The Neural Code for Auditory Space Depends on Sound Frequency and Head Size in an Optimal Manner

Abstract

A major cue to the location of a sound source is the interaural time difference (ITD)–the difference in sound arrival time at the two ears. The neural representation of this auditory cue is unresolved. The classic model of ITD coding, dominant for a half-century, posits that the distribution of best ITDs (the ITD evoking a neuron’s maximal response) is unimodal and largely within the range of ITDs permitted by head-size. This is often interpreted as a place code for source location. An alternative model, based on neurophysiology in small mammals, posits a bimodal distribution of best ITDs with exquisite sensitivity to ITDs generated by means of relative firing rates between the distributions. Recently, an optimal-coding model was proposed, unifying the disparate features of these two models under the framework of efficient coding by neural populations. The optimal-coding model predicts that distributions of best ITDs depend on head size and sound frequency: for high frequencies and large heads it resembles the classic model, for low frequencies and small head sizes it resembles the bimodal model. The optimal-coding model makes key, yet unobserved, predictions: for many species, including humans, both forms of neural representation are employed, depending on sound frequency. Furthermore, novel representations are predicted for intermediate frequencies. Here, we examine these predictions in neurophysiological data from five mammalian species: macaque, guinea pig, cat, gerbil and kangaroo rat. We present the first evidence supporting these untested predictions, and demonstrate that different representations appear to be employed at different sound frequencies in the same species.

Relative sound localisation abilities in human listeners

“…While recent neuroimaging studies have lent support to a two-channel model of sound location in human auditory cortex (Salminen et al, 2009;Salminen et al, 2010;Magezi and Krumbholz, 2010;Briley et al, 2013), alternative models of the neural representation of sound location propose that space may be represented by a three-channel model (Dingle et al, 2010(Dingle et al, , 2012(Dingle et al, , 2013 or that an optimal model would change according to both frequency and head size such that, for humans, coding is predicted to be two-channel at low frequencies and labeled line/topographic at higher frequencies (Harper et al, 2014). Recent physiological findings from auditory cortex are also consistent with a labeled-line code for sound localisation cues (Belliveau et al, 2014;Moshitch and Nelken, 2014).…”

In vivo Recordings from Low-Frequency Nucleus Laminaris in the Barn Owl

“…In a 2-channel model of ITD coding, many best ITD values are predicted to fall outside the naturally heard range of the animal [Harper and McAlpine, 2004;Harper et al, 2014], while the Jeffress model predicts all values to fall within that range. What is this range for the barn owl?…”

“…However, the work by Harper and colleagues [Harper and McAlpine, 2004;Harper et al, 2014] on optimal ITDcoding strategies opened up a different interpretation, suggesting that animal head size and the frequency range of coding may be the primary factors that determine the neural code. This can be tested by examining the neural organization in the relevant nuclei as a function of frequency.…”

Sound Localization Strategies in Three Predators

“…Also, with low best frequency ITD functions, the response maxima often lie outside the physiological range of ITDs, so that the resolution of place code of best ITDs decreases. Harper and McAlpine [Harper and McAlpine, 2004; Harper et al, 2014] proposed an optimized solution for low frequency ITD coding would be to compare the response slopes of two populations of neurons, one in each hemifield, with response peaks outside the physiological range of ITD, i.e. the meters described above [Harper and McAlpine, 2004].…”

“…a meter at low frequencies and maps at higher frequencies. These coding strategies would also depend on head size [Harper et al, 2014]. Given the low frequency hearing in crocodilians, their best coding strategy might be to compare two meters.…”