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Randomized Controlled Trial
. 2019 Oct 1;19(12):12.
doi: 10.1167/19.12.12.

Trained-feature-specific offline learning by sleep in an orientation detection task

Masako Tamaki  1 , Zhiyan Wang  1 , Takeo Watanabe  1 , Yuka Sasaki  1
Affiliations
Randomized Controlled Trial

Trained-feature-specific offline learning by sleep in an orientation detection task

Masako Tamaki et al. J Vis. .

Abstract

Training-induced performance gains in a visual perceptual learning (VPL) task that take place during sleep are termed "offline performance gains." Offline performance gains of VPL so far have been reported in the texture discrimination task and other discrimination tasks. This raises the question as to whether offline performance gains on VPL occur exclusively in discrimination tasks. The present study examined whether offline performance gains occur in detection tasks. In Experiment 1, subjects were trained on a Gabor orientation detection task. They were retested after a 12-hr interval, which included either nightly sleep or only wakefulness. Offline performance gains occurred only after sleep on the trained orientation, not on an untrained orientation. In Experiment 2, we tested whether offline performance gains in the detection task occur over a nap using polysomnography. Moreover, we tested whether sigma activity during non-rapid eye movement (NREM) sleep recorded from occipital electrodes, previously implicated in offline performance gains of the texture discrimination task, was associated with the degree of offline performance gains of the Gabor orientation detection task. We replicated offline performance gains on the trained orientation in the detection task over the nap. Sigma activity during NREM sleep was significantly larger in the occipital electrodes relative to control electrodes in correlation with offline performance gains. The results suggest that offline performance gains occur over the sleep period generally in VPL. Moreover, sigma activity in the occipital region during NREM sleep may play an important role in offline performance gains of VPL.

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Figures

Figure 1
Figure 1
Experimental designs and the Gabor orientation detection task. (A) Experiment 1. (B) Experiment 2. (C) Schematic illustration of one trial of the Gabor orientation detection task.
Figure 2
Figure 2
The mean performance improvement (± SEM) at the postinterval test session for the sleep and the wake groups in Experiment 1. See the main text for the results of ANOVA. Asterisks (**) indicate that post hoc t tests (one sample t test and a paired t test) showed significance at p < 0.01. An FDR correction was applied (see the main text for details).
Figure 3
Figure 3
The mean performance improvement (± SEM) at the post interval test session for Experiment 2. N = 9. Paired and one-sample t tests, **p < 0.01; *p < 0.05. See the main text for additional details of the statistical results.
Figure 4
Figure 4
Correlation between offline performance gains and (A) region-specific sigma activity and (B) sigma activity in the control electrodes during NREM sleep. N = 9. *p < 0.05. No outliers were detected by Grubbs' test.
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