Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

Vladislav Myrov*, Felix Siebenhühner, Joonas J. Juvonen, Gabriele Arnulfo, Satu Palva, J. Matias Palva

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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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.

Original languageEnglish
Article number405
Pages (from-to)1-18
Number of pages18
JournalCommunications Biology
Issue number1
Publication statusPublished - 3 Apr 2024
MoE publication typeA1 Journal article-refereed


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