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While asleep, people heard sounds that had earlier been associated with objects at specific spatial locations. Upon waking, they recalled these locations more accurately than other locations for which no reminder cues were provided. Consolidation thus operates during sleep with high specificity and is subject to systematic influences through simple auditory stimulation.Initially fragile memories can gain stability via consolidation, but the extent to which sleep contributes to this process is unresolved (1,2). Sleep between encoding and retrieval, relative to wakefulness, promotes memory storage in some circumstances, perhaps from internally generated memory reactivation (3,4). Moreover, reinstating a learning context (an odor) during slow-wave sleep enhances retrieval of spatial information learned in that context (5). It remains unclear whether exposure during sleep to cues associated with newly learned information can selectively enhance the storage of individual memories.We taught people to associate each of 50 unique object images with a location on a computer screen prior to a nap (Fig. 1A). Each object was paired with a characteristic sound delivered over a speaker (e.g., cat/meow, kettle/whistle). For the entirety of the nap, white noise was presented at an unobtrusive intensity (~62dB sound-pressure level), and during non-REM sleep the sounds for 25 of the objects were presented, with white-noise intensity lowered so that overall levels were approximately constant (Fig. 1B).After waking, individuals viewed all 50 objects and attempted to position each one in its original location. Absolute distance measures showed that object placements were more accurate for objects that were cued by their sounds during sleep than for those not cued (1.07 cm ± 0.08 SE vs. 1.23 cm ± 0.10 SE, respectively, t 11 = 2.6, p < .05). Forgetting occurred between the final stage of learning and the post-nap test, with a smaller decline for cued compared to uncued objects (Fig. 1C). An advantage for cued-object locations computed in this manner was evident in 10 of the 12 participants.EEG recordings provided information for determining sleep stages (6). Additionally, EEG responses to sound cues were sorted into 2 conditions via a median split on the difference between pre-and post-nap accuracy: (1) in the less-forgetting condition, mean accuracy was superior post-nap (placements 0.51 cm ± 0.1 cm SE closer to correct); (2) in the moreforgetting condition, mean accuracy was superior pre-nap (placements 0.60 cm ± 0.1 cm SE farther from correct). Average EEG amplitudes measured over the interval from 600-1000 ms after sound onset were 15.3 μV greater when there was less forgetting (t 11 = 3.2, p < .

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Information acquired during waking can be reactivated during sleep, promoting memory stabilization. After people learned to produce two melodies in time with moving visual symbols, we produced a relative improvement in performance by presenting one melody during an afternoon nap. Electrophysiological signs of memory processing during sleep corroborated the notion that appropriate auditory stimulation that does not disrupt sleep can nevertheless bias memory consolidation in relevant brain circuitry.

The stability of long-term memories is enhanced by reactivation during sleep. Correlative evidence has linked memory reactivation with thalamocortical sleep spindles, although their functional role is not fully understood. Our initial study replicated this correlation and also demonstrated a novel rhythmicity to spindles, such that a spindle is more likely to occur approximately 3-6 s following a prior spindle. We leveraged this rhythmicity to test the role of spindles in memory by using real-time spindle tracking to present cues within versus just after the presumptive refractory period; as predicted, cues presented just after the refractory period led to better memory. Our findings demonstrate a precise temporal link between sleep spindles and memory reactivation. Moreover, they reveal a previously undescribed neural mechanism whereby spindles may segment sleep into two distinct substates: prime opportunities for reactivation and gaps that segregate reactivation events.

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning.

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