Quantifying the Information in Auditory-Nerve Responses for Level Discrimination

Abstract

An analytical approach for quantifying the information in auditory-nerve (AN) fiber responses for the task of level discrimination is described. A simple analytical model for AN responses is extended to include temporal response properties, including the nonlinear-phase effects of the cochlear amplifier. Use of simple analytical models for AN discharge patterns allows quantification of the contributions of leveldependent aspects of the patterns to level discrimination. Specifically, the individual and combined contributions of the information contained in discharge rate, synchrony, and relative phase cues are explicitly examined for level discrimination of tonal stimuli. It is shown that the rate information provided by individual AN fibers is more constrained by increases in variance with increases in rate than by saturation. As noted in previous studies, there is sufficient average-rate information within a narrow-CF region to account for robust behavioral performance over a wide dynamic range; however, there is no model based on a simple limitation or use of AN information consistent with parametric variations in performance. This issue is explored in the current study through analysis of performance based on different aspects of AN patterns. For example, we show that performance predicted from use of all rate information degrades significantly as level increases above low-medium levels, inconsistent with Weber's Law. At low frequencies, synchrony information extends the range over which behavioral performance can be explained by 10-15 dB, but only at low levels. In contrast to rate and synchrony, nonlinear-phase cues are shown to provide robust information at medium and high levels in near-CF fibers for lowfrequency stimuli. The level dependence of the discharge rate and phase properties of AN fibers are influenced by the compressive nonlinearity of the inner ear. Evaluating the role of the compressive nonlinearity in level coding is important for understanding neural encoding mechanisms and because of its association with the cochlear amplifier, which is a fragile aspect of the ear believed to be affected in common forms of hearing impairment.

Intensity-invariant coding in the auditory system

“…Threshold measurements made in auditory nerve support the notion that individual neuronal dynamic ranges are dispersed somewhat across the total intensity range of hearing (Evans, 1972; Liberman, 1978; Liberman and Kiang, 1978; Sachs and Abbas, 1974). Thresholds of auditory nerve fibers have classically been evaluated as absolute spiking rate measures evoked by stimuli versus spontaneous rates, but similar trends hold true when statistical properties of rate responses are taken into account (Geisler, Deng et al, 1985; Young and Barta, 1986) and are logically extended when temporal information in the spike trains is considered (Carney, 1994; Colburn, Carney et al, 2003). …”

Across-Channel Timing Differences as a Potential Code for the Frequency of Pure Tones

“…Here, we simply note that the various potential weaknesses of the two traditional approaches have led to considerable interest in an alternative class of explanation, whereby the auditory system performs an instantaneous comparison of the temporal pattern of firing in auditory neurons having different CFs (Loeb et al 1983; Shamma 1985; Carney 1994; Heinz et al 2001; Carney et al 2002; Colburn et al 2003; Oxenham et al 2004; Loeb 2005; Moore and Carlyon 2005; Cedolin and Delgutte 2010). This idea stems from the fact that the phase of AN responses varies across CF in a manner that varies with the input frequency.…”

“…Bright colours ( red , yellow ) indicate a high instantaneous firing rate; darker colours ( dark blue ) correspond to instantaneous firing rates close to zero. Following Colburn et al (2003), the instantaneous firing rate was approximated as a scaled exponential function of the input waveform where the scaling factor was chosen to yield a synchronization index of 0.81. Because the purpose of this figure is to illustrate specifically the phase effects and the relative timing of neural responses to tones of different frequencies, the effects of peripheral frequency selectivity on the firing rate are not shown.…”

“…A number of authors have described neural mechanisms by which the auditory system might exploit these across-channel phase differences, both for the perception of pitch, the detection of tones in noise, the coding of sound level, and for enhancing spectral representations of complex sounds (Loeb et al 1983; Shamma 1985; Carney 1994; Heinz et al 2001; Carney et al 2002; Colburn et al 2003; Loeb 2005; Cedolin and Delgutte 2010). Examples include the subtraction of the outputs of nearby channels (Shamma 1985; Cedolin and Delgutte 2010), the processing of channels whose outputs are de-correlated due to the presence of a narrowband sound (Carney et al 2002), and the detection of co-incidences between the outputs of channels having different CFs (Loeb et al 1983; Loeb 2005).…”

“…Furthermore, it has been known for some time that the phase response of the BM and of individual neurons varies with the input level (Anderson et al 1971; Rhode 1971); in fact, the slopes of the lines in Figure 1 are slightly shallower at higher levels, reflecting the broader frequency tuning at those levels (Kim, personal communication). Moreover, changes in this slope with level, arising from the operation of the cochlear amplifier and the consequent change in tuning, have been proposed as a means by which the sound level is encoded by the auditory system (Carney 1994; Heinz et al 2001; Colburn et al 2003), suggesting that PT cues may not provide a level-independent cue to pitch. The present study investigates this issue in an attempt to determine whether PTs can support a level-independent code for pure-tone pitch and evaluates four possible ways that phase transitions could be processed in order to provide such a level-independent code.…”