MfD EEG/MEG Source Localization4th Feb 2009Maro MachizawaHimn Sabir

Expert: Vladimir Litvak

ExistenceUnicityStability

ExistenceUnicityStability

ExistenceUnicityStabilityIntroduction of prior knowledge is needed

Spatio-temporal modeling

Spatio-temporal modeling step 1Load EEG/MEG file

Spatio-temporal modeling step 2Name the analysis (optional)

Spatio-temporal modeling step 3Create/load meshesBigger the parameter, better the resolution of the results

Spatio-temporal modeling step 4Coregister fiducial points with MRIChoose either of methods to coregisterselect from default locations (at FIL)type MNI coordinates directoryclick manually each fiducial point from MRI images

Spatio-temporal modeling step 4Coregister fiducial points with MRI

Spatio-temporal modeling step 5Forward model

Spatio-temporal modeling step 5Bayesian model inversion

Spatio-temporal modeling step 5Invert: alternative modelsGS (greedy search: default): iteratively add constraints (priors)ARD (automatic relevance determination): iteratively remove irrelevant constraintsCOH (coherence): LORETA-like smooth priorIID (independent identically distributed): minimum norm

Spatio-temporal modeling step 5Invert: alternative modelsThe bigger the number, the better the model-1893-1913-1913

Spatio-temporal modeling step 5Invert: visualization options1 digit (ms): map on that time(ms)2 digits (ms): video during the period 3 digits (x y z): max. voxel on that MNI coordinate

Spatio-temporal modeling step 6Window :Induced: localization on each single trial then averagedEvoked: localization on already averaged data

INDUCED IMAGE

Spatio-temporal modeling step 7Image

Group analysis: same analysis on multiple subjects

(Optional step5)Variational Bayes Equivalent Current Dipole

Optional: time-voltage display