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Working memory (WM) is engaged in most cognitive tasks deployed in the human brain . Braintraining regimens that target WM may promote plasticity, leading to improved WM skills . Additionally, sleep is known to facilitate consolidation of newly learned information and skills . Here, we asked if napping could boost benefits of brain-training for WM. Participants completed ten days of WM training on an N-back task; on each training day, a subset of participants were given a 30-minute nap opportunity (with EEG recording) immediately following their training session (training+nap) . In Study 1 (n=10), we equated the amount of training (20-min training/day) in all participants and compared training only to training+nap . In Study 2 (n=8), we asked if napping can effectively replace additional time spent training; we compared training+nap (20-min training/day) to double training (40-min training/day) . On average, the nap group slept 16 .0±5 .77 minutes/nap in Study 1 and 15 .98±7 .44 minutes/nap in Study 2 . Our dependent measure of performance was the highest N-level achieved on each day of training .In both studies, we found that performance improved across the ten days of the study . However, there was no day x group interaction in either study, suggesting that the degree of improvement did not differ between training only vs . training+nap groups . In Study 2, there was a trend towards more improvement with double training compared to single training+nap . For people looking to dedicate time each day to improving their WM, it may be more beneficial to spend the entire time training rather than training+napping .

Streaming services provide people with a seemingly infinite set of entertainment choices. This large set of options makes the decision to view alternative content or stop consuming content altogether compelling. Yet, nearly all experimental studies of the attributes of video content and their ability to influence behavior require that participants view stimuli in their entirety. The present study measured neurophysiologic responses while participants viewed videos with the option to stop viewing without penalty in order to identify signals that capture the neural value of content. A post-video behavioral choice was included to reduce the likelihood that measured neurophysiologic responses were noise rather than signal. We found that a measure derived from neurophysiologic Immersion predicted how long participants would watch a video. Further, the time spent watching a video increased the likelihood that it influenced behavior. The analysis indicates that the neurologic value one receives helps explain why people continue to watch videos and why they are influenced by them.

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