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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-60599

Scheffzük, C; Kukushka, V I; Vyssotski, A L; Draguhn, A; Tort, A B I; Brankačk, J (2011). Selective coupling between theta phase and neocortical fast gamma oscillations during REM-sleep in mice. PLoS ONE, 6(12):e28489.

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Abstract

BACKGROUND:

The mammalian brain expresses a wide range of state-dependent network oscillations which vary in frequency and spatial extension. Such rhythms can entrain multiple neurons into coherent patterns of activity, consistent with a role in behaviour, cognition and memory formation. Recent evidence suggests that locally generated fast network oscillations can be systematically aligned to long-range slow oscillations. It is likely that such cross-frequency coupling supports specific tasks including behavioural choice and working memory.
PRINCIPAL FINDINGS:

We analyzed temporal coupling between high-frequency oscillations and EEG theta activity (4-12 Hz) in recordings from mouse parietal neocortex. Theta was exclusively present during active wakefulness and REM-sleep. Fast oscillations occurred in two separate frequency bands: gamma (40-100 Hz) and fast gamma (120-160 Hz). Theta, gamma and fast gamma were more prominent during active wakefulness as compared to REM-sleep. Coupling between theta and the two types of fast oscillations, however, was more pronounced during REM-sleep. This state-dependent cross-frequency coupling was particularly strong for theta-fast gamma interaction which increased 9-fold during REM as compared to active wakefulness. Theta-gamma coupling increased only by 1.5-fold.
SIGNIFICANCE:

State-dependent cross-frequency-coupling provides a new functional characteristic of REM-sleep and establishes a unique property of neocortical fast gamma oscillations. Interactions between defined patterns of slow and fast network oscillations may serve selective functions in sleep-dependent information processing.

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
DDC:570 Life sciences; biology
Language:English
Date:01 December 2011
Deposited On:03 Mar 2012 22:10
Last Modified:14 Dec 2013 12:06
Publisher:Public Library of Science
Series Name:PLoS ONE
Number of Pages:0
ISSN:1932-6203
Publisher DOI:10.1371/journal.pone.0028489
PubMed ID:22163023
Citations:Web of Science®. Times Cited: 11
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