CCNi

Centre for Cognitive Neuroimaging

Magnetoencephalography (MEG), similar to electroencephalography (EEG), allows for the measurement of brain signals with a high temporal resolution, providing the necessary information for the study of the temporal dynamics of cognitive processes. In addition, new techniques for source modelling (beam forming, spatial filtering) allow estimating the cortical generators (brain areas) of the signals and signal interactions of interest. In this context the time course of activation and oscillation of brain areas is of major interest. Especially the latter aspect of brain activity opens a new window of opportunity for investigating cognitive processes by studying the process-related coupling within the networks of the brain, i.e. synchronization between cortical areas. Our aims in the future will be to further develop the existing techniques for estimating the cortical generators and for studying their interaction on the one hand, and to apply these techniques to reveal the cortical implementation of the basic cognitive processes in perception, attention, memory, and language.


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In the Figure above the schematic arrangement of MEG sensors (SQUIDs; supraconducting quantum interference devices) around the head of a generic participant is depicted on the top left. Recorded raw data (lower left) are similar to EEG signals and can be averaged in a corresponding way to obtain evoked responses (equivalent to ERPs). The raw data may yet also be decomposed in time-frequency components that allow for a representation of the signal’s frequency spectrum over time (top middle). In a next step spatial filters in the frequency domain may be applied to identify the cortical generators (lower middle). Cortico-cortical interactions may then be quantified in terms of synchronization as shown on the lower right and the time course of synchronization may be compared between experimental conditions (black versus grey line).


MEG and EEG are different ways to measure the electric activity of the brain. While EEG electrodes record variations in the electric potential of neural populations in relation to a reference signal, MEG sensors measure changes in the magnetic field (gradiometers) generated by the same neural populations. The Figure below provides a scheme of how EEG and MEG relate each other (neural populations are approximated by so-called electric dipoles): EEG is particularly sensitive to potential changes in the direction of a given dipole (sensitive to radial dipoles), whereas MEG is specifically sensitive to changes in the magnetic field that surrounds the dipole (sensitive to tangential dipoles)

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Selected References
Gross J, Kujala J, Hamalainen M, Timmermann L, Schnitzler A, Salmelin R (2001) Dynamic imaging of coherent sources: Studying neural interactions in the human brain. Proc Natl Acad Sci U S A 98:694-699.

Kessler, K., Schmitz, F., Gross, J., Hommel, B., Shapiro, K., & Schnitzler, A. (2005). Target consolidation under high temporal processing demands as revealed by MEG. Neuroimage, 26, 1030-1041.

Rosenblum MG, Pikovsky AS, Kurths J (1996) Phase synchronization of chaotic oscillators. Physical Review Letters 76:1804-1807.

Hari R, Karhu J, Hamalainen M, Knuutila J, Salonen O, Sams M, Vilkman V (1993) Functional organization of the human first and second somatosensory cortices: a neuromagnetic study. Eur J Neurosci 5:724-734.
Facilities Labs MEG Suite