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.
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Notes
In a purely resistive medium, the propagation of electromagnetic fields only depends on the electrical resistance of the different components (here, brain, skull, CSF, scalp…). Importantly, in this case, there is no dependency of the observed fields on frequency. In other words, there is no filtering effect of the tissues, in contrast with non-resistive tissues where signals may be attenuated at high frequencies.
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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).
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Bénar, C...G., Grova, C., Jirsa, V.K. et al. Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study. J Comput Neurosci 47, 31–41 (2019). https://doi.org/10.1007/s10827-019-00721-9
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DOI: https://doi.org/10.1007/s10827-019-00721-9