Performance of an MEG adaptive-beamformer technique in the presence of correlated neural activities: effects on signal intensity and time-course estimates

• Published in: IEEE transactions on biomedical engineering Vol. 49; no. 12; pp. 1534 - 1546
• Main Authors: Sekihara, K., Nagarajan, S.S., Poeppel, D., Marantz, A.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.2002; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biological and medical sciences; Biomagnetics; Biomedical signal processing; Brain - physiology; Brain Mapping - methods; Computer Simulation; Distortion; Image reconstruction; Magnetoencephalography - instrumentation; Magnetoencephalography - methods; Medical sciences; Models, Neurological; Models, Statistical; Neuroimaging; Neurons - physiology; Quality Control; Radar signal processing; Reproducibility of Results; Sensitivity and Specificity; Signal analysis; Signal processing algorithms; Signal to noise ratio; Spatial filters; Statistics as Topic; Stochastic Processes; biomagnetism; Adaptive beamformer; functional neuroimaging; magnetoencephalography; neuromagnetic signal processing; magnetoencephalographic (MEG) inverse problems
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2002.805485

The influence of temporarily correlated source activities on neuromagnetic reconstruction by adaptive beamformer techniques was investigated. It is known that the spatial filter weight of an adaptive beamformer cannot perfectly block correlated signals. This causes two major influences on the reconstruction results: time course distortions and reductions in reconstructed signal intensities. Our theoretical analysis and numerical experiments both showed that the reduction in signal intensity for sources with a medium degree of correlation is small. The time-course distortion for such sources, however, may be discernible. Our analysis also showed that the magnitude correlation coefficient between two correlated sources can be accurately estimated by using the beamformer outputs. A method of retrieving the original time courses using estimated correlation coefficients was developed. Our numerical experiments demonstrated that reasonably accurate time courses can be retrieved from considerably distorted time courses even when the signal-to-noise ratio is low.