| Autor: |
Vladislav Myrov, Felix Siebenhühner, Joonas J. Juvonen, Gabriele Arnulfo, Satu Palva, J. Matias Palva |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Communications Biology, Vol 7, Iss 1, Pp 1-18 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2399-3642 |
| DOI: |
10.1038/s42003-024-06083-y |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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