Evidence map›Paper›PMID 35785365›Full record

ArticleFrontiers in neurology2022

A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG.

Dimitrios Mylonas, Martin Sjøgård, Zhaoyue Shi, Bryan Baxter, Matti Hämäläinen, Dara S Manoach, Sheraz Khan

Abstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Increased Sleep Spindles in Regions Engaged during Motor Learning Predict Memory Consolidation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dimitrios MylonasDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Martin SjøgårdDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Zhaoyue ShiDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Bryan BaxterDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Matti HämäläinenAthinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.
Dara S ManoachDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Sheraz KhanAthinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.

Indexed as

cortical sourcesEEGMEG (magnetoencephalography)sleep oscillationssleep spindlessource localizationstage 2 NREM sleep

Identifiers

PMID35785365
PMCPMC9243385

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.