A simple nonparametric statistical thresholding for MEG spatial-filter source reconstruction images

• Published in: NeuroImage (Orlando, Fla.) Vol. 27; no. 2; pp. 368 - 376
• Main Authors: Sekihara, Kensuke, Sahani, Maneesh, Nagarajan, Srikantan S.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.08.2005; Elsevier Limited
• Subjects: Algorithms; Biomagnetism; Data Interpretation, Statistical; Economic models; Electromagnetic Fields; Evoked Potentials, Auditory - physiology; Humans; Hypotheses; Image Processing, Computer-Assisted - methods; Magnetic fields; Magnetoencephalography; Magnetoencephalography - methods; Magnetoencephalography - statistics & numerical data; Medical imaging; Nonparametric statistics; Spatial filter; Spatio-temporal reconstruction; Statistical threshold; Statistics, Nonparametric; Biomagnetism; Spatial filter; Magnetoencephalography; Statistical threshold; Nonparametric statistics; Spatio-temporal reconstruction
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2005.04.009

This paper proposes a simple statistical method for extracting target source activities from spatio-temporal source activities reconstructed from MEG measurements. The method requires measurements in a control condition, which contains only non-target source activities. The method derives, at each pixel location, an empirical probability distribution of the non-target source activity using the time course reconstruction obtained from the control period. The statistical threshold that can extract the target source activities is derived from the empirical distributions obtained from all pixel locations. Here, the multiple comparison problem is addressed with a two-step procedure involving standardizing these empirical distributions and deriving an empirical distribution of the maximum pseudo T value at each pixel location. The results of applying the proposed method to auditory-evoked measurements are presented to demonstrate the method's effectiveness.