Keyword search (4,163 papers available)

"MEG" Keyword-tagged Publications:

Title Authors PubMed ID
1 Human Auditory-Motor Networks Show Frequency-Specific Phase-Based Coupling in Resting-State MEG Bedford O; Noly-Gandon A; Ara A; Wiesman AI; Albouy P; Baillet S; Penhune V; Zatorre RJ; 39757971
PSYCHOLOGY
2 EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy Afnan J; Cai Z; Lina JM; Abdallah C; Delaire E; Avigdor T; Ros V; Hedrich T; von Ellenrieder N; Kobayashi E; Frauscher B; Gotman J; Grova C; 38994740
SOH
3 New Megastigmane and Polyphenolic Components of Henna Leaves and Their Tumor-Specific Cytotoxicity on Human Oral Squamous Carcinoma Cell Lines Orabi MAA; Orabi EA; Awadh AAA; Alshahrani MM; Abdel-Wahab BA; Sakagami H; Hatano T; 38001804
CHEMBIOCHEM
4 The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; 37675803
CONCORDIA
5 Air monitoring of tire-derived chemicals in global megacities using passive samplers Johannessen C; Saini A; Zhang X; Harner T; 36152723
CHEMBIOCHEM
6 Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients Pellegrino G, Xu M, Alkuwaiti A, Porras-Bettancourt M, Abbas G, Lina JM, Grova C, Kobayashi E, 32582009
PERFORM
7 Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients. Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E 32386115
PERFORM
8 Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study. Bénar CG, Grova C, Jirsa VK, Lina JM 31292816
PERFORM
9 Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Heers M, Chowdhury RA, Hedrich T, Dubeau F, Hall JA, Lina JM, Grova C, Kobayashi E 25609211
PERFORM
10 Source localization of the seizure onset zone from ictal EEG/MEG data. Pellegrino G, Hedrich T, Chowdhury R, Hall JA, Lina JM, Dubeau F, Kobayashi E, Grova C 27059157
PERFORM
11 Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study. Aydin Ü, Rampp S, Wollbrink A, Kugel H, Cho J-, Knösche TR, Grova C, Wellmer J, Wolters CH 28510905
PERFORM
12 Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method. Pellegrino G, Hedrich T, Chowdhury RA, Hall JA, Dubeau F, Lina JM, Kobayashi E, Grova C 29024165
PERFORM
13 Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy. Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C 29164737
PERFORM
14 Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C 28619655
PERFORM

 

Title:Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study.
Authors:Bénar CGGrova CJirsa VKLina JM
Link:https://www.ncbi.nlm.nih.gov/pubmed/31292816?dopt=Abstract
DOI:10.1007/s10827-019-00721-9
Publication:Journal of computational neuroscience
Keywords:Biophysical modelEEGMEGPower-law spectrumScale-free dynamics
PMID:31292816 Category:J Comput Neurosci Date Added:2019-08-07
Dept Affiliation: PERFORM
1 Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France. christian.benar@univ-amu.fr.
2 PERFORM Centre and Physics Department, Concordia University, Montreal, QC, Canada.
3 Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
4 Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.
5 Centre de Recherches Mathématiques, Montreal, QC, Canada.
6 Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.
7 Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.
8 Centre d'Etudes Avancées en Médecine du Sommeil, Hôpital Sacré Cœur, Montreal, QC, Canada.

Description:

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

J Comput Neurosci. 2019 Jul 11;:

Authors: Bénar CG, Grova C, Jirsa VK, Lina JM

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.

PMID: 31292816 [PubMed - as supplied by publisher]





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