A hemispheric two-channel code accounts for binaural unmasking in humans

The neural representation of an auditory spatial cue in the primate cortex

Humans make use of small differences in the timing of sounds at the two ears-interaural time differences (ITDs)-to locate their sources. Despite extensive investigation, however, the neural representation of ITDs in the human brain is contentious, particularly the range of ITDs explicitly represented by dedicated neural detectors. Here, using magneto- and electro-encephalography (MEG and EEG), we demonstrate evidence of a sparse neural representation of ITDs in the human cortex. The magnitude of cortical activity to sounds presented via insert earphones oscillated as a function of increasing ITD-within and beyond auditory cortical regions-and listeners rated the perceptual quality of these sounds according to the same oscillating pattern. This pattern was accurately described by a population of model neurons with preferred ITDs constrained to the narrow, sound-frequency-dependent range evident in other mammalian species. When scaled for head size, the distribution of ITD detectors in the human cortex is remarkably like that recorded in vivo from the cortex of rhesus monkeys, another large primate that uses ITDs for source localization. The data solve a long-standing issue concerning the neural representation of ITDs in humans and suggest a representation that scales for head size and sound frequency in an optimal manner.

Fast binaural processing but sluggish masker representation reconfiguration

Perceptual organization of complex acoustic scenes requires fast binaural processing for accurate localization or lateralization based on short single-source-dominated glimpses. This sensitivity also manifests in the ability to detect rapid oscillating interaural time and phase differences as well as interaural correlation. However, binaural processing has also been termed "sluggish" based on experiments that require binaural detection in a masker with an additional binaural cue change in temporal proximity. The present study shows that the temporal integration windows obtained from data on binaural sluggishness cannot account for the detection of rapid binaural oscillations. A model with fast IPD encoding but a slower process of updating the internal representation of the masker IPD statistics accounted for both experiments of the "fast" and the "sluggish" categories.

Inferring the basis of binaural detection with a modified autoencoder

The binaural system utilizes interaural timing cues to improve the detection of auditory signals presented in noise. In humans, the binaural mechanisms underlying this phenomenon cannot be directly measured and hence remain contentious. As an alternative, we trained modified autoencoder networks to mimic human-like behavior in a binaural detection task. The autoencoder architecture emphasizes interpretability and, hence, we "opened it up" to see if it could infer latent mechanisms underlying binaural detection. We found that the optimal networks automatically developed artificial neurons with sensitivity to timing cues and with dynamics consistent with a cross-correlation mechanism. These computations were similar to neural dynamics reported in animal models. That these computations emerged to account for human hearing attests to their generality as a solution for binaural signal detection. This study examines the utility of explanatory-driven neural network models and how they may be used to infer mechanisms of audition.

Statistics of the instantaneous interaural parameters for dichotic tones in diotic noise (N0Sψ)

Stimuli consisting of an interaurally phase-shifted tone in diotic noise—often referred to as N0Sψ—are commonly used to study binaural hearing. As a consequence of mixing diotic noise with a dichotic tone, this type of stimulus contains random fluctuations in both interaural phase- and level-difference. We report the joint probability density functions of the two interaural differences as a function of amplitude and interaural phase of the tone. Furthermore, a second joint probability density function for interaural phase differences and the instantaneous cross-power is derived. The closed-form expression can be used in future studies of binaural unmasking first to obtain the interaural statistics and then study more directly the relation between those statistics and binaural tone detection.