Localization of MEG human brain responses to retinotopic visual stimuli with contrasting source reconstruction approaches

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.

Spatial specificity of alpha oscillations in the human visual system

“…During the delay period, in the absence of an external stimulus, the spatial distribution of alpha activity reflected the participant's attended location in the visual field. In line with previous electrophysiological studies (Bahramisharif et al, 2010;Cicmil, Bridge, Parker, Woolrich, & Krug, 2014;Fahrenfort, Grubert, Olivers, & Eimer, 2017;Hagler Jr. et al, 2009;Kelly et al, 2006;Kelly, Gomez-Ramirez, & Foxe, 2009;Perry et al, 2011;Rihs et al, 2007), the present report points to a novel mechanism on the relevance of alpha activity in allocating neurocomputational resources in a spatial attention task. This mechanism relates to the notion that the spatial variability of alpha power reflects a "moving spot" of reduced alpha (Jensen, Gips, Bergmann, & Bonnefond, 2014;.…”

“…This is in line with recent findings from human and animal intracranial recordings demonstrating the spatial specificity of alpha activity in the auditory domain. Taskrelevant alpha power is differentially modulated within the auditory system in accordance with differential sound input and relates to population-level activity (de Pesters et al, 2016). Thus, the spatial tuning reported here potentially reflects the allocation of spatial attention by setting the gain in a regionally specific sense such that processing of upcoming targets are facilitated while distractors are inhibited.…”

“…Previous MEG studies have reported retinotopic organization of primary visual areas following spatially-specific visual input (Cicmil et al, 2014;Hagler Jr. et al, 2009;Perry et al, 2011 Figure 4). We suggest that F I G U R E 4 Group averaged phase maps of coronal (top) and transversal (bottom) slides.…”

“…Previous MEG studies have reported retinotopic organization of primary visual areas following spatially‐specific visual input (Cicmil et al, ; Hagler Jr. et al, ; Perry et al, ). Here we extend this literature by demonstrating retinotopic specificity beyond early visual areas in an absence of visual input, extending to parietal regions.…”

From evoked potentials to cortical currents: Resolving V1 and V2 components using retinotopy constrained source estimation without fMRI

“…Sharon et al [] combined MEG and EEG signals and constrained localization to the gray/white matter boundary segmented from a structural MRI and achieved localization to within 10 mm of an fMRI‐RL based localization. Cicmil et al [] compared localization sources of MEG signals using an anatomical MRI and Minimum Norm Estimation (MNE) [Dale et al, ; Gramfort et al, ; Hämäläinen and Ilmoniemi, ] to Beamformer [Litvak et al, ; Woolrich et al, ]. Localization accuracy in mm was not reported, however, the minimum source spacing was 4mm.…”