The authors would like to thank Matti S. H&auml;m&auml;l&auml;inen, Lilla Z&ouml;llei and three anonymous reviewers for their helpful comments. Funding sources: R00DC010196 (AKCL); T32DC000018 (EDL); T32DC005361 (RKM).

1. Anatomical Data Acquisition and Processing
<ol>
 <li>Acquire one magnetization-prepared rapid gradient echo (MPRAGE) MRI scan of the subject. This may take 5-10 min depending on which specific scanning protocol is used.</li>
 <li>Acquire two additional fast low-angle shot (FLASH) MRI scans (flip angles = 5&deg; and 30&deg;) if EEG data are used for inverse imaging analysis, as FLASH sequences provide different tissue contrast from the standard MPRAGE sequences 1.</li>
 <li>Use FreeSurfer software (see Tab...

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In order to estimate the dipole activation on the cortex from the acquired MEG/EEG data, we need to solve an inverse problem, which does not have a unique stable solution unless appropriate anatomically and physiologically sound constraints are applied. Using the anatomical constraint acquired for individual subjects using MRI and adopting the minimum-norm as our estimation criterion, we can arrive at an inverse cortical current source estimate that agrees with the sensor measurements. This approach has proved useful in ...

<table border="1">
 <tbody>
 <tr>
 <td>Name of equipment / software</td>
 <td>Company / source</td>
 <td></td>
 <td></td>
 </tr>
 <tr>
 <td>306-channel Vectorview MEG system</td>
 <td>Eleka-Neuromag Ltd,</td>
 <td></td>
 <td></td>
 </tr>
 <tr>
 <td>1.5-T Avanto MRI scanner</td>
 <td>Siemens Medical Solutions</td>
 <td></td>
 <td></td>
 </tr>
 <tr>
 <td>FreeSurfer</td>
 <td></td>
 <td></td>
 <td><a href="http://freesurfer.net/" target="_blank">http://freesurfer.net/</a></td>
 </tr>
 <tr>
 <td>MNE software</td>
 <td></td>
 <td></td>
 <td><a href="http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/sofMNE.php" target="_blank">http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/sofMNE.php</a></td>
 </tr>
 <tr>
 <td>EEG electrodes</td>
 <td>Brain Products, Easycap GmbH</td>
 <td></td>
 <td></td>
 </tr>
 <tr>
 <td>3Space Fastrak system</td>
 <td>Polhemus</td>
 <td></td>
 <td></td>
 </tr>
 <tr>
 <td>Optical button box (FIU-932)</td>
 <td>Current Designs</td>
 <td></td>
 <td></td>
 </tr>
 </tbody>
</table>

mapping cortical dynamics using simultaneous meg/eeg and anatomically-constrained minimum-norm estimates: an auditory attention example

Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.
Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e., perform group-level analysis) based on a common cortical coordinate space.

Watch this Scientific Journal Video about Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example at JoVE.com

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

We use magneto- and electroencephalography (MEG/EEG), combined with anatomical information captured by magnetic resonance imaging (MRI), to map the dynamics of the cortical network associated with auditory attention.

Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the ...

mapping-cortical-dynamics-using-simultaneous-megeeg-anatomically

Research

JoVE Journal

Neuroscience

14.5K visualizações.  University of Washington. Usamos magneto-e eletroencefalografia (MEG / EEG), combinado com informações anatômicas capturado por ressonância magnética (MRI), para mapear a dinâmica da rede cortical associado à atenção auditiva.