Mimicking opioid analgesia in cortical pain circuits
Abstract
The anterior cingulate cortex is a key brain region involved in the affective and motivational dimensions of pain, but how opioid analgesics modulate this cortical circuit remains unclear1. Uncovering how opioids alter nociceptive neural dynamics to produce pain relief is essential for developing safer and more targeted treatments for chronic pain. Here we show that a population of cingulate neurons encodes spontaneous pain-related behaviours and is selectively modulated by morphine. Using deep learning behavioural analyses combined with longitudinal neural recordings in mice, we identified a persistent shift in cortical activity patterns following nerve injury that reflects the emergence of an unpleasant, affective chronic pain state. Morphine reversed these neuropathic neural dynamics and reduced affective–motivational behaviours without altering sensory detection or reflexive responses, mirroring how opioids alleviate pain unpleasantness in humans. Leveraging these findings, we built a biologically inspired chemogenetic gene therapy that targets opioid-sensitive neurons in the cingulate using a synthetic μ-opioid receptor promoter to drive inhibition2. This opioid-mimetic chemogenetic gene therapy recapitulated the analgesic effects of morphine during chronic neuropathic pain, thereby offering a new strategy for precision pain management that targets a key nociceptive cortical opioid circuit with safe, on-demand analgesia. The anterior cingulate cortex encodes affective pain behaviours modulated by opioids; targeting opioid-sensitive neurons through a new chemogenetic gene therapy replicates the analgesic effects of morphine, providing precise chronic pain relief without affecting sensory detection.
Fields of Study & Subjects
Pain Mechanisms and Treatments
Receptor Mechanisms and Signaling
Neurotransmitter Receptor Influence on Behavior
Publication details
- Journal / source
- Nature
- Publisher
- Springer Science and Business Media LLC
- Volume
- 649
- Issue
- 8098
- Pages
- 938–947
- Publication date
- 7 January 2026
- Language
- EN