Statistical Analyses of Temporal Information in Auditory Brainstem Responses to Tones in Noise: Correlation Index and Spike-distance Metric

Gai and Carney (J Neurophysiol 96:2451–2464, 2006) previously explored the detection of tones in noise based on responses in the anteroventral cochlear nucleus; that study focused on temporal information in discharge reliability and analyses of neural responses related to the fine structure or envelope of the stimulus. Two additional temporal approaches, the correlation index (Joris et al., Hearing Res 216–217:19–30, 2006) and the spike-distance metric (Victor and Purpura, J Neurophysiol 76:1310–1326, 1996; Netw Comput Neural Syst 8:127–164, 1997), are tested in the present study. Trends in the correlation index as a function of stimulus level are similar to those of the synchronization coefficient (also called the vector strength) when the tone is presented alone. However, the present study found that trends in the correlation index did not agree with those of the synchronization coefficient for tones presented with relatively high-level background noise. Instead, trends in the correlation index generally agreed with those of the temporal reliability metric discussed in Gai and Carney (J Neurophysiol 96:2451–2464, 2006); that is, the correlation index decreased with increased tone level in the presence of relatively high-level background noise. The spike-distance metric, which was based on absolute spike times or on interspike intervals, was compared to the temporal measures described above, which were generally based on relative spike times. The results confirm that the spike-distance metric is not an optimal temporal metric. In addition, absolute spike times of primary-like responses generally contained much less temporal information than absolute spike times of chopper response types. The present study highlights the importance of relative spike-timing information as characterized by traditional and novel temporal measures

Neural population coding of sound level adapts to stimulus statistics

Mammals can hear sounds extending over a vast range of sound levels with remarkable accuracy. How auditory neurons code sound level over such a range is unclear; firing rates of individual neurons increase with sound level over only a very limited portion of the full range of hearing. We show that neurons in the auditory midbrain of the guinea pig adjust their responses to the mean, variance and more complex statistics of sound level distributions. We demonstrate that these adjustments improve the accuracy of the neural population code close to the region of most commonly occurring sound levels. This extends the range of sound levels that can be accurately encoded, fine-tuning hearing to the local acoustic environment

Detection of Tones in Reproducible Noise Maskers by Rabbits and Comparison to Detection by Humans

Processing mechanisms used for detection of tones in noise can be revealed by using reproducible noise maskers and analyzing the pattern of results across masker waveforms. This study reports detection of a 500-Hz tone in broadband reproducible noise by rabbits using a set of masker waveforms for which human results are available. An appetitive-reinforcement, operant-conditioning procedure with bias control was used. Both fixed-level and roving-level noises were used to explore the utility of energy-related cues for detection. An energy-based detection model was able to partially explain the fixed-level results across reproducible noise waveforms for both rabbit and human. A multiple-channel energy model was able to explain fixed-level results, as well as the robust performance observed with roving-level noises. Further analysis using the energy model indicated a difference between species: human detection was influenced most by the noise spectrum surrounding the tone frequency, whereas rabbit detection was influenced most by the noise spectrum at frequencies above that of the tone. In addition, a temporal envelope-based model predicted detection by humans as well as the single-channel energy model did, but the envelope-based model failed to predict detection by rabbits. This result indicates that the contributions of energy and temporal cues to auditory processing differ across species. Overall, these findings suggest that caution must be used when evaluating neural encoding mechanisms in one species on the basis of behavioral results in another

Effects of Signal Level and Background Noise on Spectral Representations in the Auditory Nerve of the Domestic Cat

Background noise poses a significant obstacle for auditory perception, especially among individuals with hearing loss. To better understand the physiological basis of this perceptual impediment, the present study evaluated the effects of background noise on the auditory nerve representation of head-related transfer functions (HRTFs). These complex spectral shapes describe the directional filtering effects of the head and torso. When a broadband sound passes through the outer ear en route to the tympanic membrane, the HRTF alters its spectrum in a manner that establishes the perceived location of the sound source. HRTF-shaped noise shares many of the acoustic features of human speech, while communicating biologically relevant localization cues that are generalized across mammalian species. Previous studies have used parametric manipulations of random spectral shapes to elucidate HRTF coding principles at various stages of the cat’s auditory system. This study extended that body of work by examining the effects of sound level and background noise on the quality of spectral coding in the auditory nerve. When fibers were classified by their spontaneous rates, the coding properties of the more numerous low-threshold, high-spontaneous rate fibers were found to degrade at high presentation levels and in low signal-to-noise ratios. Because cats are known to maintain accurate directional hearing under these challenging listening conditions, behavioral performance may be disproportionally based on the enhanced dynamic range of the less common high-threshold, low-spontaneous rate fibers