Abstract
Binaural sound localization is usually considered a discrimination task, where interaural phase (IPD) and level (ILD) disparities at narrowly tuned frequency channels are utilized to identify a position of a sound source. In natural conditions however, binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. Distribution of cues encountered naturally and their dependence on physical properties of an auditory scene have not been studied before. In the present work we analyzed statistics of naturally encountered binaural sounds. We performed binaural recordings of three auditory scenes with varying spatial configuration and analyzed empirical cue distributions from each scene. We have found that certain properties such as the spread of IPD distributions as well as an overall shape of ILD distributions do not vary strongly between different auditory scenes. Moreover, we found that ILD distributions vary much weaker across frequency channels and IPDs often attain much higher values, than can be predicted from head filtering properties. In order to understand the complexity of the binaural hearing task in the natural environment, sound waveforms were analyzed by performing Independent Component Analysis (ICA). Properties of learned basis functions indicate that in natural conditions soundwaves in each ear are predominantly generated by independent sources. This implies that the real-world sound localization must rely on mechanisms more complex than a mere cue extraction.
Highlights
The idea that sensory systems reflect the statistical structure of stimuli encountered by organisms in their ecological niches [1,2,3] has driven numerous theoretical and experimental studies
In the present study we approached binaural hearing from a different perspective - we focused on marginal distributions of naturally encountered binaural sounds
We have selected them as stereotypes of numerous possible environments consisting of static and moving sources. This diversity increased the likelihood that any other auditory scene typically encountered by a human listener would resemble one of those recorded in the present study
Summary
The idea that sensory systems reflect the statistical structure of stimuli encountered by organisms in their ecological niches [1,2,3] has driven numerous theoretical and experimental studies. Obtained results suggest that tuning properties of sensory neurons match regularities present in natural stimuli [4]. In light of this theory, neural representations, coding mechanisms and anatomical structures could be understood by studying characteristics of the sensory environment. The statistical characterization of ecological input allows to better understand the complexity of perceptual tasks, when performed in non-laboratory conditions. This in turn provides a constraint on a class of algorithms, which may be implemented by the nervous system when dealing with the real world stimuli
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