In the present study, we investigate how lexicality affects the processing of suprasegmental features at the word level. In contrast to earlier studies which analyzed the role of either segmental or suprasegmental feature in language processing our aim was to investigate the effect of the lexical status on the processing of violated stress pattern defined by linguistic rules. We have conducted a passive oddball ERP experiment, presenting a frequent CVCV word with legal (familiar) and illegal (unfamiliar) stress patterns. Former results obtained with pseudo-words in a similar paradigm enabled to assess the influence of lexical information on stress processing. The presence of lexically relevant information resulted in different ERP patterns compared to those obtained with pseudo-words. We obtained two consecutive MMN responses to the illegally stressed words while violating the illegal stress pattern with a legal one the deviant stimulus elicited two consecutive MMN responses as well. In the latter condition lexicality clearly enhanced the comparison of prosodic information between standard and deviant stimuli, as these components very completely missing when presenting pseudo-words. We interpret the results that lexicality acts as a filter since in the absence of lexical familiarity unfamiliar stress patterns are discriminated better. Our results highlight that even when stress is fully predictable, it is taken into account during pre-attentive processing of linguistic input.

The neural substrates by which speech sounds are perceptually segregated into distinct streams are poorly understood. Here, we recorded high-density scalp event-related potentials (ERPs) while participants were presented with a cyclic pattern of three vowel sounds (/ee/-/ae/-/ee/). Each trial consisted of an adaptation sequence, which could have either a small, intermediate, or large difference in first formant (Δf1) as well as a test sequence, in which Δf1 was always intermediate. For the adaptation sequence, participants tended to hear two streams (“streaming”) when Δf1 was intermediate or large compared to when it was small. For the test sequence, in which Δf1 was always intermediate, the pattern was usually reversed, with participants hearing a single stream with increasing Δf1 in the adaptation sequences. During the adaptation sequence, Δf1-related brain activity was found between 100–250 ms after the /ae/ vowel over fronto-central and left temporal areas, consistent with generation in auditory cortex. For the test sequence, prior stimulus modulated ERP amplitude between 20–150 ms over left fronto-central scalp region. Our results demonstrate that the proximity of formants between adjacent vowels is an important factor in the perceptual organization of speech, and reveal a widely distributed neural network supporting perceptual grouping of speech sounds.

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The efficient coding hypothesis postulates that neurons shape their response properties to match their dynamic range to the statistics of incoming signals. However, whether and how the dynamics of efficient neuronal adaptation inform behavior has not been directly shown. Here, we trained mice to detect a target presented in background noise shortly after a change in the background contrast. The observed changes in cortical gain and detection behavior followed the predictions of a normative model of efficient cortical sound processing; specifically, target detection and sensitivity to target volume improved in low contrast backgrounds relative to high contrast backgrounds. Additionally, the time course of target detectability adapted asymmetrically depending on contrast, decreasing rapidly after a transition to high contrast, and increasing more slowly after a transition to low contrast. Auditory cortex was required for detection of targets in background noise and cortical neuronal responses exhibited the patterns of target detectability observed during behavior and in the normative model. Furthermore, variability in cortical gain predicted behavioral performance beyond the effect of stimulus-driven gain control. Combined, our results demonstrate that efficient neural codes in auditory cortex directly influence perceptual behavior.