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Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations.

ABSTRACT: Learning is assumed to induce specific changes in neuronal activity during sleep that serve the consolidation of newly acquired memories. To specify such changes, we measured electroencephalographic (EEG) coherence during performance on a declarative learning task (word pair associations) and subsequent sleep. Compared with a nonlearning control condition, learning performance was accompanied with a strong increase in coherence in several EEG frequency bands. During subsequent non-rapid eye movement sleep, coherence only marginally increased in a global analysis of EEG recordings. However, a striking and robust increase in learning-dependent coherence was found when analyses were performed time-locked to the occurrence of slow oscillations (<1 Hz). Specifically, the surface-positive half-waves of the slow oscillation resulting from widespread cortical depolarization were associated with distinctly enhanced coherence after learning in the slow-oscillatory, delta, slow-spindle, and gamma bands. The findings identify the depolarizing phase of the slow oscillations in humans as a time period particularly relevant for a reprocessing of memories in sleep.

SUBMITTER: Molle M

PROVIDER: S-EPMC518860 | biostudies-literature | 2004 Sep

REPOSITORIES: biostudies-literature

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Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations.

Mölle Matthias M Marshall Lisa L Gais Steffen S Born Jan J

Proceedings of the National Academy of Sciences of the United States of America 20040908 38

Learning is assumed to induce specific changes in neuronal activity during sleep that serve the consolidation of newly acquired memories. To specify such changes, we measured electroencephalographic (EEG) coherence during performance on a declarative learning task (word pair associations) and subsequent sleep. Compared with a nonlearning control condition, learning performance was accompanied with a strong increase in coherence in several EEG frequency bands. During subsequent non-rapid eye move ...[more]

PMID: 15356341

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Project description:Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = -0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories.

Dataset Information

Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations.

Publications

Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations.

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