Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or ‘oscillatoriness’ per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantification of rhythmicity. We applied pACF to human...

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Published inCommunications biology Vol. 7; no. 1; p. 405
Main Authors Myrov, Vladislav, Siebenhühner, Felix, Juvonen, Joonas J., Arnulfo, Gabriele, Palva, Satu, Palva, J. Matias
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 03.04.2024
Nature Publishing Group
Nature Portfolio
Subjects
631/1647/1453
631/378/116
Attention - physiology
Biology
Biomedical and Life Sciences
Electroencephalography
Humans
Life Sciences
Lifetime
Magnetoencephalography
Magnetoencephalography - methods
Neurons - physiology
Oscillations
Periodicity
Stereotaxic Techniques
Synchronization
Time series
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Summary:Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or ‘oscillatoriness’ per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantification of rhythmicity. We applied pACF to human intracerebral stereoelectroencephalography (SEEG) and magnetoencephalography (MEG) data and uncovered a spectrally and anatomically fine-grained cortical architecture in the rhythmicity of single- and multi-frequency neuronal oscillations. Evidencing the functional significance of rhythmicity, we found it to be a prerequisite for long-range synchronization in resting-state networks and to be dynamically modulated during event-related processing. We also extended the pACF approach to measure ’burstiness’ of oscillatory processes and characterized regions with stable and bursty oscillations. These findings show that rhythmicity is double-dissociable from amplitude and constitutes a functionally relevant and dynamic characteristic of neuronal oscillations. Myrov and colleagues introduce a novel method to measure the rhythmicity of neuronal oscillations and demonstrating that the oscillatory architecture of the human cortex is spectrally sparse and anatomically well delineated.
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ISSN:2399-3642
2399-3642
DOI:10.1038/s42003-024-06083-y