Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne.

Magnetoencephalographic (MEG) recordings are a rich source of information about the neural dynamics underlying cognitive processes in the brain, with excellent temporal and good spatial resolution. In recent years there have been considerable advances in MEG hardware developments and methods. Sophisticated analysis techniques are now routinely applied and continuously improved, leading to fascinating insights into the intricate dynamics of neural processes. However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats. Furthermore, the complexity of MEG data acquisition and data analysis requires special attention when describing MEG studies in publications, in order to facilitate interpretation and reproduction of the results. This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies. These recommendations will hopefully serve as guidelines that help to strengthen the position of the MEG research community within the field of neuroscience, and may foster discussion in order to further enhance the quality and impact of MEG research.

People are embedded in social interaction that shapes their brains throughout lifetime. Instead of emerging from lower-level cognitive functions, social interaction could be the default mode via which humans communicate with their environment. Should this hypothesis be true, it would have profound implications on how we think about brain functions and how we dissect and simulate them. We suggest that the research on the brain basis of social cognition and interaction should move from passive spectator science to studies including engaged participants and simultaneous recordings from the brains of the interacting persons.

Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalography (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the invidual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers). We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle. Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively.

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The neural correlates of consciousness are typically sought by comparing the overall brain responses to perceived and unperceived stimuli. However, this comparison may be contaminated by non-specific attention, alerting, performance, and reporting confounds. Here, we pursue a novel approach, tracking the neuronal coding of consciously and unconsciously perceived contents while keeping behavior identical (blindsight). EEG and MEG were recorded while participants reported the spatial location and visibility of a briefly presented target. Multivariate pattern analysis demonstrated that considerable information about spatial location traverses the cortex on blindsight trials, but that starting ≈270 ms post-onset, information unique to consciously perceived stimuli, emerges in superior parietal and superior frontal regions. Conscious access appears characterized by the entry of the perceived stimulus into a series of additional brain processes, each restricted in time, while the failure of conscious access results in the breaking of this chain and a subsequent slow decay of the lingering unconscious activity.DOI: http://dx.doi.org/10.7554/eLife.05652.001

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Most neuroimaging studies are performed using one imaging method only, either functional magnetic resonance imaging (fMRI), electroencephalography (EEG), or magnetoencephalography (MEG). Information on both location and timing has been sought by recording fMRI and EEG, simultaneously, or MEG and fMRI in separate sessions. Such approaches assume similar active areas whether detected via hemodynamic or electrophysiological signatures. Direct comparisons, after independent analysis of data from each imaging modality, have been conducted primarily on low-level sensory processing. Here, we report MEG (timing and location) and fMRI (location) results in 11 subjects when they named pictures that depicted an action or an object. The experimental design was exactly the same for the two imaging modalities. The MEG data were analyzed with two standard approaches: a set of equivalent current dipoles and a distributed minimum norm estimate. The fMRI blood-oxygen-level dependent (BOLD) data were subjected to the usual random-effect contrast analysis. At the group level, MEG and fMRI data showed fairly good convergence, with both overall activation patterns and task effects localizing to comparable cortical regions. There were some systematic discrepancies, however, and the correspondence was less compelling in the individual subjects. The present analysis should be helpful in reconciling results of fMRI and MEG studies on high-level cognitive functions.