Automatic detection of rapid eye movements (REMs): A machine learning approach.

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Automatic detection of rapid eye movements (REMs): A machine learning approach.

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2015 nî lūn-bûn

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2015年の論文

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2015年学术文章

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2015年学术文章

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2015年学术文章

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2015年学术文章

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2015年学术文章

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2015年學術文章

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Automatic detection of rapid eye movements (REMs): A machine learning approach.

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Automatic detection of rapid eye movements

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Automatic detection of rapid eye movements (REMs): A machine learning approach.

@en

Automatic detection of rapid eye movements

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Automatic detection of rapid eye movements (REMs): A machine learning approach.

@en

Automatic detection of rapid eye movements

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P1476

Automatic detection of rapid eye movements (REMs): A machine learning approach.

@en

P2093

Benjamin D Yetton

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Elizabeth A McDevitt

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Lauren N Whitehurst

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Mohammad Niknazar

http://www.w3.org/2001/XMLSchema#string

Negin Sattari

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P2860

REM, not incubation, improves creativity by priming associative networks

Automatic REM detection: modifications on an existing system and preliminary normative data.

fMRI evidence for multisensory recruitment associated with rapid eye movements during sleep.

Donepezil-induced REM sleep augmentation enhances memory performance in elderly, healthy persons.

Daytime naps, motor memory consolidation and regionally specific sleep spindles.

Sleep-dependent learning: a nap is as good as a night.

Regularly occurring periods of eye motility, and concomitant phenomena, during sleep.

A functional role for REM sleep in brain maturation.

Sleep-dependent memory consolidation.

Posttraining increases in REM sleep intensity implicate REM sleep in memory processing and provide a biological marker of learning potential

P304

72-82

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P31

scholarly article

P356

10.1016/J.JNEUMETH.2015.11.015

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P478

259

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P50

Sara C Mednick

Katherine A Duggan

P577

2015-11-28T00:00:00Z

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P5875

285043257

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P698

26642967

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P921

automation

machine learning

P932

5310222

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