MEG-EEG-fMRI: What can be gained in the study of the brain with a multimodal approach

Autor: Dante Mantini, C. Del Gratta, G.L. Romani, Marcella Brunetti

In this short review we describe the potentialities, the difficulties, and the most common methods of combining EEG/MEG and fMRI data into a single neuroimaging technique with high spatial and temporal resolution. Two examples of application to brain

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::105dd3f36f02d9a86beb23b7a35f8674
https://ora.ox.ac.uk/objects/uuid:b4ce3db4-7b33-4039-aecc-aee8cb5f4fe8

Multimodal Integration of fMRI and EEG Data for High Spatial and Temporal Resolution Analysis of Brain Networks

Autor: G.L. Romani, Maurizio Corbetta, C. Del Gratta, Dante Mantini, Laura Marzetti

Publikováno v: Brain Topography. 23:150-158

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e28e811bb64d88d2f4e237b179f04de
https://doi.org/10.1007/s10548-009-0132-3

Empirical Markov Chain Monte Carlo Bayesian analysis of fMRI data

Autor: F. de Pasquale, G.L. Romani, C. Del Gratta

Publikováno v: NeuroImage. 42:99-111

In this work an Empirical Markov Chain Monte Carlo Bayesian approach to analyse fMRI data is proposed. The Bayesian framework is appealing since complex models can be adopted in the analysis both for the image and noise model. Here, the noise autocor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a391da5816da09ff1154db2beb492fdb
https://doi.org/10.1016/j.neuroimage.2008.04.235

The use of standardized infinity reference in EEG coherency studies

Autor: Gian Luca Romani, Laura Marzetti, C. Del Gratta, Mauro Gianni Perrucci, Guido Nolte

Publikováno v: NeuroImage. 36:48-63

The study of large scale interactions in the brain from EEG signals is a promising method for the identification of functional networks. However, the validity of a large scale parameter is limited by two factors: the use of a non-neutral reference an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6a45a462c9eb7bad6879af4940cde3c
https://doi.org/10.1016/j.neuroimage.2007.02.034

Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics?

Autor: Claudia Altamura, Antonio Ferretti, Franca Tecchio, Massimo Caulo, G.L. Romani, C. Del Gratta, Filippo Zappasodi, Fabrizio Vernieri, Vittorio Pizzella, P.M. Rossini

Publikováno v: Brain
127 (2004): 99–110. doi:10.1093/brain/awh012
info:cnr-pdr/source/autori:Rossini PM; Altamura C; Ferretti A; Vernieri F; Zappasodi F; Caulo M; Pizzella V; Del Gratta C; Romani GL; Tecchio F/titolo:Does cerebrovascular disease affect the coupling between neuronal activity and local hemodinamics?/doi:10.1093%2Fbrain%2Fawh012/rivista:Brain (Print)/anno:2004/pagina_da:99/pagina_a:110/intervallo_pagine:99–110/volume:127

The relationship between neurophysiological and cerebrovascular-metabolic findings in patients affected by severe cerebrovascular deficits was investigated by comparing magnetoencephalographic (MEG-evoked fields) and blood oxygen level-dependent func

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a7e479484c6acbaf3c2ca7752f82871
https://doi.org/10.1093/brain/awh012