That MEG/EEG signals are linearly related to the current amplitude is a physical fact. After an introduction to MEG and EEG source estimation this video describes the “inverse problem” (methods, restrictions, ambiguity, common features, terminology). It means that based on the data we arrive at an approximation of the currents in the brain. Besides, current dipole models are addressed (effect of source extent, find the best-fitting dipole, etc.) along with their caveats, challenges and solving strategies.
Lecture 1: Source estimation current dipole models in MEG
Lecture 2: Frecuency analysis in neuroscience
Lecture 3: On-scalp MEG will provide ultimate spatial resolution and sensitivity
Lecture 4: Infant MEG, why and how?
The video describes how oscillations reveal aspects of brain functions. “Classic” papers are presented to show early observations and then explain: spatiotemporal rhythms analysis, microscopic/macroscopic neurophysiology, age-related changes in mu-rhythms and time-course of the phase-locked value (PLV). Following, how to extract activity with MNE (minimum norm estimates) and GLM (general linear model), conclusions about connectivity and correlation between neurophysiological and behavioural data.
This video is an introduction to M/EEG in multimodal non-invasive imaging (benefits, forward/inverse problem, interpretation of frequency bands in connectivity, sensitivity to cortical sources, etc.). Then, it summarises the evolution of MEG technology (first real-time magnetoencephalogram, developing alternative sensors, etc.) concluding with future lines: possibilities of new sensors and on-scalp meg (benefits from bringing the sensors next to the head).
First, “why” is explored and different MEG systems are presented. It is a multimodal non-invasive brain imaging technique that has benefits for baby scanning. Second, “how” is addressed: differences in infant vs. adult responses, BabyMEG characteristics, localization errors (anatomical sourcing needs manual intervention), infant M/EEG infant models and some examples. Finally, developing steps towards whole-head BabyMEG, forward models and on scalp meg are described.