A mechanism for attenuating responses to anticipated sounds in the dorsal cochlear nucleus
Zhang, Q.; Muller, S. Z.; Abbott, L.; Sawtell, N. B.
Show abstract
The dorsal cochlear nucleus (DCN) is a cerebellum-like structure in the mammalian auditory brainstem that combines auditory nerve input with diverse auditory and non-auditory signals conveyed by granule cells. Granule cells form excitatory synapses onto inhibitory interneurons known as cartwheel cells, and in vitro studies have demonstrated an anti-Hebbian form of plasticity at these synapses. However, the function of cartwheel cells and their plastic granule cell input has remained unknown. Using in vivo electrophysiological recordings, optogenetics, and computational modeling, we provide evidence that intrinsic electrophysiological properties of cartwheel cells invert the expected effects of anti-Hebbian plasticity, generating a positive feedback loop that enhances cartwheel cell inhibition of DCN output neurons at the onset of anticipated sounds. This combined cellular and synaptic mechanism may implement a novel form of predictive processing that is robust to variability in the timing of anticipated sensory input.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- The superior colliculus gates dopamine responses to conditioned stimuli in visual classical conditioning 94%
- Prefrontal cortical ChAT-VIP interneurons provide local excitation by cholinergic synaptic transmission and control attention 94%
- Spectral cues are necessary to encode azimuthal auditory space in the mouse superior colliculus 94%
Similar papers in this journal
- The role of inhibitory neurons in novelty sound detection in regular and random statistical contexts. 97%
- Mechanisms of synaptic zinc plasticity at mouse dorsal cochlear nucleus glutamatergic synapses 96%
- Cortical and subcortical neurons discriminate sounds in noise on the sole basis of acoustic amplitude modulations 95%
"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.