Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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2024-04-03

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en

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18

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Communications Biology, Volume 7, issue 1, pp. 1-18

Abstract

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.

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Publisher Copyright: © The Author(s) 2024.

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Myrov, V, Siebenhühner, F, Juvonen, J J, Arnulfo, G, Palva, S & Palva, J M 2024, ' Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture ', Communications Biology, vol. 7, no. 1, 405, pp. 1-18 . https://doi.org/10.1038/s42003-024-06083-y