scholarly journals Reward does not facilitate visual perceptual learning until sleep occurs

2019 ◽  
Vol 117 (2) ◽  
pp. 959-968 ◽  
Author(s):  
Masako Tamaki ◽  
Aaron V. Berard ◽  
Tyler Barnes-Diana ◽  
Jesse Siegel ◽  
Takeo Watanabe ◽  
...  
Keyword(s):  
Perceptual Learning ◽  
Eye Movement ◽  
Rem Sleep ◽  
Visual Processing ◽  
Reward Processing ◽  
Rapid Eye Movement ◽  
Performance Gain ◽  
Reward Group ◽  
Visual Perceptual Learning ◽  
Performance Gains

A growing body of evidence indicates that visual perceptual learning (VPL) is enhanced by reward provided during training. Another line of studies has shown that sleep following training also plays a role in facilitating VPL, an effect known as the offline performance gain of VPL. However, whether the effects of reward and sleep interact on VPL remains unclear. Here, we show that reward interacts with sleep to facilitate offline performance gains of VPL. First, we demonstrated a significantly larger offline performance gain over a 12-h interval including sleep in a reward group than that in a no-reward group. However, the offline performance gains over the 12-h interval without sleep were not significantly different with or without reward during training, indicating a crucial interaction between reward and sleep in VPL. Next, we tested whether neural activations during posttraining sleep were modulated after reward was provided during training. Reward provided during training enhanced rapid eye movement (REM) sleep time, increased oscillatory activities for reward processing in the prefrontal region during REM sleep, and inhibited neural activation in the untrained region in early visual areas in non-rapid eye movement (NREM) and REM sleep. The offline performance gains were significantly correlated with oscillatory activities of visual processing during NREM sleep and reward processing during REM sleep in the reward group but not in the no-reward group. These results suggest that reward provided during training becomes effective during sleep, with excited reward processing sending inhibitory signals to suppress noise in visual processing, resulting in larger offline performance gains over sleep.

scholarly journals Reward does not facilitate visual perceptual learning until sleep occurs

2019 ◽  
Author(s):  
Masako Tamaki ◽  
Aaron V. Berard ◽  
Tyler Barnes-Diana ◽  
Jesse Siegel ◽  
Takeo Watanabe ◽  
...  
Keyword(s):  
Perceptual Learning ◽  
Rem Sleep ◽  
Visual Processing ◽  
Nrem Sleep ◽  
Reward Processing ◽  
Reward Group ◽  
Visual Perceptual Learning ◽  
Visual Areas ◽  
Prefrontal Region ◽  
Performance Gains

ABSTRACTA growing body of evidence indicates that visual perceptual learning (VPL) is enhanced by reward provided during training. Another line of studies has shown that sleep following training also plays a role in facilitating VPL, an effect known as the offline performance gain of VPL. However, whether the effects of reward and sleep interact on VPL remains unclear. Here, we show that reward interacts with sleep to facilitate offline performance gains of VPL. First, we demonstrated a significantly larger offline performance gain over a 12-h interval including sleep in a reward group than that in a No-reward group. However, the offline performance gains over the 12-h interval without sleep were not significantly different with or without reward during training, indicating a crucial interaction between reward and sleep in VPL. Next, we tested whether neural activations during posttraining sleep were modulated after reward was provided during training. Reward provided during training enhanced REM sleep time, increased oscillatory activities for reward processing in the prefrontal region during REM sleep, and inhibited neural activation in the untrained region in early visual areas in NREM and REM sleep. The offline performance gains were significantly correlated with oscillatory activities of visual processing during NREM sleep and reward processing during REM sleep in the reward group but not in the No-reward group. These results suggest that reward provided during training becomes effective during sleep, with excited reward processing sending inhibitory signals to suppress noise in visual processing, resulting in larger offline performance gains over sleep.Significance statementIndependent lines of research have shown that visual perceptual learning (VPL) is improved by reward or sleep. Here, we show that reward provided during training increased offline performance gains of VPL over sleep. Moreover, during posttraining sleep, reward was associated with longer REM sleep, increased activity in reward processing in the prefrontal region during REM sleep, and decreased activity in the untrained region of early visual areas during NREM and REM sleep. Offline performance gains were correlated with modulated oscillatory activity in reward processing during REM sleep and visual processing during NREM sleep. These results suggest that reward provided during training becomes effective on VPL through the interaction between reward and visual processing during sleep after training.

scholarly journals Sleep-dependent offline performance gain in visual perceptual learning is consistent with a learning-dependent model

2020 ◽  
Author(s):  
Masako Tamaki ◽  
Yuka Sasaki
Keyword(s):  
Perceptual Learning ◽  
Nrem Sleep ◽  
Wave Activity ◽  
Performance Gain ◽  
Learning Condition ◽  
Interference Condition ◽  
Visual Perceptual Learning ◽  
Visual Areas ◽  
Dependent Model ◽  
Performance Gains

SummaryAre the sleep-dependent offline performance gains of visual perceptual learning (VPL) consistent with a use-dependent or learning-dependent model? Here, we found that a use-dependent model is inconsistent with the offline performance gains in VPL. In two training conditions with matched visual usages, one generated VPL (learning condition), while the other did not (interference condition). The use-dependent model predicts that slow-wave activity (SWA) during posttraining NREM sleep in the trained region increases in both conditions, in correlation with offline performance gains. However, compared with those in the interference condition, sigma activity, not SWA, during NREM sleep and theta activity during REM sleep, source-localized to the trained early visual areas, increased in the learning condition. Sigma activity correlated with offline performance gain. These significant differences in spontaneous activity between the conditions suggest that there is a learning-dependent process during posttraining sleep for the offline performance gains in VPL.

scholarly journals The Relationship Between Daily Rapid-Eye Movement Sleep and Cognitive Functioning in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 159-159
Author(s):  
Tiana Broen ◽  
Tomiko Yoneda ◽  
Jonathan Rush ◽  
Jamie Knight ◽  
Nathan Lewis ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Cognitive Functioning ◽  
Eye Movement ◽  
Rem Sleep ◽  
Cognitive Tests ◽  
Rapid Eye Movement ◽  
Targeted Interventions ◽  
The Impact ◽  
The Relationship

Abstract Previous cross-sectional research suggests that age-related decreases in Rapid-Eye Movement (REM) sleep may contribute to poorer cognitive functioning (CF); however, few studies have examined the relationship at the intraindividual level by measuring habitual sleep over multiple days. Applying a 14-day daily diary design, the current study examines the dynamic relationship between REM sleep and CF in 69 healthy older adults (M age=70.8 years, SD=3.37; 73.9% female; 66.6% completed at least an undergraduate degree). A Fitbit device provided actigraphy indices of REM sleep (minutes and percentage of total sleep time), while CF was measured four times daily on a smartphone via ambulatory cognitive tests that captured processing speed and working memory. This research addressed the following questions: At the within-person level, are fluctuations in quantity of REM sleep associated with fluctuations in next day cognitive measures across days? Do individuals who spend more time in REM sleep on average, perform better on cognitive tests than adults who spend less time in REM sleep? A series of multilevel models were fit to examine the extent to which each index of sleep accounted for daily fluctuations in performance on next day cognitive tests. Results indicated that during nights when individuals had more REM sleep minutes than was typical, they performed better on the working memory task the next morning (estimate = -.003, SE = .002, p = .02). These results highlight the impact of REM sleep on CF, and further research may allow for targeted interventions for earlier treatment of sleep-related cognitive impairment.

Sleep Disorders

2015 ◽  
Author(s):  
Sudhansu Chokroverty
Keyword(s):  
Sleep Apnea ◽  
Sleep Disorders ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Apnea Syndrome ◽  
Nrem Sleep ◽  
Rapid Eye Movement ◽  
Circadian Rhythm Sleep Disorders ◽  
Apnea Syndrome ◽  
Sleep Mechanism

Recent research has generated an enormous fund of knowledge about the neurobiology of sleep and wakefulness. Sleeping and waking brain circuits can now be studied by sophisticated neuroimaging techniques that map different areas of the brain during different sleep states and stages. Although the exact biologic functions of sleep are not known, sleep is essential, and sleep deprivation leads to impaired attention and decreased performance. Sleep is also believed to have restorative, conservative, adaptive, thermoregulatory, and consolidative functions. This review discusses the physiology of sleep, including its two independent states, rapid eye movement (REM) and non–rapid eye movement (NREM) sleep, as well as functional neuroanatomy, physiologic changes during sleep, and circadian rhythms. The classification and diagnosis of sleep disorders are discussed generally. The diagnosis and treatment of the following disorders are described: obstructive sleep apnea syndrome, narcolepsy-cataplexy sydrome, idiopathic hypersomnia, restless legs syndrome (RLS) and periodic limb movements in sleep, circadian rhythm sleep disorders, insomnias, nocturnal frontal lobe epilepsy, and parasomnias. Sleep-related movement disorders and the relationship between sleep and psychiatric disorders are also discussed. Tables describe behavioral and physiologic characteristics of states of awareness, the international classification of sleep disorders, common sleep complaints, comorbid insomnia disorders, causes of excessive daytime somnolence, laboratory tests to assess sleep disorders, essential diagnostic criteria for RLS and Willis-Ekbom disease, and drug therapy for insomnia. Figures include polysomnographic recording showing wakefulness in an adult; stage 1, 2, and 3 NREM sleep in an adult; REM sleep in an adult; a patient with sleep apnea syndrome; a patient with Cheyne-Stokes breathing; a patient with RLS; and a patient with dream-enacting behavior; schematic sagittal section of the brainstem of the cat; schematic diagram of the McCarley-Hobson model of REM sleep mechanism; the Lu-Saper “flip-flop” model; the Luppi model to explain REM sleep mechanism; and a wrist actigraph from a man with bipolar disorder. This review contains 14 highly rendered figures, 8 tables, 115 references, and 5 MCQs.

scholarly journals REM Sleep Behavior Disorder (RBD) in Dementia with Lewy Bodies (DLB)

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Po-Chi Chan ◽  
Hsun-Hua Lee ◽  
Chien-Tai Hong ◽  
Chaur-Jong Hu ◽  
Dean Wu
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Dementia With Lewy Bodies ◽  
Clinical Manifestations ◽  
Lewy Bodies ◽  
Rem Sleep Behavior Disorder ◽  
Behavior Disorder ◽  
Rapid Eye Movement ◽  
Sleep Behavior ◽  
Neurologic Disorders

Rapid eye movement sleep behavior disorder (RBD) is a parasomnia, with abnormal dream-enacting behavior during the rapid eye movement (REM) sleep. RBD is either idiopathic or secondary to other neurologic disorders and medications. Dementia with Lewy bodies (DLB) is the third most common cause of dementia, and the typical clinical presentation is rapidly progressive cognitive impairment. RBD is one of the core features of DLB and may occur either in advance or simultaneously with the onset of DLB. The association between RBD with DLB is widely studied. Evidences suggest that both DLB and RBD are possibly caused by the shared underlying synucleinopathy. This review article discusses history, clinical manifestations, possible pathophysiologies, and treatment of DLB and RBD and provides the latest updates.

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