associated neural signaling. This integration of computational modeling has yielded crucial insights into neuropathic pain pathophysiology, with great potential to inform novel pharmacological and neurostimulation-based treatments for the disease.