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

Autor: Christophe Grova, Viktor K. Jirsa, Jean-Marc Lina, Christian Bénar
Přispěvatelé: Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Aix Marseille Université (AMU), Concordia University [Montreal], Ecole de Technologie Supérieure [Montréal] (ETS), ANR-16-CONV-0002,ILCB,ILCB: Institute of Language Communication and the Brain(2016), ANR-11-IDEX-0001,Amidex,INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE(2011), ANR-13-PRTS-0011,VIBRATIONS,Interprétation des signaux électrophysiologiques en épilepsie basée sur un cerveau virtuel(2013), ANR-11-INBS-0006,FLI,France Life Imaging(2011)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Signal Processing (eess.SP)
0301 basic medicine
Logarithmic scale
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
Cognitive Neuroscience
Models
Neurological
Electroencephalography
Power law
03 medical and health sciences
Cellular and Molecular Neuroscience
0302 clinical medicine
Power-law spectrum
Neuroimaging
FOS: Electrical engineering
electronic engineering
information engineering
medicine
Animals
Humans
Computer Simulation
Statistical physics
EEG
Electrical Engineering and Systems Science - Signal Processing
Scaling
Biophysical model
Physics
MEG
medicine.diagnostic_test
Brain
Magnetoencephalography
Signal Processing
Computer-Assisted
Scale-free dynamics
Sensory Systems
030104 developmental biology
Amplitude
FOS: Biological sciences
Quantitative Biology - Neurons and Cognition
Spatial ecology
Neurons and Cognition (q-bio.NC)
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Algorithms
030217 neurology & neurosurgery
Zdroj: Journal of Computational Neuroscience
Journal of Computational Neuroscience, Springer Verlag, 2019, 47 (1), pp.31-41. ⟨10.1007/s10827-019-00721-9⟩
ISSN: 0929-5313
1573-6873
DOI: 10.1007/s10827-019-00721-9⟩
Popis: International audience; 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 cm 2). 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.
Databáze: OpenAIRE
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