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Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study

  • C . G. BénarEmail author
  • C. Grova
  • V. K. Jirsa
  • J. M. Lina
Article

Abstract

Electrophysiological signals (electroencephalography, EEG, and magnetoencephalography, MEG), as many natural processes, exhibit scale-invariance properties resulting in a power-law (1/f) spectrum. Interestingly, EEG and MEG differ in their slopes, which could be explained by several mechanisms, including non-resistive properties of tissues. Our goal in the present study is to estimate the impact of space/frequency structure of source signals as a putative mechanism to explain spectral scaling properties of neuroimaging signals. We performed simulations based on the summed contribution of cortical patches with different sizes (ranging from 0.4 to 104.2 cm2). Small patches were attributed signals of high frequencies, whereas large patches were associated with signals of low frequencies, on a logarithmic scale. The tested parameters included i) the space/frequency structure (range of patch sizes and frequencies) and ii) the amplitude factor c parametrizing the spatial scale ratios. We found that the space/frequency structure may cause differences between EEG and MEG scale-free spectra that are compatible with real data findings reported in previous studies. We also found that below a certain spatial scale, there were no more differences between EEG and MEG, suggesting a limit for the resolution of both methods.Our work provides an explanation of experimental findings. This does not rule out other mechanisms for differences between EEG and MEG, but suggests an important role of spatio-temporal structure of neural dynamics. This can help the analysis and interpretation of power-law measures in EEG and MEG, and we believe our results can also impact computational modeling of brain dynamics, where different local connectivity structures could be used at different frequencies.

Keywords

Power-law spectrum EEG MEG Biophysical model Scale-free dynamics 

Notes

Acknowledgments

CGB thanks Jean Gotman for useful discussions on spatial coherence. Research supported by grants ANR-16-CONV-0002 (ILCB) and ANR-11-IDEX-0001-02 (A*MIDEX)“. This work has been carried out within the FHU EPINEXT with the support of the A*MIDEX project (ANR-11-IDEX-0001-02) funded by the “Investissements d’Avenir“ French Governement program managed by the French National Research Agency (ANR). Part of this work was funded by a joint Agence Nationale de la Recherche (ANR) and Direction Génerale de l’Offre de Santé (DGOS) under grant “VIBRATIONS” ANR-13-PRTS-0011-01. Part of this work was funded by a FLAG ERA/HBP grant from Agence Nationale de la Recherche "SCALES" ANR-17-HBPR-0005. This work was performed within a platform member of France Life Imaging network (grant ANR-11-INBS-0006).

Compliance with ethical standards

Conflict of interests

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. 1.Aix Marseille Univ, INSERMINS, Inst Neurosci SystMarseilleFrance
  2. 2.PERFORM Centre and Physics DepartmentConcordia UniversityMontrealCanada
  3. 3.Montreal Neurological Institute and HospitalMcGill UniversityMontrealCanada
  4. 4.Multimodal Functional Imaging Laboratory, Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
  5. 5.Centre de Recherches MathématiquesMontrealCanada
  6. 6.Département de Génie ÉlectriqueÉcole de Technologie SupérieureMontrealCanada
  7. 7.Centre d’Etudes Avancées en Médecine du SommeilHôpital Sacré CœurMontrealCanada

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