Psychophysical and physiological evidence for fast binaural processing

The mammalian auditory system is the temporally most precise sensory modality: To localize low-frequency sounds in space, the binaural system can resolve time differences between the ears with microsecond precision. In contrast, the binaural system appears sluggish in tracking changing interaural time differences as they arise from a low-frequency sound source moving along the horizontal plane. For a combined psychophysical and electrophysiological approach, we created a binaural stimulus, called "Phasewarp," that can transmit rapid changes in interaural timing. Using this stimulus, the binaural performance in humans is significantly better than reported previously and comparable with the monaural performance revealed with amplitude-modulated stimuli. Parallel, electrophysiological recordings of binaural brainstem neurons in the gerbil show fast temporal processing of monaural and different types of binaural modulations. In a refined electrophysiological approach that was matched to the psychophysics, the seemingly faster binaural processing of the Phasewarp was confirmed. The current data provide both psychophysical and physiological evidence against a general, hard-wired binaural sluggishness and reconcile previous contradictions of electrophysiological and psychophysical estimates of temporal binaural performance

Adjustment of interaural-time-difference analysis to sound level

To localize low-frequency sound sources in azimuth, the binaural system compares the timing of sound waves at the two ears with microsecond precision. A similarly high precision is also seen in the binaural processing of the envelopes of high-frequency complex sounds. Both for low- and high-frequency sounds, interaural time difference (ITD) acuity is to a large extent independent of sound level. The mechanisms underlying this level-invariant extraction of ITDs by the binaural system are, however, only poorly understood. We use high-frequency pip trains with asymmetric and dichotic pip envelopes in a combined psychophysical, electrophysiological, and modeling approach. Although the dichotic envelopes cannot be physically matched in terms of ITD, the match produced perceptually by humans is very reliable, and it depends systematically on the overall sound level. These data are reflected in neural responses from the gerbil lateral superior olive and lateral lemniscus. The results are predicted in an existing temporal-integration model extended with a level-dependent threshold criterion. These data provide a very sensitive quantification of how the peripheral temporal code is conditioned for binaural analysis

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

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

Cooperative population coding facilitates efficient sound-source separability by adaptation to input statistics

Our sensory environment changes constantly. Accordingly, neural systems continually adapt to the concurrent stimulus statistics to remain sensitive over a wide range of conditions. Such dynamic range adaptation (DRA) is assumed to increase both the effectiveness of the neuronal code and perceptual sensitivity. However, direct demonstrations of DRA-based efficient neuronal processing that also produces perceptual benefits are lacking. Here, we investigated the impact of DRA on spatial coding in the rodent brain and the perception of human listeners. Complex spatial stimulation with dynamically changing source locations elicited prominent DRA already on the initial spatial processing stage, the Lateral Superior Olive (LSO) of gerbils. Surprisingly, on the level of individual neurons, DRA diminished spatial tuning because of large response variability across trials. However, when considering single-trial population averages of multiple neurons, DRA enhanced the coding efficiency specifically for the concurrently most probable source locations. Intrinsic LSO population imaging of energy consumption combined with pharmacology revealed that a slow-acting LSO gain-control mechanism distributes activity across a group of neurons during DRA, thereby enhancing population coding efficiency. Strikingly, such "efficient cooperative coding" also improved neuronal source separability specifically for the locations that were most likely to occur. These location-specific enhancements in neuronal coding were paralleled by human listeners exhibiting a selective improvement in spatial resolution. We conclude that, contrary to canonical models of sensory encoding, the primary motive of early spatial processing is efficiency optimization of neural populations for enhanced source separability in the concurrent environment

Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficient coding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform - Independent Component Analysis (ICA) trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment.Comment: 22 pages, 9 figure

Testing model for supernormal auditory localization

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 38-39).by John J. Park.M.Eng

Spectral cues are necessary to encode azimuthal auditory space in the mouse superior colliculus.

Sound localization plays a critical role in animal survival. Three cues can be used to compute sound direction: interaural timing differences (ITDs), interaural level differences (ILDs) and the direction-dependent spectral filtering by the head and pinnae (spectral cues). Little is known about how spectral cues contribute to the neural encoding of auditory space. Here we report on auditory space encoding in the mouse superior colliculus (SC). We show that the mouse SC contains neurons with spatially-restricted receptive fields (RFs) that form an azimuthal topographic map. We found that frontal RFs require spectral cues and lateral RFs require ILDs. The neurons with frontal RFs have frequency tunings that match the spectral structure of the specific head and pinna filter for sound coming from the front. These results demonstrate that patterned spectral cues in combination with ILDs give rise to the topographic map of azimuthal auditory space