Temporal information in the responses of auditory neurons to sustained sounds has been studied mostly with periodic stimuli, using measures that are based on Fourier analysis. Less information is available on temporal aspects of responses to nonperiodic wideband sounds. We recorded responses to a reference Gaussian noise and its polarity-inverted version in the auditory nerve of barbiturate-anesthetized cats and used shuffled autocorrelograms (SACs) to quantify spike timing. Two metrics were extracted from the central peak of autocorrelograms: the peak-height and the width at halfheight. Temporal information related to stimulus fine-structure was isolated from that to envelope by subtracting or adding responses to the reference and inverted noise. Peak-height and halfwidth generally behaved as expected from the existing body of data on phase-locking to pure tones and sinusoidally amplitude-modulated tones but showed some surprises as well. Compared with synchronization to low-frequency tones, SACs reveal large differences in temporal behavior between the different classes of nerve fibers (based on spontaneous rate) as well as a strong dependence on characteristic frequency (CF) throughout the phase-locking range. SACs also reveal a larger temporal consistency (i.e., tendency to discharge at the same point in time on repeated presentation of the same stimulus) in the responses to the stochastic noise stimulus than in the responses to periodic tones. Responses at high CFs reflect envelope phase-locking and are consistent with previous reports using sinusoidal AM. We conclude that the combined use of broadband noise and SAC analysis allow a more general characterization of temporal behavior than periodic stimuli and Fourier analysis.
Binaural auditory neurons exhibit ''best delays'' (BDs): They are maximally activated at certain acoustic delays between sounds at the two ears and thereby signal spatial sound location. BDs arise from delays internal to the auditory system, but their source is controversial. According to the classic Jeffress model, they reflect pure time delays generated by differences in axonal length between the inputs from the two ears to binaural neurons. However, a relationship has been reported between BDs and the frequency to which binaural neurons are most sensitive (the characteristic frequency), and this relationship is not predicted by the Jeffress model. An alternative hypothesis proposes that binaural neurons derive their input from slightly different places along the two cochleas, which induces BDs by virtue of the slowness of the cochlear traveling wave. To test this hypothesis, we performed a coincidence analysis on spiketrains of pairs of auditory nerve fibers originating from different cochlear locations. In effect, this analysis mimics the processing of phase-locked inputs from each ear by binaural neurons. We find that auditory nerve fibers that innervate different cochlear sites show a maximum number of coincidences when they are delayed relative to each other, and that the optimum delays decrease with characteristic frequency as in binaural neurons. These findings suggest that cochlear disparities make an important contribution to the internal delays observed in binaural neurons.auditory nerve ͉ phase-locking ͉ sound localization ͉ stereo ͉ temporal coding A remarkable feat of the human auditory system is its extraordinary sensitivity to differences in the acoustic waveforms between the two ears. Interaural time differences (ITDs) arise when sound sources are offset from the midline toward one side of the head, and differences in ITD can be perceived to values of 10-20 s. Most computational models of this ability are based on the qualitative scheme of Jeffress (1) in which a population of binaural cells effectively cross-correlates the two monaural signals by a process of coincidence detection and delay lines. In this scheme, the input to a binaural neuron from one ear is delayed relative to that of the other ear by a so-called ''internal delay,'' generated by differences in length of the axonal pathways from each side. The binaural neurons are coincidence detectors whose inputs are spiketrains that are time-locked to the ongoing features of the sound stimulus at each ear. Only spiketrains that arrive coincidentally activate the binaural cell: This activation is achieved at an ITD (''best delay'' or BD) that exactly compensates for the internal delay. By arranging these axons in a delay-line pattern, a range of internal delays to different coincidence detectors is created.There is physiological and anatomical support for the Jeffress model both in the medial superior olive (MSO) of mammals and in nucleus laminaris of the barn owl (2, 3). However, binaural data in the mammalian inferior colliculus (IC), whi...
Compared with auditory nerve (AN) fibers, trapezoid body (TB) fibers of the cat show enhanced synchronization to low-frequency tones. This phenomenon probably contributes to the high temporal resolution of binaural processing. We examined whether enhanced synchronization also occurs to sustained broadband noise. We recorded responses to a reference Gaussian noise and its polarity-inverted version in the TB of barbiturate-anesthetized cats. From these we constructed shuffled autocorrelograms (SACs) and quantified spike timing by measuring the amplitude and width of their central peak.Many TB fibers with low characteristic frequency (CF) showed SACs with higher and narrower central peaks than ever observed in the AN, indicating better consistency and precision of temporal coding. Larger peaks were also observed in TB fibers with high CF, but this was mostly caused by higher average firing rates, resulting in a larger number of coincident spikes across stimulus repetitions. The results document monaural preprocessing of the temporal information delivered to binaural nuclei in the olivary complex, which likely contributes to the high sensitivity to interaural time differences.
Binaural neurons show remarkable sensitivity to temporal differences in the waveforms at the two ears. This ability obviously requires temporal coding of sound waveforms in the monaural afferents that converge on such binaural neurons. We introduce a new analysis to investigate how well responses of single monaural neurons support discrimination of decorrelations in waveforms. Spike trains from auditory nerve (AN) and anteroventral cochlear nucleus (AVCN) neurons of cats to many repetitions of a set of broadband and narrowband noise tokens were obtained. The normalized correlation between the noise tokens ranged from 0.99 to Ϫ1. A coincidence and signal detection analysis was used to perform a correlation discrimination task using the monaural spike trains. The correlation discrimination thresholds derived from AVCN neurons were lower than those derived from AN fibers and sometimes as low as human psychophysical just noticeable differences. Importantly, low detection thresholds required comparisons of spike trains at small internal delays. Bandwidth dependence of neural decorrelation thresholds agreed with psychophysical data when large internal delays contributed to the detection. We conclude that, in the context of correlation discrimination, coding by AVCN fibers is superior to that by AN fibers and that these discriminations require a distribution of internal or best delays in binaural processing that differs from the predictions from studies of discrimination in interaural time delays.
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