Anxiety sensitivity and daily cigarette smoking in relation to sleep disturbances in treatment-seeking smokers

ABSTRACT

Although the association between anxiety and sleep disturbance is well-documented, the underlying mechanisms are less clear. Anxiety sensitivity (AS), the fear of physiological arousal and bodily sensations, is a risk factor for anxiety and poor sleep. Smoking also contributes to poor sleep and may compound the effects of AS on sleep quality. This study evaluated the main and interactive effects of AS and cigarettes/day on sleep quality among smokers. Participants (n = 190) were adult treatment-seeking daily smokers who completed a baseline assessment as part of a larger smoking cessation trial. Sleep quality was self-reported. Results indicated that AS was significantly correlated with greater disturbance in sleep duration, subjective sleep quality, sleep onset latency, sleep disturbance, daytime dysfunction, and sleep medication use. There was a significant interaction between AS and cigarettes/day in terms of sleep onset latency, but not other sleep quality indices. AS was associated with significantly longer sleep onset latency minutes among heavier smokers, but not lighter smokers. Specifically, the association between AS and sleep onset latency was significant for those who smoked ≥ 33 cigarettes/day. AS is a psychological factor that may contribute to poor sleep quality, especially in heavy smokers, and thus may be a promising intervention target.     

Tracking transitional probabilities and segmenting auditory sequences are dissociable processes in adults and neonates

Since speech is a continuous stream with no systematic boundaries between words, how do pre-verbal infants manage to discover words? A proposed solution is that they might use the transitional probability between adjacent syllables, which drops at word boundaries. Here, we tested the limits of this mechanism by increasing the size of the word-unit to four syllables, and its automaticity by testing asleep neonates. Using markers of statistical learning in neonates’ EEG, compared to adult behavioral performances in the same task, we confirmed that statistical learning is automatic enough to be efficient even in sleeping neonates. We also revealed that: (1) Successfully tracking transition probabilities (TP) in a sequence is not sufficient to segment it. (2) Prosodic cues, as subtle as subliminal pauses, enable to recover words segmenting capacities. (3) Adults’ and neonates’ capacities to segment streams seem remarkably similar despite the difference of maturation and expertise. Finally, we observed that learning increased the overall similarity of neural responses across infants during exposure to the stream, providing a novel neural marker to monitor learning. Thus, from birth, infants are equipped with adult-like tools, allowing them to extract small coherent word-like units from auditory streams, based on the combination of statistical analyses and auditory parsing cues.

Research Highlights

• Successfully tracking transitional probabilities in a sequence is not always sufficient to segment it.
• Word segmentation solely based on transitional probability is limited to bi- or tri-syllabic elements.
• Prosodic cues, as subtle as subliminal pauses, enable to recover chunking capacities in sleeping neonates and awake adults for quadriplets.