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  Head models and dynamic causal modeling of subcortical activity using magnetoencephalographic/electroencephalographic data

Attal, Y., Maess, B., Friederici, A. D., & David, O. (2012). Head models and dynamic causal modeling of subcortical activity using magnetoencephalographic/electroencephalographic data. Reviews in the Neurosciences, 23(1), 85-95. doi:10.1515/rns.2011.056.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-10D0-A Version Permalink: http://hdl.handle.net/21.11116/0000-0004-5C24-D
Genre: Journal Article

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 Creators:
Attal, Yohan1, 2, 3, Author
Maess, Burkhard4, Author              
Friederici, Angela D.5, Author              
David, Olivier6, 7, 8, Author
Affiliations:
1Centre de Recherche de l’institut du Cerveau et de la Moelle épinière, Université Pierre et Marie Curie-Paris VI, Paris, France, ou_persistent22              
2Institut national de la santé et de la recherche médicale, Paris, France, ou_persistent22              
3Centre national de la recherche scientifique, Paris, France, ou_persistent22              
4Methods and Development Unit MEG and EEG: Signal Analysis and Modelling, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634559              
5Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
6Brain Function and Neuromodulation, Joseph Fourier University, Grenoble, France, ou_persistent22              
7Grenoble Institut des Neurosciences, La Tronche, France, ou_persistent22              
8Neuroradiology Department and MRI Unit, University Hospital, Grenoble, France, ou_persistent22              

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Free keywords: Deep brain activity; Dynamic causal modeling; Electroencephalography; Head models; Inverse models; Magnetoencephalography
 Abstract: Cognitive functions involve not only cortical but also subcortical structures. Subcortical sources, however, contribute very little to magnetoencephalographic (MEG) and electroencephalographic (EEG) signals because they are far from external sensors and their neural architectonic organization often makes them electromagnetically silent. Estimating the activity of deep sources from MEG and EEG (M/EEG) data is thus a challenging issue. Here, we review the influence of geometric parameters (location/orientation) on M/EEG signals produced by the main deep brain structures (amygdalo-hippocampal complex, thalamus and some basal ganglia). We then discuss several methods that have been utilized to solve the issues and localize or quantify the M/EEG contribution from deep neural currents. These methods rely on realis­tic forward models of subcortical regions or on introducing strong dynamical priors on inverse solutions that are based on biologically plausible neural models, such as those used in dynamic causal modeling (DCM) for M/EEG.

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Language(s): eng - English
 Dates: 2011-08-232011-10-072012-02-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1515/rns.2011.056
PMID: 22718615
 Degree: -

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Title: Reviews in the Neurosciences
Source Genre: Journal
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Publ. Info: London : Freund Pub. House
Pages: - Volume / Issue: 23 (1) Sequence Number: - Start / End Page: 85 - 95 Identifier: ISSN: 0334-1763
CoNE: https://pure.mpg.de/cone/journals/resource/954927654884