The dorsal cochlear nucleus (DCN) integrates auditory nerve input with a
diverse array of sensory and motor signals processed within circuity similar to
the cerebellum. Yet how the DCN contributes to early auditory processing has
been a longstanding puzzle. Using electrophysiological recordings in mice during
licking behavior we show that DCN neurons are largely unaffected by
self-generated sounds while remaining sensitive to external acoustic stimuli.
Recordings in deafened mice, together with neural activity manipulations,
indicate that self-generated sounds are cancelled by non-auditory signals
conveyed by mossy fibers. In addition, DCN neurons exhibit gradual reductions in
their responses to acoustic stimuli that are temporally correlated with licking.
Together, these findings suggest that DCN may act as an adaptive filter for
cancelling self-generated sounds. Adaptive filtering has been established
previously for cerebellum-like sensory structures in fish suggesting a conserved
function for such structures across vertebrates.
Effective presentation of antigens by HLA class I molecules to CD8+ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multi-omic technology to generate the first unified ex vivo characterization of the CD8+ T cell response to SARS-CoV-2 across 4 major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCR a/b sequence diversity, and the utilization of pre-existing SARS-CoV-2 reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations influence pre-existing immunity to SARS-CoV-2 and shape the immune repertoire upon subsequent viral exposure.
In this issue of Neuron, Suvrathan et al. (2016) provide a striking demonstration of a plasticity rule with temporal properties precisely matched to the computational requirements of behavioral learning and suggest major revisions to the rules for synaptic plasticity in the cerebellum.
Appropriate generalization of learned responses to new situations is vital for adaptive behavior. We provide a circuit-level account of generalization in the electrosensory lobe (ELL) of weakly electric mormyrid fish. Much is already known in this system about a form of learning in which motor corollary discharge signals cancel responses to the uninformative input evoked by the fish’s own electric pulses. However, for this cancellation to be useful under natural circumstances, it must generalize accurately across behavioral regimes, specifically different electric pulse rates. We show that such generalization indeed occurs in ELL neurons, and develop a circuit-level model explaining how this may be achieved. The mechanism involves regularized synaptic plasticity and an approximate matching of the temporal dynamics of motor corollary discharge and electrosensory inputs. Recordings of motor corollary discharge signals in mossy fibers and granule cells provide direct evidence for such matching.
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