Grant: Discovery Grants Program - Individual

The principal goal of the research program is to gain a deeper understanding of how learning and memory can be enhanced by sound presented during sleep. In 2013, Ngo at al. demonstrated that the strength of slow oscillations (SOs) and the density of spindles during sleep could be boosted by precisely timed sound bursts, a technique known as closed-loop auditory stimulation (CLAS). Enhancement was related to memory performance improvements the following day. CLAS thus provides a means of probing the memory function of sleep, but the mechanism through which sound affects brain activity is not understood, and its effects on real-life tasks (which are far more complex than the simple paradigms studied to date) are unknown. I have developed a skill set that is uniquely suited to understanding these processes: experience with complex training tasks, CLAS, and whole-brain source modeling of oscillations induced by tasks during wakefulness and those during sleep, using MEG; this work will form the basis of my new lab's research direction. I propose three distinct aims: Aim I: How does closed-loop auditory stimulation (CLAS) enhance slow oscillations (SOs)?  We will deliver noise bursts during NREM sleep in the MEG to target phases of SOs, in order to test the hypotheses: i) that signal propagation from the primary auditory cortex to secondary regions depends on the phase of ongoing SOs; and, using source-localized connectivity analysis, ii) that the critical interaction between evoked responses and endogenous cortical SOs takes place in the cortex vs. in the brainstem via processes of arousal. Aim II: What are the neural correlates of complex task consolidation in NREM sleep?  We will establish an effect of sleep-dependent memory consolidation in a piano-based learning paradigm that we previously developed (i.e. on sequence, timing accuracy), and characterize spatiotemporal signatures of wake task performance and sleep consolidation using EEG. We predict an increase in SO and spindle activity which is proportional to next-day task improvement. Aim III: Can we enhance complex learning with CLAS? Armed with the knowledge gained in I and II, we will use MEG's higher spatial resolution to test the hypothesis that CLAS enhances consolidation in a use-dependent fashion. We hypothesize that CLAS as compared with no stimulation will increase SO amplitude and spindle density within task-related brain regions. Because CLAS has considerable potential for health applications, a deeper understanding of the mechanisms through which sound can influence endogenous brain activity and memory is necessary. Our results will be directly relevant to the many groups who are trying to harness sleep-dependent consolidation, and may eventually lead to the development of better therapies to the cognitive benefits of sleep that can be degraded by disease and aging. Our results will also further our understanding of the memory function of sleep.