We remember little of what we commit to memory. What determine which memories will ultimately be retained, and the role of sleep-dependent memory consolidation in ensuring their retention, are unknown. The long-term goal is to understand how offline memory processing in wake and sleep interact to control what we remember and what we forget. The objective of the proposed research is to determine the impact of memory processing during post-encoding wake on sleep-dependent memory consolidation. The central hypothesis is that the strength and salience of recently formed memories lead to their modification in a manner that enhances the likelihood of their subsequent sleep-dependent consolidation. (The term """"""""memory modification during wake"""""""" (MMW) is used to denote processes during post-training wake that modulate the subsequent sleep-dependent consolidation of those memories.) It is further hypothesized that MMW facilitates sleep-dependent consolidation by triggering the reactivation of memories during sleep and by modulating the structure of sleep to enhance consolidation of the modified memories. The rationale for this research is that understanding how offline memory processing during wake interacts with sleep-dependent memory consolidation to determine what we ultimately remember will increase our understanding of the normal evolution of memories over time, and provide clues into how breakdowns in these processes and interactions contribute to the memory deficits associated with a range of psychiatric and neurologic disorders.
Three Specific Aims test this hypothesis: (i) Measure the impact of the strength and salience of newly formed memories on their retention across wake and sleep, expecting larger effects across sleep;(ii) Use functional connectivity (fc) MRI and high density (hd) EEG measures of memory related brain activity in post- encoding rest to quantify MMW, and correlate these measures with subsequent memory retention;and (iii) Determine the role of memory reactivation during specific sleep stages in mediating the effects of MMW on memory retention. Methods shown to manipulate memory strength and salience, as well as sleep stages and memory reactivation, will be used for Aims 1 and 3. Learning-related brain activity will be recorded during post-training quiet rest with hdEEG in Aims 1 and 3 and with fcMRI for Aim 2, and used to identify patterns of post-training brain activity that predict subsequent sleep-dependent memory retention. This approach is innovative because it represents the first attempt to produce an integrated description of the regulation of sleep-dependent memory processing across wake and sleep. This research is significant because it is can increase our knowledge of memory processing during both post-encoding wake and subsequent sleep. Gaining this knowledge is the first step toward identifying how breakdowns in these processes contribute to the memory dysfunction seen in psychiatric and neurologic disorders, and in developing treatments to reverse these breakdowns.
The proposed research is relevant to public health because the discovery of how the offline selection of memories during wake regulates subsequent sleep-dependent memory consolidation can allow discrimination between memory disorders due to failures of this selection process and others due to breakdowns in sleep-dependent memory consolidation. Such findings could lead to more effective treatment of these disorders, and thus are relevant to NIMH Strategic Objectives 1.1 and 1.3-to develop an integrative understanding of basic brain-behavior processes that provide the foundation for understanding mental disorders, and to identify and integrate biological markers (biomarkers) and behavioral indicators associated with mental disorders.
|Tucker, Matthew A; Morris, Christopher J; Morgan, Alexandra et al. (2017) The Relative Impact of Sleep and Circadian Drive on Motor Skill Acquisition and Memory Consolidation. Sleep 40:|
|Cox, Roy; Schapiro, Anna C; Manoach, Dara S et al. (2017) Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles. Front Hum Neurosci 11:433|
|Purcell, S M; Manoach, D S; Demanuele, C et al. (2017) Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource. Nat Commun 8:15930|
|Demanuele, Charmaine; Bartsch, Ullrich; Baran, Bengi et al. (2017) Coordination of Slow Waves With Sleep Spindles Predicts Sleep-Dependent Memory Consolidation in Schizophrenia. Sleep 40:|
|Tucker, Matthew A; Nguyen, Nam; Stickgold, Robert (2016) Experience Playing a Musical Instrument and Overnight Sleep Enhance Performance on a Sequential Typing Task. PLoS One 11:e0159608|
|Manoach, Dara S; Pan, Jen Q; Purcell, Shaun M et al. (2016) Reduced Sleep Spindles in Schizophrenia: A Treatable Endophenotype That Links Risk Genes to Impaired Cognition? Biol Psychiatry 80:599-608|
|Walker, Matthew P; Stickgold, Robert (2016) Understanding the boundary conditions of memory reconsolidation. Proc Natl Acad Sci U S A 113:E3991-2|
|Gregory, Michael D; Robertson, Edwin M; Manoach, Dara S et al. (2016) Thinking About a Task Is Associated with Increased Connectivity in Regions Activated by Task Performance. Brain Connect 6:164-8|
|Barsky, Murray M; Tucker, Matthew A; Stickgold, Robert (2015) REM sleep enhancement of probabilistic classification learning is sensitive to subsequent interference. Neurobiol Learn Mem 122:63-8|
|Manoach, Dara S; Stickgold, Robert (2015) Sleep, memory and schizophrenia. Sleep Med 16:553-4|
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