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| ID | Type | Description | Link |
|---|---|---|---|
| 16-N-0031 |
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Background:
An electroencephalogram (EEG) measures the brain s electrical activity. EEG shows that the louder the sound needed to wake a person, the deeper the person s sleep. Researchers are using functional magnetic resonance imaging (fMRI) to study people during sleep so they can view brain activity in 3D. But they still need to correlate fMRI with sound thresholds, like the EEG.
Objective:
To measure brain activity during sleep using fMRI and EEG.
Eligibility:
Healthy people ages 18 34 who can sleep on their back for several hours.
Design:
Participants will be screened online about their sleep and general health.
At a screening visit, participants will have:
Physical exam
Hearing exam
MRI scan. A strong magnetic field and radio waves take pictures of the brain. Participants will lie down on a bed that slides into the scanner, which is shaped like a cylinder.
Participants will wear an actigraph on their wrist that records their motor activity.
Participants will follow a 2-week routine. This includes regular in-to-bed and out-of-bed times and limits on alcohol, caffeine, and nicotine.
During the overnight visits, participants will have:
Female subjects will have a urine pregnancy test.
fMRI. A coil will be placed over the head. Participants will do tasks shown on a computer screen inside the scanner.
EEG. Small electrodes on the scalp will record brain waves while sleeping or doing a task in the scanner.
Participants will be asked to try to sleep while researchers collect fMRI and EEG data. Participants eyes will be monitored with a video camera. Headphones will deliver sounds to wake them up throughout the night.
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Objective
Electroencephalography is generally considered the gold standard for defining sleep, but, in fact, sleep is a behavior and is defined by widely accepted behavioral characteristics like auditory arousal threshold. Electroencephalography merely became a surrogate for the behavioral definition when, in the first electroencephalographic sleep studies, researchers discovered a strong correlation between electroencephalographic slow waves and auditory arousal thresholds. With the advent of functional magnetic resonance imaging, one would expect the first sleep studies that used this new measure would have been designed to correlate it with auditory arousal threshold. However, these studies have never been conducted. This protocol will fill this gap in the literature. We hypothesize that undiscovered patterns of brain activity or functional connectivity exist during sleep and that an approach that defines sleep behaviorally will expose these patterns.
Study Population
The subject group in this study will be young, healthy individuals with excellent sleep health. Choosing this subject group will maximize the probability that subjects will sleep during all-night functional magnetic resonance imaging. Our target number of completers was 12 for the pilot study, was 43 for the main study, and is 85 for the normative study.
Design
After a one-week home-monitoring period that includes a regular in-to-bed and out-of-bed time, subjects will undergo two all-night functional magnetic resonance imaging sleep studies separated by a one-week washout period with continued home monitoring. The first night will serve as an adaptation night, which is known to reduce the sleep alterations that accompany sleeping in a laboratory environment. We will measure sleep depth behaviorally by arousing subjects with auditory stimuli that progressively increase in intensity. This procedure will be performed approximately eight times per night. The timing of the arousals will be distributed randomly across the night.
Data Generated
The data generated will be auditory arousal thresholds and the preceding brain activity and functional connectivity derived from functional magnetic resonance imaging.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy Volunteers | Healthy volunteers, age 18-34. |
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| Measure | Description | Time Frame |
|---|---|---|
| The data generated will be auditory arousal thresholds and the preceding brain activity and functional connectivity derived from fMRI | Auditory arousal thresholds will allow us to define sleep depth behaviorally. | This outcome will be measured during Overnight Visit 1 and 2. |
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INCLUSION CRITERIA:
EXCLUSION CRITERIA:
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Volunteers will be recruited from the community and NIH employees.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Susan C Guttman | Contact | (301) 451-9912 | fultons@mail.nih.gov | |
| Jeffrey H Duyn, Ph.D. | Contact | (301) 594-7305 | duynjeff@ninds.nih.gov |
| Name | Affiliation | Role |
|---|---|---|
| Jeffrey H Duyn, Ph.D. | National Institute of Neurological Disorders and Stroke (NINDS) | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Institutes of Health Clinical Center | Recruiting | Bethesda | Maryland | 20892 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30243817 | Derived | Moehlman TM, de Zwart JA, Chappel-Farley MG, Liu X, McClain IB, Chang C, Mandelkow H, Ozbay PS, Johnson NL, Bieber RE, Fernandez KA, King KA, Zalewski CK, Brewer CC, van Gelderen P, Duyn JH, Picchioni D. All-night functional magnetic resonance imaging sleep studies. J Neurosci Methods. 2019 Mar 15;316:83-98. doi: 10.1016/j.jneumeth.2018.09.019. Epub 2018 Sep 20. |
| Label | URL |
|---|---|
| NIH Clinical Center Detailed Web Page | View source |
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