Integration of High Resolution EEG and Functional Magnetic Resonance in the Study of Human Movement-Related Potentials
07 February 2018 (online)
Cortical sources of human movement-related potentials (i.e. unilateral finger extension) were modeled using functional magnetic resonance imaging (fMR) data as a constraint of a linear inverse source estimation from highly sampled (128 channels) EEG data. Remarkably, this estimation was performed within realistic subject’s MR-constructed head models by boundary element techniques. An appropriate figure of merit served to set the optimal amount of fMR constraints. With respect to standard linear inverse source estimates, fMR-constrained ones presented increased spatial detail and provided a more reliable timing of activation in bilateral sensorimotor cortical regions of interest.
- 1 Nunez PL. Neocortical dynamics and human EEG rhythms. New York: Oxford University Press; 1995
- 2 Babiloni F, Carducci F, Del Gratta C, Babiloni C. et al. Combined high resolution EEG and functional MRI data for modeling of cortical sources of human event-related potentials. Proceedings of EMBS98. 1998: 2303-5.
- 3 Babiloni F, Babiloni C, Carducci F. et al. A high resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subjects head model. Electroenceph Clin Neurophysiol 1997; 102: 69-80.
- 4 Grave de Peralta R, Hauk O, Gonzalez Andino S. et al. Linear inverse solution with optimal resolution kernels applied to the electromagnetic tomography. Human Brain Mapping 1997; 5: 454-67.
- 5 Woods RP, Cherry RJ, Mazziotta JC. Rapid automated algorithm for aligning and reslicing PET images. J Comput Assisted Tomogr 1992; 16: 620-33.
- 6 Kim S, Ashe J, Hendrich K. et al. A. Functional magnetic resonance imaging of motor cortex: hemispheric asymmetry and handedness. Science 1993; 261: 615-7.
- 7 Babiloni F, Del Gratta C, Carducci F. et al. Combined high resolution EEG and MEG data for linear inverse estimate of human event-related cortical activity. Proceedings of EMBS98. 1998: 2298-302.
- 8 Lawson CL, Hanson RJ. Solving least squares problems. Englewood Cliffs: Prentice Hall; 1974