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Relationships Between Sleep Spindles and Activities of Cerebral Cortex as Determined by Simultaneous EEG and MEG Recording

Summary: The purpose of this study was to clarify the relationships between the distributions and cortical sources of two types of spindles in the magnetoencephalogram (MEG) and how cortical activating areas contribute to the distribution of spindles. Spontaneous activities during sleep stage 2 were recorded from 7 normal subjects by simultaneous EEG and MEG recordings. Two types of spindles with frequency-specific topographic differences (fast spindles and slow spindles) were defined by EEG, and, subsequently, the sources of spindles were estimated as equivalent current dipoles using MEG. Activation centered in four areas, the precentral and postcentral areas in posterior frontal cortex and parietal cortex of each hemisphere. However, these areas were not always activated simultaneously. Fast spindles were associated with more frequent activation of postcentral areas with stronger activation strengths, whereas slow spindles were associated with more frequent activation of precentral areas with stronger activation strengths. When spindles were distributed symmetrically in amplitude between the hemispheres on both EEG and MEG, the four areas were activated equally and simultaneously. When spindles exhibited asymmetric distributions with amplitude differences above 30% between hemispheres, the cortical areas were activated with variable temporal relationships. Two types of spindle oscillations observed in the MEG had a common neural basis at the cortical level, with variability in patterns of activation and activation strengths resulting in the differences in distribution observed on the EEG and MEG. The differences in cortical activation patterns and activation strengths between the two types of spindles suggest that two distinct forms of spindle bursts propagate to cortex through different underlying neuronal circuits. Defining the cortical activating areas for spindles by MEG is valuable to consider the underlying neural basis.