Imaging brain synchrony at high spatio-temporal resolution: application to MEG signals during absence seizures

Abstract

Imaging the dynamics of distributed phase synchrony across brain signals is of crucial importance for the study of large-scale interactions in the brain, and requires combining at the same time, wide coverage of the brain with high spatial and temporal resolution. Electro- and magneto-encephalography (EEG–MEG), which provide full head coverage measurements of the human brain activity, can potentially satisfy those needs. Nevertheless, EEG–MEG signals reflects the integration of separately generated brain processes on the scalp that typically overlap in space and give rise to spurious phase-locking between their signals. Moreover, current phase synchronization measures do not have a sufficient time resolution to capture very brief periods of phase locking between brain signals, because of their dependence on a window of time integration. We present here a new, non-invasive technique for characterizing the phase synchronization between brain regions at high spatial and temporal resolution. An efficient inverse problem algorithm was used to estimate, from the MEG signals and with the help of the anatomical MRI, the corresponding intracranial brain sources on the cortical surface. The synchronization analysis was then directly performed on the cortex by the characterization of common instantaneous frequencies between groups of cortical sources which preserve a fine temporal resolution. The proposed method was illustrated by its application to MEG data recorded during absence seizures in two epileptic patients. The technique visualizes local and short-lasting synchronization patterns leading to the seizure, thus providing new potential for understanding non-invasively the origin of epileptic discharges.