A growing body of research shows that sleep facilitates the consolidation of memories. For example, the number of sleep spindles (transient neural events in non-rapid eye movement (NREM) sleep, 9-15 Hz) in a post-training sleep period correlates with the magnitude of declarative memory improvement (e.g., conscious, episodic memories), whereas minutes in REM sleep correlate with improvement in non-declarative memories (e.g., unconscious, perceptual or sensorimotor skills). Although these studies report that individual sleep features correlate with improvement in specific memory domains, we do not know if manipulating these sleep features will lead to changes in these precise memory domains. The central aim of this application is to use pharmacological intervention to address the specificity of sleep-dependent memory with respect to 1) sleep feature (i.e., sleep spindles vs. other sleep features), 2) memory domain (i.e. declarative vs. non-declarative), and 3) pharmacological agents (i.e., zolpidem (ZOL) vs. sodium oxybate (SO) vs. placebo). Establishing a link between correlational sleep studies and pharmacological interventions that target precise memory domains will advance our long-term goal of developing pharmacological treatments for memory impairments. We hypothesize that increasing spindles with ZOL will improve declarative, but not non-declarative memory, and decreasing spindles with SO will reduce declarative memory. Strong preliminary data demonstrate the feasibility of the project aim's in the applicant's hands. First, preliminary data from the PI's K01 demonstrates successful pharmacological modulation of sleep spindles (i.e., increased with ZOL and decreased with SO, vs. placebo); and second, pilot data shows that pharmacologically modulating sleep spindles does affect memory performance. Results of our pharmacological intervention on sleep-dependent memory consolidation in healthy young subjects will be leveraged to develop novel treatment approaches for older adults with pharmacologically tailored sleep. Outcomes from these studies will lead to future translational interventions in populations with more severe memory impairment (e.g., dementia and Alzheimer's patients). A compelling observation supports our approach: along with hallmark impairments in declarative memory, older adults and patients with dementia and Alzheimer's also have deteriorated sleep, including a reduced number of sleep spindles. Furthermore, older adults do not appear to benefit from sleep-dependent consolidation as much as younger adults. Yet, cognitive aging treatment strategies do not address the possibility of improving or tailoring sleep to reverse these memory impairments. The proposed studies investigate the hypothesis that pharmacologically boosting sleep spindles in older adults will improve declarative memory, compared with non-declarative memory and placebo. Outcomes of studies will have broad impact given 1) that over 70 million people in the U.S. suffer from disordered sleep at an annual cost of $150 billion; 2) the need to improve treatments for cognitive aging as well as the 5.5 million Americans affected by Alzheimer's at a cost of $200 billion annually; and 3) that improved mechanistic understanding of memory can influence education that costs $1 trillion annually.

Public Health Relevance

The proposed research will serve the mission of the National Institutes of Health by expanding the basic science knowledge of memory and in investigating translational approaches to prevention and treatment of conditions that impact memory in clinical and at risk populations (e.g., older adults, dementia and Alzheimer's patients). We will use a widely prescribed drug, zolpidem (Ambien), which is used to treat some of the 70 million Americans that experience abnormal sleep. The results of these studies will allow us to examine the role of drugs on sleep and memory in human subjects that have previously only been carried out in animal models.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG046646-03
Application #
8989514
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Mackiewicz, Miroslaw
Project Start
2014-01-01
Project End
2018-12-31
Budget Start
2016-01-15
Budget End
2016-12-31
Support Year
3
Fiscal Year
2016
Total Cost
$280,440
Indirect Cost
$95,940
Name
University of California Riverside
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
627797426
City
Riverside
State
CA
Country
United States
Zip Code
92521
McDevitt, Elizabeth A; Sattari, Negin; Duggan, Katherine A et al. (2018) The impact of frequent napping and nap practice on sleep-dependent memory in humans. Sci Rep 8:15053
Schapiro, Anna C; McDevitt, Elizabeth A; Rogers, Timothy T et al. (2018) Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance. Nat Commun 9:3920
Duggan, Katherine A; McDevitt, Elizabeth A; Whitehurst, Lauren N et al. (2018) To Nap, Perchance to DREAM: A Factor Analysis of College Students' Self-Reported Reasons for Napping. Behav Sleep Med 16:135-153
Baker, Fiona C; Sattari, Negin; de Zambotti, Massimiliano et al. (2018) Impact of sex steroids and reproductive stage on sleep-dependent memory consolidation in women. Neurobiol Learn Mem :
Ahmadi, Maryam; McDevitt, Elizabeth A; Silver, Michael A et al. (2018) Perceptual learning induces changes in early and late visual evoked potentials. Vision Res 152:101-109
Obradovich, Nick; Migliorini, Robyn; Mednick, Sara C et al. (2017) Nighttime temperature and human sleep loss in a changing climate. Sci Adv 3:e1601555
Schapiro, Anna C; McDevitt, Elizabeth A; Chen, Lang et al. (2017) Sleep Benefits Memory for Semantic Category Structure While Preserving Exemplar-Specific Information. Sci Rep 7:14869
Cellini, Nicola; McDevitt, Elizabeth A; Mednick, Sara C et al. (2016) Response to the letter to the editor from Dr. Kawada, ""Comparison of two accelerometers for monitoring sleep: Agreement and validity"". Physiol Behav 163:333
Whitehurst, Lauren N; Cellini, Nicola; McDevitt, Elizabeth A et al. (2016) Autonomic activity during sleep predicts memory consolidation in humans. Proc Natl Acad Sci U S A 113:7272-7
Yetton, Benjamin D; Niknazar, Mohammad; Duggan, Katherine A et al. (2016) Automatic detection of rapid eye movements (REMs): A machine learning approach. J Neurosci Methods 259:72-82

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