Abstract
Magnetoencephalography (MEG) allows the physiological recording of human brain activity at high temporal resolution. However, spatial localization of the source of the MEG signal is an ill-posed problem as the signal alone cannot constrain a unique solution and additional prior assumptions must be enforced. An adequate source reconstruction method for investigating the human visual system should place the sources of early visual activity in known locations in the occipital cortex. We localized sources of retinotopic MEG signals from the human brain with contrasting reconstruction approaches (minimum norm, multiple sparse priors, and beamformer) and compared these to the visual retinotopic map obtained with fMRI in the same individuals. When reconstructing brain responses to visual stimuli that differed by angular position, we found reliable localization to the appropriate retinotopic visual field quadrant by a minimum norm approach and by beamforming. Retinotopic map eccentricity in accordance with the fMRI map could not consistently be localized using an annular stimulus with any reconstruction method, but confining eccentricity stimuli to one visual field quadrant resulted in significant improvement with the minimum norm. These results inform the application of source analysis approaches for future MEG studies of the visual system, and indicate some current limits on localization accuracy of MEG signals.
Highlights
Magnetoencephalography (MEG) measures magnetic fields emitted by neuronal electrical activity and allows the noninvasive recording of neuronal signals with millisecond temporal resolution (Hämäläinen et al, 1993)
We focused on three methods included in freely available software packages: minimum norm (Minimum Norm Estimate, MGH/MIT Martinos Centre for Biomedical Imaging; Dale et al, 2000; Gramfort et al, 2014), multiple sparse priors (MSP in SPM8 software, FIL Methods Group, UCL; Litvak et al, 2011), and beamforming
LOCALIZATION OF VISUALLY EVOKED RESPONSES TO ANGULAR RETINOTOPIC STIMULI Contrast-reversing checkerboard quadrant stimuli were presented to six human observers and the evoked brain responses were measured with MEG
Summary
Magnetoencephalography (MEG) measures magnetic fields emitted by neuronal electrical activity and allows the noninvasive recording of neuronal signals with millisecond temporal resolution (Hämäläinen et al, 1993). A current approach to overcome this limitation is to impose prior constraints on the source solution, informed by assumptions about the brain activity patterns that give rise to the MEG signal. Brain activity can be assumed to be sparse, i.e., occurring in discrete cortical “patches”, which in certain tasks may have a bilaterally correlated response (Pascual-Marqui et al, 1994). These sparseness and correlation parameters can be inferred from the data using Bayesian techniques, for example in the multiple sparse priors approach (Mattout et al, 2007; Friston et al, 2008; Henson et al, 2009). Related algorithms have been the basis of other source reconstruction approaches (Moradi et al, 2003; Poghosyan and Ioannides, 2007; Cottereau et al, 2011)
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