Back

GABAB Receptors Gate Sex-Specific Synaptic Plasticity in the Nucleus Accumbens

LeGates, T. A.; Copenhaver, A. E.

2026-09-01 neuroscience
10.64898/2026.08.26.747391 bioRxiv
Show abstract

Excitatory synaptic plasticity within the nucleus accumbens (NAc) drives motivated behaviors, and dysregulation is implicated in several psychiatric disorders marked by impaired reward processing. The NAc integrates glutamatergic input, which conveys information about reward, context, and behavioral goals, with local GABAergic signaling that regulates excitatory transmission and medium spiny neuron (MSNs) output. However, little is known regarding GABA-dependent modulation of activity-dependent excitatory synaptic plasticity. Here, we investigated GABAB receptor (GABABR) regulation of plasticity at hippocampus (Hipp)-NAc synapses, at which plasticity is a key mediator of reward-related behaviors. Using whole-cell electrophysiological recordings in mouse brain slices, we found that pharmacological inhibition of GABABRs converts long-term potentiation (LTP) into long-term depression (LTD) selectively in females, identifying a sex-specific role for GABABRs in modulating long-term plasticity of Hipp-MSN synapses. This LTD required mGluR5 activation and estrogen receptor alpha (ER) in both D1- and D2-expressing MSN subtypes, while only D1-MSNs suggested that LTD was expressed presynaptically through a CB1 receptor-dependent mechanism. Notably, GABABR inhibition did not alter basal synaptic transmission, indicating a specific role for these receptors in gating plasticity beyond regulation of basal excitatory drive. Together, these findings identify a novel, sex-specific mechanism by which GABABRs control the direction of synaptic plasticity.

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.