Increased reliance on temporal coding when target sound is softer than the background

Abstract Everyday environments often contain multiple concurrent sound sources that fluctuate over time. Normally hearing listeners can benefit from high signal-to-noise ratios (SNRs) in energetic dips of temporally fluctuating background sound, a phenomenon called dip-listening. Specialized mechanisms of dip-listening exist across the entire auditory pathway. Both the instantaneous fluctuating and the long-term overall SNR shape dip-listening. An unresolved issue regarding cortical mechanisms of dip-listening is how target perception remains invariant to overall SNR, specifically, across different tone levels with an ongoing fluctuating masker. Equivalent target detection over both positive and negative overall SNRs (SNR invariance) is reliably achieved in highly-trained listeners. Dip-listening is correlated with the ability to resolve temporal fine structure, which involves temporally-varying spike patterns. Thus the current work tests the hypothesis that at negative SNRs, neuronal readout mechanisms need to increasingly rely on decoding strategies based on temporal spike patterns, as opposed to spike count. Recordings from chronically implanted electrode arrays in core auditory cortex of trained and awake Mongolian gerbils that are engaged in a tone detection task in 10 Hz amplitude-modulated background sound reveal that rate-based decoding is not SNR-invariant, whereas temporal coding is informative at both negative and positive SNRs

Diminished behavioral and neural sensitivity to sound modulation is associated with moderate developmental hearing loss.

The acoustic rearing environment can alter central auditory coding properties, yet altered neural coding is seldom linked with specific deficits to adult perceptual skills. To test whether developmental hearing loss resulted in comparable changes to perception and sensory coding, we examined behavioral and neural detection thresholds for sinusoidally amplitude modulated (sAM) stimuli. Behavioral sAM detection thresholds for slow (5 Hz) modulations were significantly worse for animals reared with bilateral conductive hearing loss (CHL), as compared to controls. This difference could not be attributed to hearing thresholds, proficiency at the task, or proxies for attention. Detection thresholds across the groups did not differ for fast (100 Hz) modulations, a result paralleling that seen in humans. Neural responses to sAM stimuli were recorded in single auditory cortex neurons from separate groups of awake animals. Neurometric analyses indicated equivalent thresholds for the most sensitive neurons, but a significantly poorer detection threshold for slow modulations across the population of CHL neurons as compared to controls. The magnitude of the neural deficit matched that of the behavioral differences, suggesting that a reduction of sensory information can account for limitations to perceptual skills

Differences in 5 Hz sAM detection thresholds are not attributable to measures of training or attention.

<p>(A) Higher sAM detection thresholds in CHLs were not due to better training, as CHLs reached slightly better compentence during training than CTRs, and criterion performance for detection of a fully-modulated sAM did not correlate with sAM detection thresholds for either group. (B) Proficiency with the task during initial testing, measured by d′ levels for fully-modulated sAM, did not explain differences in sAM detection threshold. (C) False alarm rates, a measure of attention, were not different across groups. (D) The number of trials per session, a measure of motivation, also did not explain differences in sAM detection threshold. <i>Black</i>  =  CTR; <i>Orange</i>  =  CHL.</p

Limited effects of CHL on cortical responses to static tones.

<p>Cells were analyzed irrespective of responses to sAM, thus include a range of BMFs. (A) Cells were sampled across an equivalent frequency range, indicated by similar distributions of BF across groups. Rate-level functions were taken at each neuron’s BF. There were no group differences in (B) dynamic range, (C) the proportion of monotonic versus non-monotonic cells, or (D) the first-spike latencies when cells were driven most strongly, measured at the RLF peak. (E) As expected in the CHL animals, the level threshold across cells was higher than in CTRs. Group differences emerged based on firing rate: both (F) the firing rate at RLF threshold and (G) the maximal firing rate of the RLF were lower in CHL animals. <i>Black</i>  =  CTR; <i>Orange</i>  =  CHL. ***  =  p<.001; (*)  =  p = .05.</p

CHL alters cortical responses to sAM.

<p>(A) Modulation transfer functions (measuring responses across modulation frequency) differed across CTRs and CHLs for response measures that include strength of firing: firing rate (middle) and power at the stimulus MF (bottom). They did not differ for the response measure of synchrony: vector strength (<i>top</i>). Unlike at slow MFs, at 100 Hz sAM the response measures overlapped across the groups. (B) Population period histograms for those cells with a BMF of 5 Hz. Histograms were normalized for number of cells in each group, and are shown for several sAM modulation depths. The envelope shape of the sAM is increasingly apparent in the histograms at larger depths, for both groups. Qualitatively, in the CTR population a visible envelope shape emerges at a lower depth (10%), and the magnitude of the envelope is larger at higher depths. (C) Neural responses over the range of depths where behavioral thresholds differ were stronger for CTRs when measured by power (<i>bottom</i>), the measure that best reflects envelope shape. <i>Black</i>  =  CTR; <i>Orange</i>  =  CHL. ***  =  p<.001; *  =  p≤.05.</p

Developmental CHL increases behavioral detection thresholds for slow but not fast sAM.

<p>(A) Detection thresholds during initial testing and for all subsequent testing days indicate gradual improvement (linear fitted <i>lines</i>) which did not differ across groups. (B) Behavioral detection curves for 5 Hz noise were averaged over the last 3 days of testing. (<i>C</i>) Thresholds derived from these curves showed that CHL animals had a small but highly significant increase in detection thresholds. (D) Improvement for 100 Hz sAM detection across testing days (linear fitted <i>lines</i>) did not differ across groups. (E) In contrast with slow sAM detection, behavioral curves for 100 Hz sAM detection overlapped in CTR and CHL animals, and (F) depth detection thresholds did not differ. <i>Black</i>  =  CTR; <i>Orange</i>  =  CHL. **  =  p<.01.</p

Neurometrics and psychometrics correlate with CHL treatment.

<p>Cells with BMFs of 5 Hz are compared with 5 Hz behavioral detection. (A) Individual neural d′ curves calculated from power at the modulation frequency (P_MF) were truncated by displaying only that portion that crossed threshold (<i>horizontal dashed line</i>) until the peak d′ value was attained, with all curves truncated at d′ = 4.0. Neurons whose curves never reached threshold are in <i>grey</i>. In CTRs (<i>top, black</i>) there are visibly more cells with sensitive thresholds than in CHL animals (<i>bottom, orange</i>): cells with thresholds <30% MD (<i>vertical dashed line</i>) are shown with thick lines. (B) The distribution of P_MF-based neural d′ thresholds (<i>bars</i>) was shifted significantly toward lower modulation depths for CTRs compared with CHLs. The behavioral performance of CTR and CHL animals (<i>circles</i>) is plotted at the top of each graph. The <i>blue shaded bars</i> indicate the region of CTR thresholds that do not overlap those of CHLs. (C) A pooling neurometric that represents a downstream neuron’s input summed across cells reveals better detection thresholds at low modulation depths for CTR versus CHL animals (<i>top</i>). The summed activity from which detection is computed is shown in the <i>bottom</i> graph. The larger symbols and dotted lines represent the baseline power in response to the lowest tested modulation depth, against which the other values were compared. *  =  p<.05.</p