EEG/MEG source imaging using fMRI informed time‐variant constraints

EEG/MEG source imaging using fMRI informed time‐variant constraints Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) or magnetoencephalography (MEG) is able to provide high spatiotemporal resolution mapping of brain activity. However, the accuracy of fMRI‐constrained EEG/MEG source imaging may be degraded by potential spatial mismatches between the locations of fMRI activation and electrical source activities. To address this problem, we propose a novel fMRI informed time‐variant constraint (FITC) method. The weights in FITC are determined by combining the fMRI activities and electrical source activities in a time‐variant manner to reduce the impact of the fMRI extra sources. The fMRI weights are modified using cross‐talk matrix and normalized partial area under the curve to reduce the impact of fMRI missing sources. Monte Carlo simulations were performed to compare the source estimates produced by L2‐minimum norm estimation (MNE), fMRI‐weighted minimum norm estimation (fMNE), FITC, and depth‐weighted FITC (wFITC) algorithms with various spatial mismatch conditions. Localization error and temporal correlation were calculated to compare the four algorithms under different conditions. The simulation results indicated that the FITC and wFITC methods were more robust than the MNE and fMNE algorithms. Moreover, FITC and wFITC were significantly better than fMNE under the fMRI missing sources condition. A human visual‐stimulus EEG, MEG, and fMRI test was performed, and the experimental data revealed that FITC and wFITC displayed more focal areas than fMNE and MNE. In conclusion, the proposed FITC method is able to better resolve the spatial mismatch problems encountered in fMRI‐constrained EEG/MEG source imaging. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Human Brain Mapping Wiley

EEG/MEG source imaging using fMRI informed time‐variant constraints

Loading next page...
 
/lp/wiley/eeg-meg-source-imaging-using-fmri-informed-time-variant-constraints-RLaTqttODa
Publisher
Wiley
Copyright
© 2018 Wiley Periodicals, Inc.
ISSN
1065-9471
eISSN
1097-0193
D.O.I.
10.1002/hbm.23945
Publisher site
See Article on Publisher Site

Abstract

Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) or magnetoencephalography (MEG) is able to provide high spatiotemporal resolution mapping of brain activity. However, the accuracy of fMRI‐constrained EEG/MEG source imaging may be degraded by potential spatial mismatches between the locations of fMRI activation and electrical source activities. To address this problem, we propose a novel fMRI informed time‐variant constraint (FITC) method. The weights in FITC are determined by combining the fMRI activities and electrical source activities in a time‐variant manner to reduce the impact of the fMRI extra sources. The fMRI weights are modified using cross‐talk matrix and normalized partial area under the curve to reduce the impact of fMRI missing sources. Monte Carlo simulations were performed to compare the source estimates produced by L2‐minimum norm estimation (MNE), fMRI‐weighted minimum norm estimation (fMNE), FITC, and depth‐weighted FITC (wFITC) algorithms with various spatial mismatch conditions. Localization error and temporal correlation were calculated to compare the four algorithms under different conditions. The simulation results indicated that the FITC and wFITC methods were more robust than the MNE and fMNE algorithms. Moreover, FITC and wFITC were significantly better than fMNE under the fMRI missing sources condition. A human visual‐stimulus EEG, MEG, and fMRI test was performed, and the experimental data revealed that FITC and wFITC displayed more focal areas than fMNE and MNE. In conclusion, the proposed FITC method is able to better resolve the spatial mismatch problems encountered in fMRI‐constrained EEG/MEG source imaging.

Journal

Human Brain MappingWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off