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Journal Article

Frequency-specific directed interactions in the human brain network for language

MPS-Authors
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Schoffelen,  Jan-Mathijs
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Hulten,  Annika
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Lam,  Nietzsche H. L.
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
International Max Planck Research School for Language Sciences, MPI for Psycholinguistics, Max Planck Society;

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Udden,  Julia
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Hagoort,  Peter
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Fulltext (public)

Schoffelen_etal_PNAS_2017.pdf
(Publisher version), 2MB

Supplementary Material (public)

pnas.201703155SI.pdf
(Supplementary material), 2MB

Citation

Schoffelen, J.-M., Hulten, A., Lam, N. H. L., Marquand, A. F., Udden, J., & Hagoort, P. (2017). Frequency-specific directed interactions in the human brain network for language. Proceedings of the National Academy of Sciences of the United States of America, 114(30), 8083-8088. doi:10.1073/pnas.1703155114.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002D-94A8-1
Abstract
The brain’s remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that the information flow between language-relevant brain areas, which is required for linguistic processing, may depend on the contributions of distinct brain rhythms