![]() We first established the ferret as an animal model for streaming of repeating noise sounds, by designing a behavioral paradigm that assessed animals’ ability to detect repetitions embedded in mixtures. In this study, we investigated neural correlates of streaming induced by repetition of complex sounds in primary (A1) and secondary (PEG) fields of the auditory cortex. How the brain might use adaptation to a repeating sound to enhance its perception is not known. There is no evidence that links SSA or MMN with repetition-based grouping, but it is possible that these processes share some of the same neural circuits. Although the dynamics are slower than SSA, MMN is also elicited by rare deviant sounds randomly interspersed among frequent standard sounds ( 27). In human electroencephalography (EEG), a possibly related phenomenon is observed in a late event-related component, called the mismatch negativity (MMN). Single neurons undergo stimulus-specific adaptation (SSA), where responses to repeated tones adapt, but responses to an oddball stimulus, such as a tone at a different frequency, are less adapted or even facilitated, reflecting perceptual pop-out of the oddball sound ( 25, 26). In contrast to the robust perceptual enhancement reported for a repeating foreground stream, studies of neurophysiological activity in auditory cortex have emphasized a suppressive effect of repetition ( 24). The neural bases of this perceptual pop-out remain unknown. While non-repeating samples could not be distinguished from background noise, humans could identify these same samples when they were repeated. (2011) tested specifically for the benefit of temporal regularity with a set of naturalistic noise samples that lacked other cues for streaming ( 23). Segregating spectrally overlapping sounds requires use of perceptual cues such as pitch ( 11, 12), timbre ( 13– 15), spatial location ( 3, 12– 16), common onset ( 17, 18), and temporal regularity ( 19– 22). However, more complex natural sounds often overlap in frequency. Streaming requires statistical analysis of sound sources: streams that come from the same sound source share statistical regularities, and the brain uses these properties as cues for stream integration or segregation ( 2– 6).īasic acoustic features, such as separation in frequency and time, are key perceptual cues for segregating simple, alternating sequences of pure tones ( 7– 10). The auditory system has the remarkable ability to group these dynamically changing spectro-temporal sound features into percepts of their distinct sources, in a process known as auditory streaming ( 1, 2). Sounds generated by different sources, or auditory objects, impinge on the ear as a complex mixture, with acoustic energy generated by each source overlapping in both time and frequency. ![]() Thus, while overall auditory responses were reduced by the repeating sound, enhancement of responses to the foreground stream relative to the background provides evidence for stream segregation that emerges in A1 and is refined in PEG. It was strongest in units that displayed low sparseness ( i.e., broad sensory tuning) and were tuned preferentially to the repeated sample. In A1, the degree of enhancement depended on auditory tuning. This enhancement was stronger in PEG than in A1. However, when we measured stream-specific changes in gain, neural responses to the foreground stream were enhanced relative to the background. Consistent with adaptation, we found an overall reduction in global gain when the stimulus was repeated. Separate models tested whether time-varying neural spike rates were better predicted by scaling the response to both streams of the repeating stimulus equally (global response gain), or by scaling the response of one stream relative to another (stream-specific response gain). We used context-dependent encoding models to test for evidence of streaming of the repeating stimulus in these brain areas. While they listened passively, we recorded neural activity in primary (A1) and secondary (PEG) fields of auditory cortex. We trained ferrets to detect a stream of repeating noise samples (foreground) embedded in a stream of random noise samples (background). Repetition is one cue that drives stream segregation in humans, but the neural basis of this perceptual phenomenon remains unknown. Statistical regularities in natural sounds facilitate the perceptual segregation of auditory sources, or streams.
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