Data from: Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

dc.contributor.affiliationAalto University - Myrov, Vladislav
dc.contributor.affiliationUniversity of Helsinki - Siebenhühner, Felix
dc.contributor.affiliationAalto University - Juvonen, Joonas J
dc.contributor.affiliationUniversity of Genoa - Arnulfo, Gabriele
dc.contributor.affiliationUniversity of Glasgow - Palva, Satu
dc.contributor.affiliationAalto University - Palva, Matias
dc.contributor.authorMyrov, Vladislav
dc.contributor.authorSiebenhühner, Felix
dc.contributor.authorJuvonen, Joonas J
dc.contributor.authorArnulfo, Gabriele
dc.contributor.authorPalva, Satu
dc.contributor.authorPalva, Matias
dc.date.accessioned2025-03-24T15:19:10Z
dc.date.issued2024-03-15
dc.date.issued2024-03-15
dc.descriptionNeuronal 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 direct quantification of rhythmicity. We applied pACF to human intracerebral stereo-electroencephalography (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.
dc.identifierhttps://doi.org/10.5061/dryad.rbnzs7hhf
dc.identifier.urihttps://hydatakatalogi-test-24.it.helsinki.fi/handle/123456789/10430
dc.rightsOpen
dc.rights.licensecc-zero
dc.subjectphase autocorrelation
dc.subjectNeuroscience
dc.subjectComputational neuroscience
dc.titleData from: Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture
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