# Optimizing sleep spindle measurements as translational assays of memory consolidation

> **NIH NIH UH3** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $670,441

## Abstract

This research proposal addresses a key challenge to drug development: the paucity of biomarkers that reveal
whether interventions affect implicated brain circuitry at early stages, in animals and humans, before embarking
on lengthy and expensive clinical trials. Studies of humans and rodents have established sleep spindles, defining
EEG oscillations of stage 2 non-rapid eye movement (NREM) sleep, as a mechanism of memory consolidation.
A growing body of work implicates sleep spindle abnormalities in neurodevelopmental and neurodegenerative
disorders characterized by memory impairment. In schizophrenia, sleep spindle deficits predict impaired sleep-
dependent memory consolidation. Findings that increasing spindles via drugs or auditory or transcranial brain
stimulation during sleep improves memory in healthy people, provides the impetus to target spindles to improve
memory in disorders. But targeting spindles does not inevitably improve memory. Complementary rodent and
human studies provide an explanation: sleep-dependent memory consolidation relies not on spindles alone, but
on their precise temporal coordination with the other two cardinal NREM sleep oscillations: cortical slow
oscillations (SOs) and hippocampal sharp-wave ripples. These findings make it clear that while spindles are
promising targets for improving memory, (i) effective therapies need to increase spindles AND preserve or
enhance their coupling with SOs and ripples, and (ii) to evaluate efficacy, we need new assays to identify spindles
that couple with SOs and ripples to mediate memory versus those that do not. We propose to: (i) identify the
most powerful translational measures of sleep spindles as assays of sleep-dependent memory consolidation
(UG3), and (ii) to noninvasively manipulate them to compare their responses in healthy humans and rodents
(UH3). Using invasive recordings in epilepsy patients and local field potentials (LFPs) in rats, we will first
demonstrate that spindles that couple with both SOs and ripples (TriCS: triple-coupled spindles) are associated
with memory consolidation, thereby validating TriCS as a translational biomarker of memory. We will then use
machine learning to develop a classifier that identifies TriCS based solely on their scalp EEG features. We will
validate the EEG spindle classifier by applying it to a dataset from healthy humans to demonstrate that TriCS,
but not non-coupled spindles, correlate with memory consolidation. In both species, we will determine which
spindle assay TriCS, SO-coupled spindles (SOCS) or total spindles predicts memory best. Finally, we will
noninvasively manipulate the spindle assays in humans and rats. Genetic studies are implicating specific
pathophysiologic mechanisms of spindle deficits in schizophrenia and autism and identifying novel targets and
treatments. The rodent and human spindle assays that we will develop will facilitate the translation of these
advances to the clinic by allowing the efficient evaluatio...

## Key facts

- **NIH application ID:** 10791859
- **Project number:** 5UH3MH125273-04
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** DARA S MANOACH
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $670,441
- **Award type:** 5
- **Project period:** 2021-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10791859

## Citation

> US National Institutes of Health, RePORTER application 10791859, Optimizing sleep spindle measurements as translational assays of memory consolidation (5UH3MH125273-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10791859. Licensed CC0.

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