PMID- 29293277
OWN - NLM
STAT- MEDLINE
DCOM- 20181217
LR  - 20200613
IS  - 1097-0193 (Electronic)
IS  - 1065-9471 (Print)
IS  - 1065-9471 (Linking)
VI  - 39
IP  - 4
DP  - 2018 Apr
TI  - EEG/MEG source imaging using fMRI informed time-variant constraints.
PG  - 1700-1711
LID - 10.1002/hbm.23945 [doi]
AB  - 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.
CI  - (c) 2018 Wiley Periodicals, Inc.
FAU - Xu, Jing
AU  - Xu J
AD  - Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy 
      Ion Physics, School of Physics, Peking University, Beijing, China.
AD  - Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking 
      University, Beijing, China.
FAU - Sheng, Jingwei
AU  - Sheng J
AD  - Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy 
      Ion Physics, School of Physics, Peking University, Beijing, China.
AD  - Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking 
      University, Beijing, China.
FAU - Qian, Tianyi
AU  - Qian T
AD  - MR Collaborations NE Asia, Siemens Healthcare, Beijing, China.
FAU - Luo, Yue-Jia
AU  - Luo YJ
AD  - Shenzhen Key Laboratory of Affective and Social Cognitive Science, Institute of 
      Affective and Social Neuroscience, Shenzhen University, Shenzhen, China.
AD  - Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 
      China.
FAU - Gao, Jia-Hong
AU  - Gao JH
AUID- ORCID: 0000-0002-9311-0297
AD  - Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy 
      Ion Physics, School of Physics, Peking University, Beijing, China.
AD  - Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking 
      University, Beijing, China.
AD  - Shenzhen Key Laboratory of Affective and Social Cognitive Science, Institute of 
      Affective and Social Neuroscience, Shenzhen University, Shenzhen, China.
AD  - Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 
      China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Validation Study
DEP - 20180102
PL  - United States
TA  - Hum Brain Mapp
JT  - Human brain mapping
JID - 9419065
SB  - IM
MH  - Algorithms
MH  - Brain/diagnostic imaging/physiology
MH  - Brain Mapping/methods
MH  - Computer Simulation
MH  - Electroencephalography/*methods
MH  - Humans
MH  - Magnetic Resonance Imaging/*methods
MH  - Magnetoencephalography/*methods
MH  - Monte Carlo Method
MH  - Multimodal Imaging/*methods
MH  - Visual Perception/physiology
PMC - PMC6866534
OTO - NOTNLM
OT  - EEG
OT  - MEG
OT  - fMRI
OT  - inverse problem
OT  - mismatch
EDAT- 2018/01/03 06:00
MHDA- 2018/12/18 06:00
PMCR- 2018/01/02
CRDT- 2018/01/03 06:00
PHST- 2017/10/20 00:00 [received]
PHST- 2017/12/13 00:00 [revised]
PHST- 2017/12/21 00:00 [accepted]
PHST- 2018/01/03 06:00 [pubmed]
PHST- 2018/12/18 06:00 [medline]
PHST- 2018/01/03 06:00 [entrez]
PHST- 2018/01/02 00:00 [pmc-release]
AID - HBM23945 [pii]
AID - 10.1002/hbm.23945 [doi]
PST - ppublish
SO  - Hum Brain Mapp. 2018 Apr;39(4):1700-1711. doi: 10.1002/hbm.23945. Epub 2018 Jan 
      2.