Back

Striatal Mu-Opioid Receptor Activation Triggers Direct-Pathway GABAergic Plasticity to Induce Negative Affect

Wang, W.; Xie, X.; Zhuang, X.; Huang, Y.; Tan, T.; Gangal, H.; Huang, Z.; Purvines, W.; Wang, X.; Stefanov, A.; Chen, R.; Yu, E.; Hook, M.; Huang, Y.; Darcq, E.; Wang, J.

2022-05-25 neuroscience
10.1101/2022.05.23.493082 bioRxiv
Show abstract

Withdrawal from chronic opioid use often causes hypodopaminergic states and negative affect, which drives relapse. Direct-pathway medium spiny neurons (dMSNs) in the striatal patch compartment contain high levels of {micro}-opioid receptors (MORs). It remains unclear how chronic opioid exposure affects these MOR-expressing dMSNs and their striatopallidal and striatonigral outputs to induce negative emotions and relapse. Here, we report that MOR activation acutely suppressed GABAergic striatopallidal transmission in habenula-projecting globus pallidus neurons. Notably, repeated administrations of a MOR agonist (morphine or fentanyl) potentiated this GABAergic transmission. We also discovered that intravenous self-administration of fentanyl enhanced GABAergic striatonigral transmission and reduced the firing activity of midbrain dopaminergic neurons. Importantly, fentanyl withdrawal caused depression-like behaviors and promoted the reinstatement of fentanyl-seeking behaviors. These data suggest that chronic opioid use triggers GABAergic striatopallidal and striatonigral plasticity to induce a hypodopaminergic state, promoting negative emotions and leading to relapse. HighlightsO_LIRepeated administration of morphine potentiates IPSCdMSN{lozenge}GPh neurotransmission. C_LIO_LIRepeated administration of fentanyl potentiates IPSCdMSN{lozenge}SNc neurotransmission. C_LIO_LIFentanyl withdrawal induces negative emotional states, which drive relapse. C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.