1 / 14

Functional Brain Signal Processing: EEG & fMRI Lesson 18

M.Tech. (CS), Semester III, Course B50. Functional Brain Signal Processing: EEG & fMRI Lesson 18. Kaushik Majumdar Indian Statistical Institute Bangalore Center kmajumdar@isibang.ac.in. Equipment and Acquisition.

hamilton-vinson
Download Presentation

Functional Brain Signal Processing: EEG & fMRI Lesson 18

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. M.Tech. (CS), Semester III, Course B50 Functional Brain Signal Processing: EEG & fMRILesson 18 Kaushik Majumdar Indian Statistical Institute Bangalore Center kmajumdar@isibang.ac.in

  2. Equipment and Acquisition • EEG electrodes to reduce eddy current by adding 5 to 10 kohm for 1.5 T fMRI scanner and/or using specialized materials for making them. • Reducing artifacts in EEG signals due to the induced current. • Reducing heat due to induced current, which may cause burn on the skin of the subject.

  3. Equipment and Acquisition (cont) • Every fMRI scanner is equipped with a very sensitive RF detector. If EEG equipment produces any RF wave that would contaminate the fMRI signal. To avoid this amplifier/digitizer can be run on battery. • Water based electrode gels proofed to produce negligible chemical shift artifacts on the scalp surface.

  4. Equipment and Acquisition (cont) • High sampling rate (1 to 5 kH) for EEG is required for good modeling of MR artifacts. • Helium pump and other unnecessary apparatus should be kept switched off during acquisition to avoid noise due to those equipments. • Digitized signal to be carried out of the shielded room through optical fibers to preserve isolation of the MR scanner.

  5. Equipment and Acquisition (cont) • To reduce residual artifacts in EEG due to MR scanning following must be adhered to: (1) MR volume acquisition must be stable in time (always equal time lag in between any two successive volume acquisition). (2) MR device and EEG amplifier will have to be synchronized.

  6. EEG and fMRI Data Fusion • A brain region may have a large metabolic load without measurable EEG generation. This can happen in deep brain region from where EEG will not reach to the electrodes on the scalp. EEG activity tangential to the scalp or opposing and self-canceling sources in the sulci may have substantial metabolic demand without significant EEG manifestation.

  7. EEG and fMRI Data Fusion (cont) • Inhibitory neuronal (for example GABA-ergic stellate cells, which do not generate measurable EEG due to concentric configuration) activities on fMRI are unpredictable. • A relatively small fraction of synchronously firing neurons may generate a measurable EEG on the scalp without a strong enough hemodynamic activity.

  8. Linden et al., 1999 EEG and fMRI Data Fusion (cont) • An increase in neuronal synchrony associated with a decrease in synaptic transmission will be associated with higher EEG amplitudes and a negative fMRI signal. BOLD response to T = target and N = non-target.

  9. Linden et al., 1999 Evoked Potential During the Same Task of the Preceding Slide Event related potential during visual odd-ball task. Black line for targets and grey for non-targets.

  10. Benar et al., 2002 BOLD Response to Interictal Epileptic Discharges Arrows indicate interictal epileptic discharges.

  11. Liu et al., 1998 fMRI Localization of EEG/MEG Sources Simultaneous EEG-fMRI significantly improves source localization of EEG over the classical dipole source estimation. A. K. Liu et al., PNAS, 95(5): 8945 – 8950, 1998.

  12. Hanson et al., 2007 Converting EEG to RF Range to be Detected by MR Scanner

  13. References • P. Ritter and A. Villringer, Simultaneous EEG-fMRI, Neurosci. Behav. Rev., 30: 823 – 838, 2006. • http://fsl.fmrib.ox.ac.uk/eeglab/fmribplugin/ Artifact removal toolbox based on MATLAB. For the detail of algorithms see R. K. Niazy et al., Removal of FMRI environment artifacts from EEG data using optimal basis set, NeuroImage, 28: 720 – 737, 2005.

  14. THANK YOUThis lecture is available at http://www.isibang.ac.in/~kaushik

More Related