Advances in electroencephalography signal processing

Saeid Sanei, Saideh Ferdowsi, Kianoush Nazarpour, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Concurrent measurement of EEG and functional magnetic resonance imaging (fMRI), provides a great opportunity to study the brain function at high spatiotemporal resolutions. Event-related potentials (ERPs), transient waves in the EEG signals, are the most important diagnostic components. An approach in detection and tracking of ERPs is by using variational Bayes (VB). A state-space method based on Kalman and particle filtering can also be employed to track the changes in amplitude and phase synchronization in the brain region. fMRI scans the whole brain at high spatial resolution of the order of millimeters and allows separation of small activity regions of the brain. The approaches for EEG-fMRI integration are classified into two main groups, model-driven and data-driven methods. In EEG-fMRI fusion based on constraints the fMRI activation map which is obtained from fMRI analyzer methods is used as a priori information for electromagnetic source localization.

Original languageEnglish
Article number6375941
Pages (from-to)170-176
Number of pages7
JournalIEEE Signal Processing Magazine
Volume30
Issue number1
DOIs
Publication statusPublished - Jan 2013
Externally publishedYes

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