Neural sensitivity to interaural time differences: beyond the Jeffress model

Tuning to interaural time differences across frequency

Interaural time differences (ITDs) are an important cue for azimuthal sound localization. Sensitivity to this cue depends on temporal synchrony to the waveform (i.e., phase locking) that begins in the hair cells and is relayed to the neural comparators. The synchrony function is low-pass. Therefore, it is expected that neural tuning to ITDs will become narrower with frequency according to a 1/frequency function. To test this, we measured ITD tuning across frequency in neurons from the superior olivary complex, the dorsal nucleus of the lateral lemniscus, the inferior colliculus, the auditory thalamus, and the auditory cortex. For some neurons in each nucleus, the ITD tuning width did become systematically narrower by the expected 1/frequency relationship. However, in other neurons the ITD tuning width was nearly constant across frequency. Constant ITD tuning width was infrequently observed in neurons of the superior olivary complex but was common in neurons in structures above the superior olivary complex. The nearly constant ITD tuning was caused both by sharper ITD tuning at low frequencies and broader tuning at higher frequencies within the low-frequency band. Neurons with nearly constant tuning to ITDs may be the mechanism underlying the perception of ITDs in humans in which just-noticeable differences to changes in ITD decrease by less than the 1/frequency prediction.

Modelling convergent input onto interaural-delay-sensitive inferior colliculus neurones

Convergent input from cells in the medial superior olive (MSO) and lateral superior olive (LSO) onto a single inferior colliculus (IC) cell explains many findings that are not compatible with a simple coincidence detector mechanism. Here this explanation is tested using a physiologically accurate computer model of the binaural pathway in which the input to the IC cell is either from two MSO cells or a MSO and a LSO cell. Auditory nerve (AN) spike trains are formed by a stochastic hair cell model following a basilar membrane simulation using a gammatone filter. In subsequent cells input spikes cause post-synaptic potentials (PSPs) which are summed causing the cell to fire when the sum crosses a threshold. The individual cells are matched to the physiology by varying the number of inputs, the magnitude and duration of the PSPs and the firing threshold. Non-linear best-phase-versus-frequency functions arise if the two IC inputs have different best frequencies and different characteristic delays. One input can be selectively suppressed by turning on an additional tone at the worst phase of that input. Non-zero characteristic phases arise if the characteristic frequencies of the AN fibres feeding into a single superior olive cell are mismatched.