Cognitive resources are distributed among the entire auditory landscape in auditory scene analysis.

Although attention has been shown to enhance neural representations of selected inputs, the fate of unselected background sounds is still debated. The goal of the current study was to understand how processing resources are distributed among attended and unattended sounds during auditory scene analysis. We used a three-stream paradigm with four acoustic features uniquely defining each sound stream (frequency, envelope shape, spatial location, tone quality). We manipulated task load by having participants perform a difficult auditory task and an easy movie-viewing task with the same set of sounds in separate conditions. The mismatch negativity (MMN) component of event-related brain potentials (ERPs) was measured to evaluate sound processing in both conditions. We found no effect of task demands on unattended sound processing: MMNs were elicited by unattended deviants during both low- and high-load task conditions. A key factor of this result was the use of unique tone feature combinations to distinguish each of the three sound streams, strengthening the segregation of streams. In the auditory task, the P3b component demonstrates a two-stage process of target evaluation. Thus, these results, in conjunction with results of previous studies, suggest that stimulus-driven factors that strengthen stream segregation can free up processing capacity for higher-level analyses. The results illustrate the interactive nature of top-down and stimulus-driven processes in stream formation, supporting a distributive theory of attention that balances the strength of the bottom-up input with perceptual goals in analyzing the auditory scene.

Distinguishing Neural Adaptation and Predictive Coding Hypotheses in Auditory Change Detection.

The auditory mismatch negativity (MMN) component of event-related potentials (ERPs) has served as a neural index of auditory change detection. MMN is elicited by presentation of infrequent (deviant) sounds randomly interspersed among frequent (standard) sounds. Deviants elicit a larger negative deflection in the ERP waveform compared to the standard. There is considerable debate as to whether the neural mechanism of this change detection response is due to release from neural adaptation (neural adaptation hypothesis) or from a prediction error signal (predictive coding hypothesis). Previous studies have not been able to distinguish between these explanations because paradigms typically confound the two. The current study disambiguated effects of stimulus-specific adaptation from expectation violation using a unique stimulus design that compared expectation violation responses that did and did not involve stimulus change. The expectation violation response without the stimulus change differed in timing, scalp distribution, and attentional modulation from the more typical MMN response. There is insufficient evidence from the current study to suggest that the negative deflection elicited by the expectation violation alone includes the MMN. Thus, we offer a novel hypothesis that the expectation violation response reflects a fundamentally different neural substrate than that attributed to the canonical MMN.