Concurrent EEG/fMRI analysis by multiway Partial Least Squares

被引:218
|
作者
Martínez-Montes, E
Valdés-Sosa, PA
Miwakeichi, F
Goldman, RI
Cohen, MS
机构
[1] Cuban Neurosci Ctr, Neurophys Dept, Havana, Cuba
[2] RIKEN, Brain Sci Inst, Lab Dynam Emergent Intelligence, Wako, Saitama 35101, Japan
[3] Columbia Univ, Hatch Ctr MR Res, New York, NY 10032 USA
[4] Univ Calif Los Angeles, Sch Med, Ahmanson Lovelace Brain Mapping Ctr, Los Angeles, CA 90095 USA
关键词
N-PLS; EEG/fMRI fusion; PARAFAC; multiway analysis; SSI; SITE;
D O I
10.1016/j.neuroimage.2004.03.038
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Data may now be recorded concurrently from EEG and functional MRI, using the Simultaneous Imaging for Tomographic Electrophysiology (SITE) method. As yet, there is no established means to integrate the analysis of the combined data set. Recognizing that the hemodynamically convolved time-varying EEG spectrum, S, is intrinsically multidimensional in space, frequency, and time motivated us to use multiway Partial Least-Squares (N-PLS) analysis to decompose EEG (independent variable) and fMRI (dependent variable) data uniquely as a sum of "atoms". Each EEG atom is the outer product of spatial, spectral, and temporal signatures and each fMRI atom the product of spatial and temporal signatures. The decomposition was constrained to maximize the covariance between corresponding temporal signatures of the EEG and fMRI. On all data sets, three components whose spectral peaks were in the theta, alpha, and gamma bands appeared; only the alpha atom had a significant temporal correlation with the fMRI signal. The spatial distribution of the alpha-band atom included parieto-occipital cortex, thalamus, and insula, and corresponded closely to that reported by Goldman et al. [NeuroReport 13(18) (2002) 2487] using a more conventional analysis. The source reconstruction from EEG spatial signature showed only the parieto-occipital sources. We interpret these results to indicate that some electrical sources may be intrinsically invisible to scalp EEG, yet may be revealed through conjoint analysis of EEG and fMRI data. These results may also expose brain regions that participate in the control of brain rhythms but may not themselves be generators. As of yet, no single neuroimaging method offers the optimal combination of spatial and temporal resolution; fusing fMRI and EEG meaningfully extends the spatio-temporal resolution and sensitivity of each method. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:1023 / 1034
页数:12
相关论文
共 50 条
  • [1] Concurrent EEG/fMRI analysis by multiway partial least squares (vol 22, pg 1023, 2004)
    Martínez-Montes, E
    Valdés-Sosa, PA
    Miwakeichi, F
    Goldman, RI
    Cohen, MS
    NEUROIMAGE, 2005, 26 (03) : 973 - 973
  • [2] INTERACTIVE INTERICTAL SPIKE DETECTION SOFTWARE FOR SIMULTANEOUS EEG-FMRI DATA USING MULTIWAY PARTIAL LEAST SQUARES
    Negishi, Michiro
    Novotny, E. J.
    Spencer, D. D.
    Constable, R. T.
    EPILEPSIA, 2009, 50 : 445 - 446
  • [3] Fast Multiway Partial Least Squares Regression
    Camarrone, Flavio
    Van Hulle, Marc M.
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2019, 66 (02) : 433 - 443
  • [4] Fusion of EEG topograhic features and fMRI using Canonical Partial Least Squares
    Michalopoulos, Kostas
    Bourbakis, Nikolaos
    2014 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE), 2014, : 297 - 303
  • [5] Multivariate analysis of fMRI data by oriented partial least squares
    Rayens, William S.
    Andersen, Anders H.
    MAGNETIC RESONANCE IMAGING, 2006, 24 (07) : 953 - 958
  • [6] Partial least squares for discrimination in fMRI data
    Andersen, Anders H.
    Rayens, William S.
    Liu, Yushu
    Smith, Charles D.
    MAGNETIC RESONANCE IMAGING, 2012, 20 (03) : 446 - 452
  • [7] Multiway Interval Partial Least Squares for Batch Process Performance Monitoring
    Stubbs, Shallon
    Zhang, Jie
    Morris, Julian
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2013, 52 (35) : 12399 - 12407
  • [8] Nonlinear Analysis for Motor Imagery EEG based Kernel Partial Least Squares
    Bao, Xuecai
    Mu, Zhendong
    Hu, Jianfeng
    ICIEA: 2009 4TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-6, 2009, : 2097 - 2100
  • [9] Spatiotemporal analysis of event-related fMRI data using partial least squares
    McIntosh, AR
    Chau, W
    Protzner, AB
    NEUROIMAGE, 2004, 23 (02) : 764 - 775
  • [10] The canonical partial least squares approach to analysing multiway datasets-N-CPLS
    Liland, Kristian Hovde
    Indahl, Ulf Geir
    Skogholt, Joakim
    Mishra, Puneet
    JOURNAL OF CHEMOMETRICS, 2022, 36 (07)