ArticlePLoS computational biology2019
Spatial neuronal synchronization and the waveform of oscillations: Implications for EEG and MEG.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Schizophrenia: temporal imprecision in phase, time, and frequency domains.Schizophrenia (Heidelberg, Germany) · 2026Article
- Primary Somatosensory to Motor Cortex Microstructural Connectivity Predicts the Mu-Rhythm Phase Effect on Corticospinal Excitability: An EEG-TMS Study.Human brain mapping · 2026Article
- The influence of nonlinear resonance on human cortical oscillations.Communications biology · 2026Article
- Modeling Emotional Arousal With Turbulence Measured by EEG.Psychophysiology · 2025Article
- Machine learning of brain-specific biomarkers from EEG.EBioMedicine · 2024Article
- The primate cortical LFP exhibits multiple spectral and temporal gradients and widespread task dependence during visual short-term memory.Journal of neurophysiology · 2024Article
- Realness of face images can be decoded from non-linear modulation of EEG responses.Scientific reports · 2024Article
- Oscillatory Waveform Shape and Temporal Spike Correlations Differ across Bat Frontal and Auditory Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- The Primate Cortical LFP Exhibits Multiple Spectral and Temporal Gradients and Widespread Task-Dependence During Visual Short-Term Memory.bioRxiv : the preprint server for biology · 2024Article
- Article
- Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms.bioRxiv : the preprint server for biology · 2023Article
- Overcoming harmonic hurdles: Genuine beta-band rhythms vs. contributions of alpha-band waveform shape.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Chronic CaeLife · 2022Article
- Non-zero mean alpha oscillations revealed with computational model and empirical data.PLoS computational biology · 2022Article
- Methodological considerations for studying neural oscillations.The European journal of neuroscience · 2022Article
- Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series.Psychophysiology · 2022Article
- Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters.PLoS computational biology · 2021Article
- Conditional Entropy: A Potential Digital Marker for Stress.Entropy (Basel, Switzerland) · 2021Article
- Time-evolving controllability of effective connectivity networks during seizure progression.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Neuronal oscillations are ubiquitous in the human brain and are implicated in virtually all brain functions. Although they can be described by a prominent peak in the power spectrum, their waveform is not necessarily sinusoidal and shows rather complex morphology. Both frequency and temporal descriptions of such non-sinusoidal neuronal oscillations can be utilized. However, in non-invasive EEG/MEG recordings the waveform of oscillations often takes a sinusoidal shape which in turn leads to a rather oversimplified view on oscillatory processes. In this study, we show in simulations how spatial synchronization can mask non-sinusoidal features of the underlying rhythmic neuronal processes. Consequently, the degree of non-sinusoidality can serve as a measure of spatial synchronization. To confirm this empirically, we show that a mixture of EEG components is indeed associated with more sinusoidal oscillations compared to the waveform of oscillations in each constituent component. Using simulations, we also show that the spatial mixing of the non-sinusoidal neuronal signals strongly affects the amplitude ratio of the spectral harmonics constituting the waveform. Finally, our simulations show how spatial mixing can affect the strength and even the direction of the amplitude coupling between constituent neuronal harmonics at different frequencies. Validating these simulations, we also demonstrate these effects in real EEG recordings. Our findings have far reaching implications for the neurophysiological interpretation of spectral profiles, cross-frequency interactions, as well as for the unequivocal determination of oscillatory phase.
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