Population rate-coding predicts correctly that human sound localization depends on sound intensity

The Rapid Decline in Interaural-Time-Difference Sensitivity for Pure Tones Can Be Explained by Peripheral Filtering

PURPOSE

The interaural time difference (ITD) is a primary horizontal-plane sound localization cue computed in the auditory brainstem. ITDs are accessible in the temporal fine structure of pure tones with a frequency of no higher than about 1400 Hz. How listeners' ITD sensitivity transitions from very best sensitivity near 700 Hz to impossible to detect within 1 octave currently lacks a fully compelling physiological explanation. Here, it was hypothesized that the rapid decline in ITD sensitivity is dictated not by a central neural limitation but by initial peripheral sound encoding, specifically, the low-frequency (apical) portion of the cochlear excitation pattern produced by a pure tone.

METHODS

ITD sensitivity was measured in 16 normal-hearing listeners as a joint function of frequency (900-1500 Hz) and level (10-50 dB sensation level).

RESULTS

Performance decreased with increasing frequency and decreasing sound level. The slope of performance decline was 90 dB/octave, consistent with the low-frequency slope of the cochlear excitation pattern.

CONCLUSION

Fine-structure ITD sensitivity near 1400 Hz may be conveyed primarily by "off-frequency" activation of neurons tuned to lower frequencies near 700 Hz. Physiologically, this could be realized by having neurons sensitive to fine-structure ITD up to only about 700 Hz. A more extreme model would have only a single narrow channel near 700 Hz that conveys fine-structure ITDs. Such a model is a major simplification and departure from the classic formulation of the binaural display, which consists of a matrix of neurons tuned to a wide range of relevant frequencies and ITDs.

The rapid decline in interaural-time-difference sensitivity for pure tones can be explained by peripheral filtering

Purpose

The interaural time difference (ITD) is a primary horizontal-plane sound localization cue computed in the auditory brainstem. ITDs are accessible in the temporal fine structure of pure tones with a frequency of no higher than about 1400 Hz. Explaining how listeners' ITD sensitivity transitions from very best sensitivity near 700 Hz to impossible to detect within 1 octave currently lacks a fully compelling physiological explanation. Here, it was hypothesized that the rapid decline in ITD sensitivity is dictated not by a central neural limitation but by initial peripheral sound encoding, specifically, the low-frequency (apical) edge of the cochlear excitation pattern produced by a pure tone.

Methods

ITD sensitivity was measured in 16 normal-hearing listeners as a joint function of frequency (900-1500 Hz) and level (10-50 dB sensation level).

Results

Performance decreased with increasing frequency and decreasing sound level. The slope of performance decline was 90 dB/octave, consistent with the low-frequency slope of the cochlear excitation pattern.

Conclusion

Fine-structure ITD sensitivity near 1400 Hz may be conveyed primarily by "off-frequency" activation of neurons tuned to lower frequencies near 700 Hz. Physiologically, this could be realized by having neurons sensitive to fine-structure ITD up to only about 700 Hz. A more extreme model would have only a single narrow channel near 700 Hz that conveys fine-structure ITDs. Such a model is a major simplification and departure from the classic formulation of the binaural display, which consists of a matrix of neurons tuned to a wide range of relevant frequencies and ITDs.

Amplification of input differences by dynamic heterogeneity in the spiral ganglion

A defining feature of type I primary auditory afferents that compose ∼95% of the spiral ganglion is their intrinsic electrophysiological heterogeneity. This diversity is evident both between and within unitary, rapid, and slow adaptation (UA, RA, and SA) classes indicative of specializations designed to shape sensory receptor input. But to what end? Our initial impulse is to expect the opposite: that auditory afferents fire uniformly to represent acoustic stimuli with accuracy and high fidelity. Yet this is clearly not the case. One explanation for this neural signaling strategy is to coordinate a system in which differences between input stimuli are amplified. If this is correct, then stimulus disparity enhancements within the primary afferents should be transmitted seamlessly into auditory processing pathways that utilize population coding for difference detection. Using sound localization as an example, one would expect to observe separately regulated differences in intensity level compared with timing or spectral cues within a graded tonotopic distribution. This possibility was evaluated by examining the neuromodulatory effects of cAMP on immature neurons with high excitability and slow membrane kinetics. We found that electrophysiological correlates of intensity and timing were indeed independently regulated and tonotopically distributed, depending on intracellular cAMP signaling level. These observations, therefore, are indicative of a system in which differences between signaling elements of individual stimulus attributes are systematically amplified according to auditory processing constraints. Thus, dynamic heterogeneity mediated by cAMP in the spiral ganglion has the potential to enhance the representations of stimulus input disparities transmitted into higher level difference detection circuitry.NEW & NOTEWORTHY Can changes in intracellular second messenger signaling within primary auditory afferents shift our perception of sound? Results presented herein lead to this conclusion. We found that intracellular cAMP signaling level systematically altered the kinetics and excitability of primary auditory afferents, exemplifying how dynamic heterogeneity can enhance differences between electrophysiological correlates of timing and intensity.

Population rate-coding predicts correctly that human sound localization depends on sound intensity

Human sound localization is an important computation performed by the brain. Models of sound localization commonly assume that sound lateralization from interaural time differences is level invariant. Here we observe that two prevalent theories of sound localization make opposing predictions. The labelled-line model encodes location through tuned representations of spatial location and predicts that perceived direction is level invariant. In contrast, the hemispheric-difference model encodes location through spike-rate and predicts that perceived direction becomes medially biased at low sound levels. Here, behavioral experiments find that softer sounds are perceived closer to midline than louder sounds, favoring rate-coding models of human sound localization. Analogously, visual depth perception, which is based on interocular disparity, depends on the contrast of the target. The similar results in hearing and vision suggest that the brain may use a canonical computation of location: encoding perceived location through population spike rate relative to baseline.

Being able to localize sounds helps us make sense of the world around us. The brain works out sound direction by comparing the times of when sound reaches the left versus the right ear. This cue is known as interaural time difference, or ITD for short. But how exactly the brain decodes this information is still unknown.

The brain contains nerve cells that each show maximum activity in response to one particular ITD. One idea is that these nerve cells are arranged in the brain like a map from left to right, and that the brain then uses this map to estimate sound direction. This is known as the Jeffress model, after the scientist who first proposed it. There is some evidence that birds and alligators actually use a system like this to localize sounds, but no such map of nerve cells has yet been identified in mammals. An alternative possibility is that the brain compares activity across groups of ITD-sensitive nerve cells. One of the oldest and simplest ways to measure this is to compare nerve activity in the left and right hemispheres of the brain. This readout is known as the hemispheric difference model.

By analyzing data from published studies, Ihlefeld, Alamatsaz, and Shapley discovered that these two models make opposing predictions about the effects of volume. The Jeffress model predicts that the volume of a sound will not affect a person’s ability to localize it. By contrast, the hemispheric difference model predicts that very soft sounds will lead to systematic errors, so that for the same ITD, softer sounds are perceived closer towards the front than louder sounds. To investigate this further, Ihlefeld, Alamatsaz, and Shapley asked healthy volunteers to localize sounds of different volumes. The volunteers tended to mis-localize quieter sounds, believing them to be closer to the body’s midline than they actually were, which is inconsistent with the predictions of the Jeffress model.

These new findings also reveal key parallels to processing in the visual system. Visual areas of the brain estimate how far away an object is by comparing the input that reaches the two eyes. But these estimates are also systematically less accurate for low-contrast stimuli than for high-contrast ones, just as sound localization is less accurate for softer sounds than for louder ones. The idea that the brain uses the same basic strategy to localize both sights and sounds generates a number of predictions for future studies to test.