Direction of information flow in large-scale resting-state networks is frequency-dependent
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Publication date
2016-04-05
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Abstract
Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-toposterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequencydependent reentry loops that are dominated by flow from parietooccipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.
Keywords
Atlas-based beamforming, Information flow, Magnetoencephalography, Phase transfer entropy, Resting-state networks, General, Journal Article, Research Support, Non-U.S. Gov't
Citation
Hillebrand, A, Tewarie, P, Van Dellen, E, Yu, M, Carbo, E W S, Douw, L, Gouw, A A, Van Straaten, E C W & Stam, C J 2016, 'Direction of information flow in large-scale resting-state networks is frequency-dependent', Proceedings of the National Academy of Sciences of the United States of America, vol. 113, no. 14, pp. 3867-3872. https://doi.org/10.1073/pnas.1515657113