Human Auditory cortical processing of changes in interaural correlation

Sensitivity to the similarity of the acoustic waveforms at the two ears, and specifically to changes in similarity, is crucial to auditory scene analysis and extraction of objects from background. Here, we use the high temporal resolution of magnetoencephalography to investigate the dynamics of cortical processing of changes in interaural correlation, a measure of interaural similarity, and compare them with behavior. Stimuli are interaurally correlated or uncorrelated wideband noise, immediately followed by the same noise with intermediate degrees of interaural correlation. Behaviorally, listeners' sensitivity to changes in interaural correlation is asymmetrical. Listeners are faster and better at detecting transitions from correlated noise than transitions from uncorrelated noise. The cortical response to the change in correlation is characterized by an activation sequence starting from ∼50 ms after change. The strength of this response parallels behavioral performance: auditory cortical mechanisms are much less sensitive to transitions from uncorrelated noise than from correlated noise. In each case, sensitivity increases with interaural correlation difference. Brain responses to transitions from uncorrelated noise lag those from correlated noise by ∼80 ms, which may be the neural correlate of the observed behavioral response time differences. Importantly, we demonstrate differences in location and time course of neural processing: transitions from correlated noise are processed by a distinct neural population, and with greater speed, than transitions from uncorrelated noise

Detectability index measures of binaural masking level difference across populations of inferior colliculus neurons.

In everyday life we continually need to detect signals against a background of interfering noise (the “cocktail party effect”): a task that is much easier to accomplish using two ears. The binaural masking level difference (BMLD) measures the ability of listeners to use a difference in binaural attributes to segregate sound sources and thus improve their discriminability against interfering noises. By computing the detectability of tones from rate-versus-level functions in the presence of a suprathreshold noise, we previously demonstrated that individual low-frequency delay-sensitive neurons in the inferior colliculus are able to show BMLDs. Here we consider the responses of a population of such neurons when the noise level is held constant (as conventionally in psychophysical paradigms). We have sampled the responses of 121 units in the inferior colliculi of five guinea pigs to identical noise and 500 Hz tones at both ears (NoSo) and to identical noise but with the 500 Hz tone at one ear inverted (NoSπ). The result suggests that the neurons subserving detection of So tones in No (identical noise at the two ears) noise are those neurons with best frequencies (BFs) close to 500 Hz that respond to So tones with an increase in their discharge rate from that attributable to the noise. The detection of the inverted (Sπ) signal is also attributable to neurons with BFs close to 500 Hz. However, among these neurons, the presence of the Sπ tone was indicated by an increased discharge rate in some neurons and by a decreased discharge rate in others

Functional anatomy of the masking level difference, an fMRI study

Introduction: Masking level differences (MLDs) are differences in the hearing threshold for the detection of a signal presented in a noise background, where either the phase of the signal or noise is reversed between ears. We use N0/Nπ to denote noise presented in-phase/out-of-phase between ears and S0/Sπ to denote a 500 Hz sine wave signal as in/out-of-phase. Signal detection level for the noise/signal combinations N0Sπ and NπS0 is typically 10-20 dB better than for N0S0. All combinations have the same spectrum, level, and duration of both the signal and the noise. Methods: Ten participants (5 female), age: 22-43, with N0Sπ-N0S0 MLDs greater than 10 dB, were imaged using a sparse BOLD fMRI sequence, with a 9 second gap (1 second quiet preceding stimuli). Band-pass (400-600 Hz) noise and an enveloped signal (.25 second tone burst, 50% duty-cycle) were used to create the stimuli. Brain maps of statistically significant regions were formed from a second-level analysis using SPM5. Results: The contrast NπS0- N0Sπ had significant regions of activation in the right pulvinar, corpus callosum, and insula bilaterally. The left inferior frontal gyrus had significant activation for contrasts N0Sπ-N0S0 and NπS0-N0S0. The contrast N0S0-N0Sπ revealed a region in the right insula, and the contrast N0S0-NπS0 had a region of significance in the left insula. Conclusion: Our results extend the view that the thalamus acts as a gating mechanism to enable dichotic listening, and suggest that MLD processing is accomplished through thalamic communication with the insula, which communicate across the corpus callosum to either enhance or diminish the binaural signal (depending on the MLD condition). The audibility improvement of the signal with both MLD conditions is likely reflected by activation in the left inferior frontal gyrus, a late stage in the what/where model of auditory processing. © 2012 Wack et al

A binaural grouping model for predicting speech intelligibility in multitalker environments

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model.R01 DC000100 - NIDCD NIH HH

Adaptation of Binaural Processing in the Adult Brainstem Induced by Ambient Noise

Interaural differences in stimulus intensity and timing are major cues for sound localization. In mammals, these cues are first processed in the lateral and medial superior olive by interaction of excitatory and inhibitory synaptic inputs from ipsi- and contralateral cochlear nucleus neurons. To preserve sound localization acuity following changes in the acoustic environment, the processing of these binaural cues needs neuronal adaptation. Recent studies have shown that binaural sensitivity adapts to stimulation history within milliseconds, but the actual extent of binaural adaptation is unknown. In the current study, we investigated long-term effects on binaural sensitivity using extracellular in vivo recordings from single neurons in the dorsal nucleus of the lateral lemniscus that inherit their binaural properties directly from the lateral and medial superior olives. In contrast to most previous studies, we used a noninvasive approach to influence this processing. Adult gerbils were exposed for 2 weeks to moderate noise with no stable binaural cue. We found monaural response properties to be unaffected by this measure. However, neuronal sensitivity to binaural cues was reversibly altered for a few days. Computational models of sensitivity to interaural time and level differences suggest that upregulation of inhibition in the superior olivary complex can explain the electrophysiological data