The extent to which the sleeping brain processes sensory information remains unclear. This is particularly true for continuous and complex stimuli such as speech, in which information is organized into hierarchically embedded structures. Recently, novel metrics for assessing the neural representation of continuous speech have been developed using noninvasive brain recordings that have thus far only been tested during wakefulness. Here we investigated, for the first time, the sleeping brain's capacity to process continuous speech at different hierarchical levels using a newly developed Concurrent Hierarchical Tracking (CHT) approach that allows monitoring the neural representation and processing-depth of continuous speech online. Speech sequences were compiled with syllables, words, phrases, and sentences occurring at fixed time intervals such that different linguistic levels correspond to distinct frequencies. This enabled us to distinguish their neural signatures in brain activity. We compared the neural tracking of intelligible versus unintelligible (scrambled and foreign) speech across states of wakefulness and sleep using high-density EEG in humans. We found that neural tracking of stimulus acoustics was comparable across wakefulness and sleep and similar across all conditions regardless of speech intelligibility. In contrast, neural tracking of higher-order linguistic constructs (words, phrases, and sentences) was only observed for intelligible speech during wakefulness and could not be detected at all during nonrapid eye movement or rapid eye movement sleep. These results suggest that, whereas low-level auditory processing is relatively preserved during sleep, higher-level hierarchical linguistic parsing is severely disrupted, thereby revealing the capacity and limits of language processing during sleep. Despite the persistence of some sensory processing during sleep, it is unclear whether high-level cognitive processes such as speech parsing are also preserved. We used a novel approach for studying the depth of speech processing across wakefulness and sleep while tracking neuronal activity with EEG. We found that responses to the auditory sound stream remained intact; however, the sleeping brain did not show signs of hierarchical parsing of the continuous stream of syllables into words, phrases, and sentences. The results suggest that sleep imposes a functional barrier between basic sensory processing and high-level cognitive processing. This paradigm also holds promise for studying residual cognitive abilities in a wide array of unresponsive states.

Dynamic attending theory suggests that predicting the timing of upcoming sounds can assist in focusing attention toward them. However, whether similar predictive processes are also applied to background noises and assist in guiding attention “away” from potential distractors, remains an open question. Here we address this question by manipulating the temporal predictability of distractor sounds in a dichotic listening selective attention task. We tested the influence of distractors’ temporal predictability on performance and on the neural encoding of sounds, by comparing the effects of Rhythmic versus Nonrhythmic distractors. Using magnetoencephalography we found that, indeed, the neural responses to both attended and distractor sounds were affected by distractors’ rhythmicity. Baseline activity preceding the onset of Rhythmic distractor sounds was enhanced relative to nonrhythmic distractor sounds, and sensory response to them was suppressed. Moreover, detection of nonmasked targets improved when distractors were Rhythmic, an effect accompanied by stronger lateralization of the neural responses to attended sounds to contralateral auditory cortex. These combined behavioral and neural results suggest that not only are temporal predictions formed for task-irrelevant sounds, but that these predictions bear functional significance for promoting selective attention and reducing distractibility.

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Bisexual people suffer from stereotypes and negative attitudes. The authors investigated one possible explanation for this bi-negativity: that bisexuality, being nonmonosexual, challenges the deep-rooted dichotomous gender construct. Sixty-two participants were randomly assigned to read one of two vignettes: One blurred gender differences, the other emphasized them. Results showed first that there was greater bi-negativity among men compared to women. Among participants who were not personally acquainted with bisexuals, those in the blurring condition displayed less bi-negativity than those in the emphasizing condition. Findings suggest that the binary gender construct can indeed interfere with acceptance of bisexuals. This, in turn, suggests a way to reduce bi-negativity and thus may prove beneficial in improving the well-being of the bisexual community.

Dynamic Attending Theory suggests that predicting the timing of upcoming sounds can assist in focusing attention towards them. However, whether similar predictive processes are also applied to background noises and assist in guiding attention away from potential distractors, remains an open question.Here we address this question by manipulating the temporal predictability of distractor sounds in a dichotic listening selective attention task. We tested the influence of distractors' temporal predictability on performance and on the neural encoding of sounds, by comparing the effects of Rhythmic vs. Nonrhythmic distractors. Using Magnetoencephalography (MEG) we found that, indeed, the neural responses to both attended and distractor sounds were affected by distractors' rhythmicity. Baseline activity preceding the onset of Rhythmic distractor sounds was enhanced relative to Non-rhythmic distractor sounds, and sensory response were suppressed. Moreover, when distractors were Rhythmic, responses to attended sounds were more strongly lateralized to the contra-lateral hemisphere. Behavioral performance also improved in the Rhythmic condition. These combined behavioral and neural results suggest that not only are temporal predictions formed for task-irrelevant sounds, but that these predictions bear functional significance for promoting selective attention and reducing distractibility.