Nguyen ND; Tucker MA; Stickgold R; Wamsley EJ. Overnight sleep enhances hippocampus-dependent aspects of spatial memory. 2013;36(7):1051-1057.

Post-learning sleep is beneficial for human memory. However, it may be that not all memories benefit equally from sleep. Here, we manipulated a spatial learning task using monetary reward and performance feedback, asking whether enhancing the salience of the task would augment overnight memory consolidation and alter its incorporation into dreaming. Contrary to our hypothesis, we found that the addition of reward impaired overnight consolidation of spatial memory. Our findings seemingly contradict prior reports that enhancing the reward value of learned information augments sleep-dependent memory processing. Given that the reward followed a negative reinforcement paradigm, consolidation may have been impaired via a stress-related mechanism.

The smooth, coordinated fine motor movements required to play a musical instrument are not only highly valued in our society; they also predict academic success in areas that generalize beyond the motor domain, including reading and math readiness, and verbal abilities. Interestingly, motor skills that overlap with those required to play a musical instrument (e.g., sequential finger tapping) markedly improve (get faster) over a night of sleep, but not after a day spent awake. Here we studied whether individuals who play musical instruments that require fine finger motor skill are better able to learn and consolidate a simple motor skill task compared to those who do not play an instrument, and whether sleep-specific motor skill benefits interact with those imparted by musical experience. We used the motor sequence task (MST), which taps into a core skill learned and used by musicians, namely, the repetition of learned sequences of key presses. Not surprisingly, we found that musicians were faster than non-musicians throughout the learning session, typing more correct sequences per 30-sec trial. In the 12hrs that followed learning we found that sleep and musical experience both led to greater improvement in performance. Surprisingly, musicians retested after a day of wake performed slightly better than non-musicians who had slept between training and retest, suggesting that musicians have the capacity to consolidate a motor skill across waking hours, while non-musicians appear to lack this capacity. These findings suggest that the musically trained brain is optimized for motor skill consolidation across both wake and sleep, and that sleep may simply promote a more effective use of this machinery. In sum, there may be something special about musicians, perhaps a neurophysiological advantage, that leads to both the expected—greater motor speed at learning—and the surprising—greater motor skill improvement over time.

Interindividual variations in the ability to perform visuospatial mental transformations have been investigated extensively, in particular through mental rotation tasks. However, the impact of early visual processes on performance has been largely ignored. To clarify this issue, we explored the time-course of early visual processing (from 0 to 450 ms poststimulus) using event-related potentials topographic analyses.

Sleep impairment significantly alters human brain structure and cognitive function, but available evidence suggests that adults in developed nations are sleeping less. A growing body of research has sought to use sleep to forecast cognitive performance by modeling the relationship between the two, but has generally focused on vigilance rather than other cognitive constructs affected by sleep, such as reaction time, executive function, and working memory. Previous modeling efforts have also utilized subjective, self-reported sleep durations and were restricted to laboratory environments. In the current effort, we addressed these limitations by employing wearable systems and mobile applications to gather objective sleep information, assess multi-construct cognitive performance, and model/predict changes to mental acuity. Thirty participants were recruited for participation in the study, which lasted 1 week. Using the Fitbit Charge HR and a mobile version of the automated neuropsychological assessment metric called CogGauge, we gathered a series of features and utilized the unified model of performance to predict mental acuity based on sleep records. Our results suggest that individuals poorly rate their sleep duration, supporting the need for objective sleep metrics to model circadian changes to mental acuity. Participant compliance in using the wearable throughout the week and responding to the CogGauge assessments was 80%. Specific biases were identified in temporal metrics across mobile devices and operating systems and were excluded from the mental acuity metric development. Individualized prediction of mental acuity consistently outperformed group modeling. This effort indicates the feasibility of creating an individualized, mobile assessment and prediction of mental acuity, compatible with the majority of current mobile devices.