Joint independent component analysis for simultaneous EEG-fMRI: Principle and simulation

被引:86
作者
Moosmann, Matthias [1 ]
Eichele, Tom [1 ]
Nordby, Helge [1 ]
Hugdahl, Kenneth [1 ,2 ]
Calhoun, Vince D. [3 ,4 ,5 ]
机构
[1] Univ Bergen, Dept Biol & Med Psychol, N-5011 Bergen, Norway
[2] Haukeland Hosp, N-5021 Bergen, Norway
[3] MIND Inst, Albuquerque, NM USA
[4] Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA
[5] Yale Univ, Sch Med, Dept Psychiat, New Haven, CT USA
关键词
EEG-fMRI; ICA; simulation; data fusion; modelling; ERP;
D O I
10.1016/j.ijpsycho.2007.05.016
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD-MRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible to identify features of latent neural sources whose trial-to-trial dynamics are jointly reflected in both modalities. We present a joint independent component analysis (jICA) model for analysis of simultaneous single trial EEG-fMRI measurements from multiple subjects. We outline the general idea underlying the jICA approach and present results from simulated data under realistic noise conditions. Our results indicate that this approach is a feasible and physiologically plausible data-driven way to achieve spatiotemporal mapping of event related responses in the human brain. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:212 / 221
页数:10
相关论文
共 58 条
[1]   A method for removing imaging artifact from continuous EEG recorded during functional MRI [J].
Allen, PJ ;
Josephs, O ;
Turner, R .
NEUROIMAGE, 2000, 12 (02) :230-239
[2]  
[Anonymous], 2005, Event-related potentials: A methods handbook
[3]   TIME COURSE EPI OF HUMAN BRAIN-FUNCTION DURING TASK ACTIVATION [J].
BANDETTINI, PA ;
WONG, EC ;
HINKS, RS ;
TIKOFSKY, RS ;
HYDE, JS .
MAGNETIC RESONANCE IN MEDICINE, 1992, 25 (02) :390-397
[4]   AN INFORMATION MAXIMIZATION APPROACH TO BLIND SEPARATION AND BLIND DECONVOLUTION [J].
BELL, AJ ;
SEJNOWSKI, TJ .
NEURAL COMPUTATION, 1995, 7 (06) :1129-1159
[5]   The ''independent components'' of natural scenes are edge filters [J].
Bell, AJ ;
Sejnowski, TJ .
VISION RESEARCH, 1997, 37 (23) :3327-3338
[6]   Single-trial analysis of oddball event-related potentials in simultaneous EEG-fMRI [J].
Benar, Christian-G. ;
Schon, Daniele ;
Grimault, Stephan ;
Nazarian, Bruno ;
Burle, Boris ;
Roth, Muriel ;
Badier, Jean-Michel ;
Marquis, Patrick ;
Liegeois-Chauvel, Catherine ;
Anton, Jean-Luc .
HUMAN BRAIN MAPPING, 2007, 28 (07) :602-613
[7]   Blind source separation of multiple signal sources of fMRI data sets using independent component analysis [J].
Biswal, BB ;
Ulmer, JL .
JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 1999, 23 (02) :265-271
[8]   Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data [J].
Calhoun, VD ;
Adali, T ;
Pearlson, GD ;
Kiehl, KA .
NEUROIMAGE, 2006, 30 (02) :544-553
[9]  
Calhoun VD, 2006, IEEE ENG MED BIOL, V25, P79, DOI 10.1109/MEMB.2006.1607672
[10]   A method for making group inferences from functional MRI data using independent component analysis [J].
Calhoun, VD ;
Adali, T ;
Pearlson, GD ;
Pekar, JJ .
HUMAN BRAIN MAPPING, 2001, 14 (03) :140-151