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Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture.
- Source :
-
Communications Biology . 4/3/2024, Vol. 7 Issue 1, p1-18. 18p. - Publication Year :
- 2024
-
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. 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *OSCILLATIONS
*MAGNETOENCEPHALOGRAPHY
Subjects
Details
- Language :
- English
- ISSN :
- 23993642
- Volume :
- 7
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Communications Biology
- Publication Type :
- Academic Journal
- Accession number :
- 176453243
- Full Text :
- https://doi.org/10.1038/s42003-024-06083-y