We use behavioral methods, magnetoencephalography, and functional MRI to investigate how human listeners discover temporal patterns and statistical regularities in complex sound sequences. Sensitivity to patterns is fundamental to sensory processing, in particular in the auditory system, because most auditory signals only have meaning as successions over time. Previous evidence suggests that the brain is tuned to the statistics of sensory stimulation. However, the process through which this arises has been elusive. We demonstrate that listeners are remarkably sensitive to the emergence of complex patterns within rapidly evolving sound sequences, performing on par with an ideal observer model. Brain responses reveal online processes of evidence accumulationdynamic changes in tonic activity precisely correlate with the expected precision or predictability of ongoing auditory input-both in terms of deterministic (first-order) structure and the entropy of random sequences. Source analysis demonstrates an interaction between primary auditory cortex, hippocampus, and inferior frontal gyrus in the process of discovering the regularity within the ongoing sound sequence. The results are consistent with precision based predictive coding accounts of perceptual inference and provide compelling neurophysiological evidence of the brain's capacity to encode high-order temporal structure in sensory signals.A ccumulating work suggests that the brain is sensitive to statistical regularities in sensory input, at multiple time scales (1-9). The auditory system has been a useful testbed to investigate these processes (2, 3, 9-13), largely due to the vantage point provided by the mismatch negativity (MMN) paradigm (12, 13). The MMN is an auditory-evoked response generated by sounds violating some regular aspect of the prior sequence and is hypothesized to reflect a discrepancy between the memory trace, or expectations, generated by the standard stimulus, and the deviant information (12,13). A large body of MMN work has demonstrated that listeners are sensitive to the violation of a variety of acoustic sequences, including very complex regularities (14, 15), and interpreted as indirect evidence for exquisite sensitivity to patterns in sound.Due to the physical constraints that characterize animate objects in the environment, sounds emanating from those sources are usually statistically regular and often repetitive (e.g., flapping wings and locomotion sounds). The ability to discover regularities within the sensory input is therefore a critical aspect of scene analysis: providing the anchor that enables an observer to identify and track a behaviorally relevant signal from within the brouhaha of a busy scene. Detecting temporally recurrent auditory features enables listeners to recognize auditory objects (because most auditory signals only have meaning as patterns over time), but also to form rules, or models, that characterize the past and expected behavior of objects within the environment (4, 16). Indeed, experimental work demonstrat...

Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. While proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modeling studies of auditory pattern processing. For the first two assumptions - that neural responses are shaped by expectations and that these expectations are hierarchically organized - animal and human studies provide compelling evidence. The anticipatory, predictive nature of these expectations also enjoys empirical support, especially from studies on unexpected stimulus omission. However, for the existence of separate error and prediction neurons, a key assumption of the theory, evidence is lacking. More work exists on the proposed oscillatory signatures of predictive coding, and on the relation between attention and precision. However, results on these latter two assumptions are mixed or contradictory. Looking to the future, more collaboration between human and animal studies, aided by model-based analyses will be needed to test specific assumptions and implementations of predictive coding - and, as such, help determine whether this popular grand theory can fulfill its expectations.

In a functional magnetic resonance imaging experiment, aimed at investigating preattentive, stimulus-driven, auditory segregation mechanisms, naive subjects listened to these stimuli while performing an irrelevant task. Results demonstrate significant activations in the intraparietal sulcus (IPS) and the superior temporal sulcus related to bottom-up, stimulus-driven figure-ground decomposition. We did not observe any significant activation in the primary auditory cortex. Our results support a role for automatic, bottom-up mechanisms in the IPS in mediating stimulus-driven, auditory figure-ground segregation, which is consistent with accumulating evidence implicating the IPS in structuring sensory input and perceptual organization.

In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention.This article is part of the themed issue ‘Auditory and visual scene analysis’.

To make sense of natural acoustic environments, listeners must parse complex mixtures of sounds that vary in frequency, space, and time. Emerging work suggests that, in addition to the well-studied spectral cues for segregation, sensitivity to temporal coherence—the coincidence of sound elements in and across time—is also critical for the perceptual organization of acoustic scenes. Here, we examine pre-attentive, stimulus-driven neural processes underlying auditory figure-ground segregation using stimuli that capture the challenges of listening in complex scenes where segregation cannot be achieved based on spectral cues alone. Signals (“stochastic figure-ground”: SFG) comprised a sequence of brief broadband chords containing random pure tone components that vary from 1 chord to another. Occasional tone repetitions across chords are perceived as “figures” popping out of a stochastic “ground.” Magnetoencephalography (MEG) measurement in naïve, distracted, human subjects revealed robust evoked responses, commencing from about 150 ms after figure onset that reflect the emergence of the “figure” from the randomly varying “ground.” Neural sources underlying this bottom-up driven figure-ground segregation were localized to planum temporale, and the intraparietal sulcus, demonstrating that this area, outside the “classic” auditory system, is also involved in the early stages of auditory scene analysis.”

In contrast to the complex acoustic environments we encounter everyday, most studies of auditory segregation have used relatively simple signals. Here, we synthesized a new stimulus to examine the detection of coherent patterns (‘figures’) from overlapping ‘background’ signals. In a series of experiments, we demonstrate that human listeners are remarkably sensitive to the emergence of such figures and can tolerate a variety of spectral and temporal perturbations. This robust behavior is consistent with the existence of automatic auditory segregation mechanisms that are highly sensitive to correlations across frequency and time. The observed behavior cannot be explained purely on the basis of adaptation-based models used to explain the segregation of deterministic narrowband signals. We show that the present results are consistent with the predictions of a model of auditory perceptual organization based on temporal coherence. Our data thus support a role for temporal coherence as an organizational principle underlying auditory segregation.DOI: http://dx.doi.org/10.7554/eLife.00699.001

We use psychophysics and MEG to test how sensitivity to input statistics facilitates auditory-scene-analysis (ASA). Human subjects listened to ‘scenes’ comprised of concurrent tone-pip streams (sources). On occasional trials a new source appeared partway. Listeners were more accurate and quicker to detect source appearance in scenes comprised of temporally-regular (REG), rather than random (RAND), sources. MEG in passive listeners and those actively detecting appearance events revealed increased sustained activity in auditory and parietal cortex in REG relative to RAND scenes, emerging ~400 ms of scene-onset. Over and above this, appearance in REG scenes was associated with increased responses relative to RAND scenes. The effect of temporal structure on appearance-evoked responses was delayed when listeners were focused on the scenes relative to when listening passively, consistent with the notion that attention reduces ‘surprise’. Overall, the results implicate a mechanism that tracks predictability of multiple concurrent sources to facilitate active and passive ASA.DOI: http://dx.doi.org/10.7554/eLife.19113.001

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