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Erschienen in: Journal of Computational Neuroscience 1/2019

11.07.2019

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

verfasst von: C . G. Bénar, C. Grova, V. K. Jirsa, J. M. Lina

Erschienen in: Journal of Computational Neuroscience | Ausgabe 1/2019

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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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Fußnoten
1
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.
 
Literatur
Zurück zum Zitat Bullock, T. H., & McClune, M. C. (1989). Lateral coherence of the electrocorticogram: A new measure of brain synchrony. Electroencephalography and Clinical Neurophysiology, 73(6), 479–498.CrossRefPubMed Bullock, T. H., & McClune, M. C. (1989). Lateral coherence of the electrocorticogram: A new measure of brain synchrony. Electroencephalography and Clinical Neurophysiology, 73(6), 479–498.CrossRefPubMed
Zurück zum Zitat Bullock, T. H., McClune, M. C., Achimowicz, J. Z., Iragui-Madoz, V. J., Duckrow, R. B., & Spencer, S. S. (1995). EEG coherence has structure in the millimeter domain: Subdural and hippocampal recordings from epileptic patients. Electroencephalography and Clinical Neurophysiology, 95(3), 161–177.CrossRefPubMed Bullock, T. H., McClune, M. C., Achimowicz, J. Z., Iragui-Madoz, V. J., Duckrow, R. B., & Spencer, S. S. (1995). EEG coherence has structure in the millimeter domain: Subdural and hippocampal recordings from epileptic patients. Electroencephalography and Clinical Neurophysiology, 95(3), 161–177.CrossRefPubMed
Zurück zum Zitat Buzsaki, G. (2006). Rhythms of the brain. Buzsaki, G. (2006). Rhythms of the brain.
Zurück zum Zitat Cointepas, Y., Geffroy, D., Souedet, N., Denghien, I., & Rivière, D. (2010). The BrainVISA project: A shared software development infrastructure for biomedical imaging research. Cointepas, Y., Geffroy, D., Souedet, N., Denghien, I., & Rivière, D. (2010). The BrainVISA project: A shared software development infrastructure for biomedical imaging research.
Zurück zum Zitat Cosandier-Rimélé, D., Badier, J. M., Chauvel, P., & Wendling, F. (2007). Modeling and interpretation of scalp-EEG and depth-EEG signals during interictal activity. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, 4277–4280. https://doi.org/10.1109/iembs.2007.4353281.CrossRef Cosandier-Rimélé, D., Badier, J. M., Chauvel, P., & Wendling, F. (2007). Modeling and interpretation of scalp-EEG and depth-EEG signals during interictal activity. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, 4277–4280. https://​doi.​org/​10.​1109/​iembs.​2007.​4353281.CrossRef
Zurück zum Zitat Destexhe, A., Contreras, D., & Steriade, M. (1999). Spatiotemporal analysis of local field potentials and unit discharges in cat cerebral cortex during natural wake and sleep states. The Journal of Neuroscience, 19(11), 4595–4608.CrossRefPubMedPubMedCentral Destexhe, A., Contreras, D., & Steriade, M. (1999). Spatiotemporal analysis of local field potentials and unit discharges in cat cerebral cortex during natural wake and sleep states. The Journal of Neuroscience, 19(11), 4595–4608.CrossRefPubMedPubMedCentral
Zurück zum Zitat Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., & Lounasmaa, O. V. (1993). Magnetoencephalography—Theory, instrumentation, and applications to noninvasive studies of the working human brain. Reviews of Modern Physics, 65, 414–497.CrossRef Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., & Lounasmaa, O. V. (1993). Magnetoencephalography—Theory, instrumentation, and applications to noninvasive studies of the working human brain. Reviews of Modern Physics, 65, 414–497.CrossRef
Zurück zum Zitat Nunez, P., & Srinivasan, R. (2005). Electric fields of the brain: The Neurophysics of EEG. Oxford: Oxford University Press. Nunez, P., & Srinivasan, R. (2005). Electric fields of the brain: The Neurophysics of EEG. Oxford: Oxford University Press.
Zurück zum Zitat Pfurtscheller, G., & Cooper, R. (1975). Frequency dependence of the transmission of the EEG from cortex to scalp. Electroencephalography and Clinical Neurophysiology, 38(1), 93–96.CrossRefPubMed Pfurtscheller, G., & Cooper, R. (1975). Frequency dependence of the transmission of the EEG from cortex to scalp. Electroencephalography and Clinical Neurophysiology, 38(1), 93–96.CrossRefPubMed
Zurück zum Zitat von Stein, A., & Sarnthein, J. (2000). Different frequencies for different scales of cortical integration: From local gamma to long range alpha/theta synchronization. International Journal of Psychophysiology, 38(3), 301–313.CrossRef von Stein, A., & Sarnthein, J. (2000). Different frequencies for different scales of cortical integration: From local gamma to long range alpha/theta synchronization. International Journal of Psychophysiology, 38(3), 301–313.CrossRef
Metadaten
Titel
Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study
verfasst von
C . G. Bénar
C. Grova
V. K. Jirsa
J. M. Lina
Publikationsdatum
11.07.2019
Verlag
Springer US
Erschienen in
Journal of Computational Neuroscience / Ausgabe 1/2019
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI
https://doi.org/10.1007/s10827-019-00721-9

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