Simple statistical regularities presented during sleep are detected but not retained

Abstract

In recent years, there has been growing interest and excitement over the newly discovered cognitive capacities of the sleeping brain, including its ability to form novel associations. These recent discoveries raise the possibility that other more sophisticated forms of learning may also be possible during sleep. In the current study, we tested whether sleeping humans are capable of statistical learning – the process of becoming sensitive to repeating, hidden patterns in environmental input, such as embedded words in a continuous stream of speech. Participants' EEG was recorded while they were presented with one of two artificial languages, composed of either trisyllabic or disyllabic nonsense words, during slow-wave sleep. We used an EEG measure of neural entrainment to assess whether participants became sensitive to the repeating regularities during sleep-exposure to the language. We further probed for long-term memory representations by assessing participants' performance on implicit and explicit tests of statistical learning during subsequent wake. In the disyllabic—but not trisyllabic—language condition, participants’ neural entrainment to words increased over time, reflecting a gradual gain in sensitivity to the embedded regularities. However, no significant behavioural effects of sleep-exposure were observed after the nap, for either language. Overall, our results indicate that the sleeping brain can detect simple, repeating pairs of syllables, but not more complex triplet regularities. However, the online detection of these regularities does not appear to produce any durable long-term memory traces that persist into wake – at least none that were revealed by our current measures and sample size. Although some perceptual aspects of statistical learning are preserved during sleep, the lack of memory benefits during wake indicates that exposure to a novel language during sleep may have limited practical value.