MEG and EEG signals are weak and need to be summed to be detectable. Temporal summation occurs in post-synaptic activity, which is slower than the presynaptic action potentials. Spatial summation is possible thanks to dendrites of pyramidal neurons, which are perpendicular to cortical surface. Also, concepts in MEG physics: impressed, primary and return (volume) currents; signal depth, cancellation, amplitude and strength factors, dipole moment, etc.

Neurotechnology is working to maximize neuroimaging spatial and temporal resolution, but better sensors and better statistical tools are needed to make the best of the data we can have. Here, concepts of M/EEG are presented from a computer vision approach, “take home messages” (THM) are given (sensors’ locations/orientations, SNR, etc.) and analytic strategies are compared. Later, advantages of MNE (minimum norm estimates) software for M/EEG are stated as an alternative to promote sparse solutions with non-stationary sources.

Can MEG see deep? This video shows an example and several considerations about it: what is deep source localization based on MEG signals, how can we localize deep sources in the brain, how does it benefit other approaches, which particular experimental paradigm should we use, or what improvements can be done. Secondly, causality is addressed: how to get robust measures of causality on MEG signals, comparison and reliability between-subjects and the strong need for cross-validated studies.

Why High-Tc SQUIDs? MEG technology is introduced (SQUIDS, helium recycling system, etc.). In particular, the difference High-Tc SQUIDS vs. Low-Tc SQUIDS is stressed: High-Tc are simpler, cheaper, and perhaps better as well due to several reasons described (biomagnetism concepts, technologies comparison, signal-to-noise ratio, etc). The hope for this project is to validate technology in neuroscience studies, starting with the High-Tc SQUIDS based MEG findings from the studies presented.

Firstly, functional connectivity is introduced with some illustrative examples of how the brain is organised, according to functional segregation and functional integration, how to define each, and we should study both. Secondly, the topic narrows to cortical activity measures with MEG, reflecting communication between the brain activity and the periphery, so-called cortico-kinematic coherence. Thirdly, cortico-kinematic coherence in the context of movement observation is addressed.

Hight-Tc SQUIDS in MEG are introduced along with some good reasons to develop them: reducing the running cost of MEG (improve energy efficiency), get rid of helium, etc. Then, several steps are described: fabrication, testing and microstructural/electron-transport properties of graphoepitaxial high-Tc films, SQUIDS and Josephson junctions on MgO substrates. Concluding, there is the possibility that this makes the sensors cheaper (if widely used, so massively produced) and contributes to wider use of MEG.

This video highlights MEG advantages, and describes concepts like field strengths, what happens below 1Hz, coregistration, filter settings or effect of interstimuli interval. Also, several problems are described: single responses are prone to artefacts, we need reasonable localization accuracy and source differentiation, automatic methods bring surprises, etc. Last, strategies to improve performance are outlined, along with wishes for the future (i.e. adjustable whole scalp coverage).

This video explains the basis of M/EEG signals, and instrumentation, with a focus in the differences between both techniques. Firstly, some basic concepts (i.e. both techniques measure post-synaptic potentials). Secondly, instrumentation is detailed: passive/active shielding, how environmental noise is supressed with an axial gradiometer,etc. Finally, EEG and MEG are compared in detail (i.e. which currents are visible in MEG but not in EEG, or vv.).