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Magnetoencephalography demonstrates multiple asynchronous generators during human sleep spindles.

Nima Dehghani¹, Sydney S Cash, Andrea O Rossetti

¹Multimodal Imaging Laboratory, Departments of Radiology and Neuroscience, University of California, San Diego, California, USA.

Journal of Neurophysiology

|April 30, 2010

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Human sleep spindles, bursts of brain activity during stage 2 sleep, appear synchronous on EEG but asynchronous on MEG, suggesting multiple underlying neural generators.

Area of Science:

Neuroscience
Sleep Science
Brain Activity

Background:

Sleep spindles are brief, rhythmic brainwave bursts during stage 2 sleep.
They are generally considered synchronous across the human scalp and in animal models.
Previous studies hinted at discrepancies between EEG and MEG during spindles, but lacked detailed analysis.

Purpose of the Study:

To systematically compare high-density electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during human sleep spindles.
To investigate the synchronicity and spatial distribution of neural generators underlying sleep spindles.

Main Methods:

Simultaneous, high-density EEG and MEG recordings were obtained during natural sleep in healthy humans.
Analysis focused on naturally occurring sleep spindles.

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Coherence, topography, and principal component analysis (PCA) were used to compare EEG and MEG data.

Main Results:

EEG showed high scalp coherence and consistent topography during spindles.
MEG signals were not synchronous, exhibiting significant variations in amplitude and phase across locations and spindles.
EEG coherence was ~0.7, while MEG coherence was ~0.3.
Two principal components explained 50% of EEG variance, whereas MEG required over 15 components.
MEG components involved multiple distributed locations, unlike the localized generators suggested by animal models.

Conclusions:

Human sleep spindles likely arise from multiple, asynchronous neural generators, challenging current models.
The apparent synchronicity in EEG may result from the overlapping activity of these distributed sources.
MEG might preferentially capture focal thalamocortical activity, while EEG reflects a more diffuse matrix system.