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A cerebellum-like circuit in the auditory system cancels responses to self-generated sounds

Abstract

The dorsal cochlear nucleus (DCN) integrates auditory nerve input with a diverse array of sensory and motor signals processed in circuitry similar to that of 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.

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Figure 1: Self-generated sounds strongly affect VCN but not DCN neurons.
Figure 2: Responses to self-generated versus external sounds in VCN and DCN.
Figure 3: DCN responses to acoustic stimuli are not suppressed during licking.
Figure 4: Non-auditory responses related to licking in DCN complex-spiking units.
Figure 5: A role for the spinal trigeminal nucleus in cancelling self-generated sounds in DCN.
Figure 6: Adaptive cancellation of sounds correlated with behavior in DCN.

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Acknowledgements

We thank L. Abbott, C. Bell and T. Jessell for comments on the manuscript. This work was supported by grants from the NIH (DC015449), the Alfred P. Sloan Foundation, the McKnight Endowment Fund for Neuroscience and the Irma T. Hirschl Trust to N.B.S. and an NIH grant (F30DC014174) to S.S.

Author information

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Authors

Contributions

S.S. and R.W. performed the experiments and analyzed the data. C.D. designed and performed the analysis. A.G.E. contributed custom software and hardware. N.B.S. and S.S. designed the study and wrote the manuscript.

Corresponding author

Correspondence to Nathaniel B Sawtell.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Cerebellum-like circuitry of DCN.

Fusiform cells integrate direct auditory nerve fiber input (orange) with a diverse array of auditory and non-auditory inputs conveyed by a mossy fiber-granule cell-parallel fiber system (blue) similar to that found in the cerebellum and cerebellum-like structures associated with electrosensory processing in fish. Cartwheel cells (green) also receive parallel fiber input but lack direct input from the auditory nerve. Cartwheel cells inhibit fusiform cells. Our hypothesis regarding DCN function is that mossy fibers convey information related to the animal’s own movements and behavior, which serves to cancel out responses to self-generated acoustic stimuli. Such cancellation could be achieved by anti-Hebbian plasticity at parallel fiber synapses onto fusiform and/or cartwheel cells, as has been shown for cerebellum-like sensory structures in fish. For clarity, some DCN cell types and inputs have been omitted.

Supplementary Figure 2 Characteristics of self-generated licking sounds in head-fixed mice.

(a) Video stills from a representative mouse. Top, still of the mouse at rest. Bottom, zoomed in stills of the dash white box at different points during the lick cycle: i. jaw opening, ii. tongue protrusion and lick spout contact, iii-iv. tongue retraction, v. jaw closure. (b) The average spectrogram of licking sounds across mice (n = 20) triggered on tongue contact with the lick spout. White circles show the time-frequency peaks of the spectrograms of each individual mouse. Red crosses show time-frequency peaks of the average spectrogram. Dotted white line indicates time of tongue contact with the spout. Solid white line indicates the average RMS across mice. Roman numerals indicate the timing of the video stills shown in a. (c) Four examples of lick-triggered spectrograms from individual mice. White crosses show time-frequency peaks. Dotted line shows time of tongue contact with spout. (d) Histogram of the timing of the largest RMS peak of the licking sound with respect to onset of tongue contact with the lick spout. (e) Histogram of the timing of the largest RMS peak of the licking sound with respect to offset of tongue contact with the lick spout. (f) Histogram of the frequencies at which peaks in the lick-triggered spectrogram occur, showing that the lick-triggered sound consists of three distinct spectral peaks (dotted lines).

Supplementary Figure 3 Identification and verification of recording sites in VCN and DCN.

(a) Rectified extracellular multiunit activity (each row is the average of 15 presentations) recorded on an electrode penetration through the auditory brainstem in response to 100 ms tones ranging in frequency from 5-50 kHz (gray rectangles). As the electrode passes through DCN the frequency evoking the largest multiunit response smoothly decreases. DCN units were isolated in DCN at depths between 100 μm and 300 μm. A sudden increase in frequency (occurring between depths of 400 μm and 600 μm) indicated entrance into VCN. VCN units were isolated at depths between 800 μm and 1000 μm. (b) Histological verification of recording sites in the same animal as the multiunit recordings shown in a. Dextran-conjugated Alexa 594 (green) was iontophoretically injected at depths of 100 μm and 800 μm. Scale bar = 200 μm. (c) Iontophoretic injections of dextran-conjugated Alexa 594 at recording sites (arrows) in DCN (top) and VCN (bottom) in 3 additional animals. Scale bars = 200 μm.

Supplementary Figure 4 Baseline firing and sound-evoked responses in DCN units.

(a) Histogram of spontaneous firing rates of all units recorded in DCN (n = 73), excluding complex-spiking units. The average spontaneous rate was 48.3 ± 28.2 Hz (mean and s.d.). No DCN units met previously established criteria for type II or type I/III responses, i.e. a spontaneous rate less than 2.5 Hz (arrow). Type II and I/III responses are associated with a major class of DCN interneuron known as vertical cells. (b) Histogram of responses to sound stimuli in DCN units (n = 60), excluding units with complex spikes. Stimuli included the mimic of the licking sound (12 dB SPL), 5-15 kHz bandpassed noise (15 dB SPL), and broadband noise used in pairing experiments recorded with a silicon probe. Average maximum noise response was 50.6 ± 26.3 Hz (mean and s.d.). No units showed inhibitory sound responses, a criterion for type III-i response cell types.

Supplementary Figure 5 Silicon probe recordings in the DCN.

Representative 16-channel silicon probe recordings from the mouse dorsal cochlear nucleus. Electrode sites were arranged in a vertical linear array with individual sites separated by 25 μm. Tracks were made until a well-isolated unit emerged on a single electrode site. (a) A single unit with clear responses to 25 kHz and broadband noise (bottom trace). (b) A recording from the dorsal cochlear nucleus in another mouse showing multiunit responses to 35 kHz, 40 kHz, and broadband noise across multiple sites. A well-isolated single unit appears on the fourth most ventral site and has clear responses to 30 kHz (bottom trace), 35 kHz, and broadband noise.

Supplementary Figure 6 Pairing-induced reductions in DCN responses to correlated sounds are not related to variability in behavior or neural responses.

(a) Changes in licking behavior cannot explain pairing induced reductions in DCN responses. Lick rates at the start (first 150 licks) and end (last 150 licks) of the pairing experiments shown in Fig. 6. There was no difference in early versus late lick rates in DCN correlated (n = 20, P = 0.9, Wilcoxon Signed Rank Test), uncorrelated (n = 11, P = 0.9, Wilcoxon Signed Rank Test), or VCN correlated conditions (n = 7, P = 0.56, Wilcoxon Signed Rank Test). There also was no difference in lick rates between the three groups (P = 0.08, Kruskal Wallis test). (b-h) To examine possible sources of the variance in cancellation amongst DCN units in which acoustic stimuli were paired with licking, we also performed a multilinear regression with the variables shown in the figure as regressors. (b) The slope of the change during the pairing period (if any) in the lick rate did not correlate with decay rate during pairing (n = 20, P = 0.81). (c) The variability of licking, defined as the standard deviation of the interlick intervals between the twenty most recent licks, did not correlate with the decay rate during pairing (n = 20, P = 0.29). (d) The mean lick rate did not correlate with the decay rate during pairing (n = 20, P = 0.86). (e) Initial magnitude of DCN unit responses to the correlated sound did not correlate with the decay rate during pairing (n = 20, P = 0.19). (f) Mean baseline firing rate calculated for the entire recording did not correlate with decay rate during pairing (n = 20, P = 0.17). (g) The slope of the change (if any) in a unit’s baseline firing rate, defined as the mean firing rate in periods at least 20 ms before the next lick and 150 ms after the previous lick, did not correlate with decay during pairing (n = 20, P = 0.98). (h) Magnitude of a unit’s response to licking alone before pairing did not correlate with the decay rate during pairing (n = 10, P = 0.73).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 (PDF 1127 kb)

Supplementary Methods Checklist (PDF 435 kb)

Sounds generated by licking behavior in a head-fixed mouse.

Left, Video of a head-fixed mouse licking a metal spout for water. The lick spout is the small metal tube with a spherical end in the bottom left of the frame. Video was recorded at 300 fps and played back at 30 fps and thus is slowed by a factor of ten. Right, r.m.s. amplitude of microphone recording; dashed line represents the time of the current frame. The microphone is the black object with metallic tip located just above the lick spout. By pausing the video, it is possible to see the relationship between RMS amplitude of the microphone recording and different phases of the licking behavior. (MP4 6538 kb)

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Singla, S., Dempsey, C., Warren, R. et al. A cerebellum-like circuit in the auditory system cancels responses to self-generated sounds. Nat Neurosci 20, 943–950 (2017). https://doi.org/10.1038/nn.4567

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